From 63c4da0586e2575d6d14a3e537ccb64863a13f78 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 28 Jul 2023 23:26:38 +0800 Subject: [PATCH 01/50] fix: avoid potential panic in `two_complement` (#2081) --- .../src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index 18c7216a6fa..eb8938b0182 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -248,8 +248,11 @@ impl GeneratedAcir { ) -> Expression { let max_power_of_two = FieldElement::from(2_i128).pow(&FieldElement::from(max_bit_size as i128 - 1)); - let inter = &(&Expression::from_field(max_power_of_two) - lhs) * &leading.into(); - lhs.add_mul(FieldElement::from(2_i128), &inter.unwrap()) + + let intermediate = + self.mul_with_witness(&(&Expression::from(max_power_of_two) - lhs), &leading.into()); + + lhs.add_mul(FieldElement::from(2_i128), &intermediate) } /// Returns an expression which represents `lhs * rhs` From c21e63f7776bc080e64fae60915234d678b6df7b Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Fri, 28 Jul 2023 17:31:32 +0200 Subject: [PATCH 02/50] chore: document truncate (#2082) document trauncate --- .../src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs | 2 ++ 1 file changed, 2 insertions(+) diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index 2fdfb0bd10f..8c7fe1e9b6a 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -579,6 +579,8 @@ impl AcirContext { } /// Returns an `AcirVar` which will be constrained to be lhs mod 2^{rhs} + /// In order to do this, we simply perform euclidian division of lhs by 2^{rhs} + /// The remainder of the division is then lhs mod 2^{rhs} pub(crate) fn truncate_var( &mut self, lhs: AcirVar, From 9f3198efc77c308028f761175da4fe3659f70579 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 28 Jul 2023 23:39:04 +0800 Subject: [PATCH 03/50] feat: Remove an unnecessary witness in `mul_with_witness` (#2078) --- .../acir_gen/acir_ir/generated_acir.rs | 18 +++++++++++------- 1 file changed, 11 insertions(+), 7 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index eb8938b0182..d80537a074a 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -260,7 +260,7 @@ impl GeneratedAcir { /// If one has multiplicative term and the other is of degree one or more, /// the function creates [intermediate variables][`Witness`] accordingly. /// There are two cases where we can optimize the multiplication between two expressions: - /// 1. If both expressions have at most a total degree of 1 in each term, then we can just multiply them + /// 1. If the sum of the degrees of both expressions is at most 2, then we can just multiply them /// as each term in the result will be degree-2. /// 2. If one expression is a constant, then we can just multiply the constant with the other expression /// @@ -271,10 +271,14 @@ impl GeneratedAcir { let lhs_is_linear = lhs.is_linear(); let rhs_is_linear = rhs.is_linear(); - // Case 1: Both expressions have at most a total degree of 1 in each term - if lhs_is_linear && rhs_is_linear { - return (lhs * rhs) - .expect("one of the expressions is a constant and so this should not fail"); + // Case 1: The sum of the degrees of both expressions is at most 2. + // + // If one of the expressions is constant then it does not increase the degree when multiplying by another expression. + // If both of the expressions are linear (degree <=1) then the product will be at most degree 2. + let both_are_linear = lhs_is_linear && rhs_is_linear; + let either_is_const = lhs.is_const() || rhs.is_const(); + if both_are_linear || either_is_const { + return (lhs * rhs).expect("Both expressions are degree <= 1"); } // Case 2: One or both of the sides needs to be reduced to a degree-1 univariate polynomial @@ -288,7 +292,7 @@ impl GeneratedAcir { // rhs, we only need to square the lhs. if lhs == rhs { return (&*lhs_reduced * &*lhs_reduced) - .expect("Both expressions are reduced to be degree<=1"); + .expect("Both expressions are reduced to be degree <= 1"); }; let rhs_reduced = if rhs_is_linear { @@ -297,7 +301,7 @@ impl GeneratedAcir { Cow::Owned(self.get_or_create_witness(rhs).into()) }; - (&*lhs_reduced * &*rhs_reduced).expect("Both expressions are reduced to be degree<=1") + (&*lhs_reduced * &*rhs_reduced).expect("Both expressions are reduced to be degree <= 1") } /// Signed division lhs / rhs From ef91286b920fb3e17c7368839a93ccad2441edc8 Mon Sep 17 00:00:00 2001 From: jfecher Date: Fri, 28 Jul 2023 12:26:35 -0500 Subject: [PATCH 04/50] feat: Make arrays and slices polymorphic over each other (#2070) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Start experiment to merge array and slice types * Finish merger of slices and arrays * Implement missing try_bind function * Add missed case for NotConstant * Fix some tests * Fix poseidon test * Fix evaluation of slice length * Fix tests * fix: Slice initialization (#2080) * fix: Initialize Value::Array of type Slice * test: improved brillig test after bug fix * Add array -> slice coercion * Update comment * Clippy suggestion * Use coercions in more places to match rust --------- Co-authored-by: Álvaro Rodríguez --- .../tests/test_data/array_len/src/main.nr | 6 +- .../test_data/brillig_slices/src/main.nr | 98 +++--- .../tests/test_data/slices/src/main.nr | 4 +- .../src/brillig/brillig_gen/brillig_block.rs | 31 +- .../src/ssa_refactor/acir_gen/mod.rs | 3 +- .../src/ssa_refactor/ir/dfg.rs | 35 +-- .../src/ssa_refactor/ir/function_inserter.rs | 6 +- .../src/ssa_refactor/ir/instruction.rs | 18 +- .../src/ssa_refactor/ir/value.rs | 10 +- .../src/ssa_refactor/opt/constant_folding.rs | 7 +- .../src/ssa_refactor/opt/flatten_cfg.rs | 32 +- .../src/ssa_refactor/opt/inlining.rs | 4 +- .../src/ssa_refactor/opt/mem2reg.rs | 5 +- .../src/ssa_refactor/ssa_builder/mod.rs | 11 +- .../src/ssa_refactor/ssa_gen/mod.rs | 20 +- .../src/hir/resolution/resolver.rs | 16 +- .../noirc_frontend/src/hir/type_check/expr.rs | 54 ++-- .../noirc_frontend/src/hir/type_check/mod.rs | 22 +- .../noirc_frontend/src/hir/type_check/stmt.rs | 5 +- crates/noirc_frontend/src/hir_def/types.rs | 283 +++++++++++++++--- .../src/monomorphization/ast.rs | 2 +- .../src/monomorphization/mod.rs | 116 ++++--- crates/noirc_frontend/src/node_interner.rs | 3 +- noir_stdlib/src/array.nr | 9 + noir_stdlib/src/ecdsa_secp256k1.nr | 2 +- noir_stdlib/src/ecdsa_secp256r1.nr | 2 +- noir_stdlib/src/hash/poseidon.nr | 2 +- noir_stdlib/src/merkle.nr | 4 +- noir_stdlib/src/schnorr.nr | 2 +- noir_stdlib/src/slice.nr | 69 ----- 30 files changed, 516 insertions(+), 365 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/array_len/src/main.nr b/crates/nargo_cli/tests/test_data/array_len/src/main.nr index 9099cfa2144..2c3cc0aee60 100644 --- a/crates/nargo_cli/tests/test_data/array_len/src/main.nr +++ b/crates/nargo_cli/tests/test_data/array_len/src/main.nr @@ -1,14 +1,14 @@ use dep::std; -fn len_plus_1(array: [T]) -> Field { +fn len_plus_1(array: [T; N]) -> Field { array.len() + 1 } -fn add_lens(a: [T], b: [Field]) -> Field { +fn add_lens(a: [T; N], b: [Field; M]) -> Field { a.len() + b.len() } -fn nested_call(b: [Field]) -> Field { +fn nested_call(b: [Field; N]) -> Field { len_plus_1(b) } diff --git a/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr index 7e4e8729199..34a9afcd515 100644 --- a/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr +++ b/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr @@ -2,71 +2,75 @@ use dep::std::slice; use dep::std; unconstrained fn main(x: Field, y: Field) { - // Mark it as mut so the compiler doesn't simplify the following operations - // But don't reuse the mut slice variable until this is fixed https://github.com/noir-lang/noir/issues/1931 - let slice: [Field] = [y, x]; + let mut slice: [Field] = [y, x]; assert(slice.len() == 2); - let mut pushed_back_slice = slice.push_back(7); - assert(pushed_back_slice.len() == 3); - assert(pushed_back_slice[0] == y); - assert(pushed_back_slice[1] == x); - assert(pushed_back_slice[2] == 7); + slice = slice.push_back(7); + assert(slice.len() == 3); + assert(slice[0] == y); + assert(slice[1] == x); + assert(slice[2] == 7); // Array set on slice target - pushed_back_slice[0] = x; - pushed_back_slice[1] = y; - pushed_back_slice[2] = 1; - - assert(pushed_back_slice[0] == x); - assert(pushed_back_slice[1] == y); - assert(pushed_back_slice[2] == 1); - - assert(slice.len() == 2); - - let pushed_front_slice = pushed_back_slice.push_front(2); - assert(pushed_front_slice.len() == 4); - assert(pushed_front_slice[0] == 2); - assert(pushed_front_slice[1] == x); - assert(pushed_front_slice[2] == y); - assert(pushed_front_slice[3] == 1); - - let (item, popped_front_slice) = pushed_front_slice.pop_front(); + slice[0] = x; + slice[1] = y; + slice[2] = 1; + + assert(slice[0] == x); + assert(slice[1] == y); + assert(slice[2] == 1); + + slice = push_front_to_slice(slice, 2); + assert(slice.len() == 4); + assert(slice[0] == 2); + assert(slice[1] == x); + assert(slice[2] == y); + assert(slice[3] == 1); + + let (item, popped_front_slice) = slice.pop_front(); + slice = popped_front_slice; assert(item == 2); - assert(popped_front_slice.len() == 3); - assert(popped_front_slice[0] == x); - assert(popped_front_slice[1] == y); - assert(popped_front_slice[2] == 1); + assert(slice.len() == 3); + assert(slice[0] == x); + assert(slice[1] == y); + assert(slice[2] == 1); - let (popped_back_slice, another_item) = popped_front_slice.pop_back(); + let (popped_back_slice, another_item) = slice.pop_back(); + slice = popped_back_slice; assert(another_item == 1); - assert(popped_back_slice.len() == 2); - assert(popped_back_slice[0] == x); - assert(popped_back_slice[1] == y); + assert(slice.len() == 2); + assert(slice[0] == x); + assert(slice[1] == y); - let inserted_slice = popped_back_slice.insert(1, 2); - assert(inserted_slice.len() == 3); - assert(inserted_slice[0] == x); - assert(inserted_slice[1] == 2); - assert(inserted_slice[2] == y); + slice = slice.insert(1, 2); + assert(slice.len() == 3); + assert(slice[0] == x); + assert(slice[1] == 2); + assert(slice[2] == y); - let (removed_slice, should_be_2) = inserted_slice.remove(1); + let (removed_slice, should_be_2) = slice.remove(1); + slice = removed_slice; assert(should_be_2 == 2); - assert(removed_slice.len() == 2); - assert(removed_slice[0] == x); - assert(removed_slice[1] == y); + assert(slice.len() == 2); + assert(slice[0] == x); + assert(slice[1] == y); - let (slice_with_only_x, should_be_y) = removed_slice.remove(1); + let (slice_with_only_x, should_be_y) = slice.remove(1); + slice = slice_with_only_x; assert(should_be_y == y); - assert(slice_with_only_x.len() == 1); - assert(removed_slice[0] == x); + assert(slice.len() == 1); + assert(slice[0] == x); - let (empty_slice, should_be_x) = slice_with_only_x.remove(0); + let (empty_slice, should_be_x) = slice.remove(0); assert(should_be_x == x); assert(empty_slice.len() == 0); } +// Tests slice passing to/from functions +unconstrained fn push_front_to_slice(slice: [T], item: T) -> [T] { + slice.push_front(item) +} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/slices/src/main.nr b/crates/nargo_cli/tests/test_data/slices/src/main.nr index a0460aafb40..f97078a2143 100644 --- a/crates/nargo_cli/tests/test_data/slices/src/main.nr +++ b/crates/nargo_cli/tests/test_data/slices/src/main.nr @@ -4,7 +4,7 @@ fn main(x : Field, y : pub Field) { /// TODO(#1889): Using slices in if statements where the condition is a witness /// is not yet supported - let mut slice: [Field] = [0; 2]; + let mut slice = [0; 2]; assert(slice[0] == 0); assert(slice[0] != 1); slice[0] = x; @@ -15,7 +15,7 @@ fn main(x : Field, y : pub Field) { assert(slice_plus_10[2] != 8); assert(slice_plus_10.len() == 3); - let mut new_slice: [Field] = []; + let mut new_slice = []; for i in 0..5 { new_slice = new_slice.push_back(i); } diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs index 4de052aad9d..c7779533a8a 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs @@ -800,10 +800,29 @@ impl<'block> BrilligBlock<'block> { value_id, dfg, ); - let heap_array = self.function_context.extract_heap_array(new_variable); - self.brillig_context - .allocate_fixed_length_array(heap_array.pointer, heap_array.size); + // Initialize the variable + let pointer = match new_variable { + RegisterOrMemory::HeapArray(heap_array) => { + self.brillig_context + .allocate_fixed_length_array(heap_array.pointer, array.len()); + + heap_array.pointer + } + RegisterOrMemory::HeapVector(heap_vector) => { + self.brillig_context + .const_instruction(heap_vector.size, array.len().into()); + self.brillig_context + .allocate_array_instruction(heap_vector.pointer, heap_vector.size); + + heap_vector.pointer + } + _ => unreachable!( + "ICE: Cannot initialize array value created as {new_variable:?}" + ), + }; + + // Write the items // Allocate a register for the iterator let iterator_register = self.brillig_context.make_constant(0_usize.into()); @@ -811,11 +830,7 @@ impl<'block> BrilligBlock<'block> { for element_id in array.iter() { let element_variable = self.convert_ssa_value(*element_id, dfg); // Store the item in memory - self.store_variable_in_array( - heap_array.pointer, - iterator_register, - element_variable, - ); + self.store_variable_in_array(pointer, iterator_register, element_variable); // Increment the iterator self.brillig_context.usize_op_in_place(iterator_register, BinaryIntOp::Add, 1); } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index b0ade9419fe..3bf18a2d86a 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -1057,7 +1057,8 @@ mod tests { let one = builder.field_constant(FieldElement::one()); let element_type = Rc::new(vec![Type::field()]); - let array = builder.array_constant(im::Vector::unit(one), element_type); + let array_type = Type::Array(element_type, 1); + let array = builder.array_constant(im::Vector::unit(one), array_type); builder.terminate_with_return(vec![array]); diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs index 5c9fde280a8..caf65c85a7e 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs @@ -1,4 +1,4 @@ -use std::{borrow::Cow, collections::HashMap, rc::Rc}; +use std::{borrow::Cow, collections::HashMap}; use crate::ssa_refactor::ir::instruction::SimplifyResult; @@ -9,7 +9,7 @@ use super::{ Instruction, InstructionId, InstructionResultType, Intrinsic, TerminatorInstruction, }, map::DenseMap, - types::{CompositeType, Type}, + types::Type, value::{Value, ValueId}, }; @@ -226,12 +226,9 @@ impl DataFlowGraph { } /// Create a new constant array value from the given elements - pub(crate) fn make_array( - &mut self, - array: im::Vector, - element_type: Rc, - ) -> ValueId { - self.make_value(Value::Array { array, element_type }) + pub(crate) fn make_array(&mut self, array: im::Vector, typ: Type) -> ValueId { + assert!(matches!(typ, Type::Array(..) | Type::Slice(_))); + self.make_value(Value::Array { array, typ }) } /// Gets or creates a ValueId for the given FunctionId. @@ -369,27 +366,19 @@ impl DataFlowGraph { /// Returns the Value::Array associated with this ValueId if it refers to an array constant. /// Otherwise, this returns None. - pub(crate) fn get_array_constant( - &self, - value: ValueId, - ) -> Option<(im::Vector, Rc)> { + pub(crate) fn get_array_constant(&self, value: ValueId) -> Option<(im::Vector, Type)> { match &self.values[self.resolve(value)] { // Vectors are shared, so cloning them is cheap - Value::Array { array, element_type } => Some((array.clone(), element_type.clone())), + Value::Array { array, typ } => Some((array.clone(), typ.clone())), _ => None, } } - /// Returns the Type::Array associated with this ValueId if it refers to an array parameter. - /// Otherwise, this returns None. - pub(crate) fn get_array_parameter_type( - &self, - value: ValueId, - ) -> Option<(Rc, usize)> { - match &self.values[self.resolve(value)] { - Value::Param { typ: Type::Array(element_type, size), .. } => { - Some((element_type.clone(), *size)) - } + /// If this value is an array, return the length of the array as indicated by its type. + /// Otherwise, return None. + pub(crate) fn try_get_array_length(&self, value: ValueId) -> Option { + match self.type_of_value(value) { + Type::Array(_, length) => Some(length), _ => None, } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs index 22a1399ae79..38dcfbbb168 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs @@ -33,11 +33,11 @@ impl<'f> FunctionInserter<'f> { match self.values.get(&value) { Some(value) => *value, None => match &self.function.dfg[value] { - super::value::Value::Array { array, element_type } => { + super::value::Value::Array { array, typ } => { let array = array.clone(); - let element_type = element_type.clone(); + let typ = typ.clone(); let new_array = array.iter().map(|id| self.resolve(*id)).collect(); - let new_id = self.function.dfg.make_array(new_array, element_type); + let new_id = self.function.dfg.make_array(new_array, typ); self.values.insert(value, new_id); new_id } diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs index 416c53ba6b4..b7a3ea02ae9 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs @@ -420,15 +420,9 @@ fn simplify_call(func: ValueId, arguments: &[ValueId], dfg: &mut DataFlowGraph) Intrinsic::ArrayLen => { let slice = dfg.get_array_constant(arguments[0]); if let Some((slice, _)) = slice { - let slice_len = - dfg.make_constant(FieldElement::from(slice.len() as u128), Type::field()); - SimplifiedTo(slice_len) - } else if let Some((_, slice_len)) = dfg.get_array_parameter_type(arguments[0]) { - let slice_len = dfg.make_constant( - FieldElement::from(slice_len as u128), - Type::Numeric(NumericType::NativeField), - ); - SimplifiedTo(slice_len) + SimplifiedTo(dfg.make_constant((slice.len() as u128).into(), Type::field())) + } else if let Some(length) = dfg.try_get_array_length(arguments[0]) { + SimplifiedTo(dfg.make_constant((length as u128).into(), Type::field())) } else { None } @@ -534,9 +528,11 @@ fn constant_to_radix( while limbs.len() < limb_count_with_padding as usize { limbs.push(FieldElement::zero()); } - let result_constants = + let result_constants: im::Vector = limbs.into_iter().map(|limb| dfg.make_constant(limb, Type::unsigned(bit_size))).collect(); - dfg.make_array(result_constants, Rc::new(vec![Type::unsigned(bit_size)])) + + let typ = Type::Array(Rc::new(vec![Type::unsigned(bit_size)]), result_constants.len()); + dfg.make_array(result_constants, typ) } /// The possible return values for Instruction::return_types diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs index 03475f5f514..cea526058b4 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs @@ -1,5 +1,3 @@ -use std::rc::Rc; - use acvm::FieldElement; use crate::ssa_refactor::ir::basic_block::BasicBlockId; @@ -8,7 +6,7 @@ use super::{ function::FunctionId, instruction::{InstructionId, Intrinsic}, map::Id, - types::{CompositeType, Type}, + types::Type, }; pub(crate) type ValueId = Id; @@ -38,7 +36,7 @@ pub(crate) enum Value { NumericConstant { constant: FieldElement, typ: Type }, /// Represents a constant array value - Array { array: im::Vector, element_type: Rc }, + Array { array: im::Vector, typ: Type }, /// This Value refers to a function in the IR. /// Functions always have the type Type::Function. @@ -64,9 +62,7 @@ impl Value { Value::Instruction { typ, .. } => typ.clone(), Value::Param { typ, .. } => typ.clone(), Value::NumericConstant { typ, .. } => typ.clone(), - Value::Array { element_type, array } => { - Type::Array(element_type.clone(), array.len() / element_type.len()) - } + Value::Array { typ, .. } => typ.clone(), Value::Function { .. } => Type::Function, Value::Intrinsic { .. } => Type::Function, Value::ForeignFunction { .. } => Type::Function, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs index 3c40e2a15c5..acf048595d7 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs @@ -92,6 +92,8 @@ impl Context { #[cfg(test)] mod test { + use std::rc::Rc; + use crate::ssa_refactor::{ ir::{ function::RuntimeType, @@ -176,8 +178,9 @@ mod test { let v0 = builder.add_parameter(Type::field()); let one = builder.field_constant(1u128); let v1 = builder.insert_binary(v0, BinaryOp::Add, one); - let arr = - builder.current_function.dfg.make_array(vec![v1].into(), vec![Type::field()].into()); + + let array_type = Type::Array(Rc::new(vec![Type::field()]), 1); + let arr = builder.current_function.dfg.make_array(vec![v1].into(), array_type); builder.terminate_with_return(vec![arr]); let ssa = builder.finish().fold_constants(); diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs index ac62071d6ee..4ff857f942f 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs @@ -131,10 +131,7 @@ //! v11 = mul v4, Field 12 //! v12 = add v10, v11 //! store v12 at v5 (new store) -use std::{ - collections::{BTreeMap, HashMap, HashSet}, - rc::Rc, -}; +use std::collections::{BTreeMap, HashMap, HashSet}; use acvm::FieldElement; use iter_extended::vecmap; @@ -148,7 +145,7 @@ use crate::ssa_refactor::{ function::Function, function_inserter::FunctionInserter, instruction::{BinaryOp, Instruction, InstructionId, TerminatorInstruction}, - types::{CompositeType, Type}, + types::Type, value::ValueId, }, ssa_gen::Ssa, @@ -393,14 +390,9 @@ impl<'f> Context<'f> { Type::Numeric(_) => { self.merge_numeric_values(then_condition, else_condition, then_value, else_value) } - Type::Array(element_types, len) => self.merge_array_values( - element_types, - len, - then_condition, - else_condition, - then_value, - else_value, - ), + typ @ Type::Array(_, _) => { + self.merge_array_values(typ, then_condition, else_condition, then_value, else_value) + } // TODO(#1889) Type::Slice(_) => panic!("Cannot return slices from an if expression"), Type::Reference => panic!("Cannot return references from an if expression"), @@ -413,8 +405,7 @@ impl<'f> Context<'f> { /// by creating a new array containing the result of self.merge_values for each element. fn merge_array_values( &mut self, - element_types: Rc, - len: usize, + typ: Type, then_condition: ValueId, else_condition: ValueId, then_value: ValueId, @@ -422,6 +413,11 @@ impl<'f> Context<'f> { ) -> ValueId { let mut merged = im::Vector::new(); + let (element_types, len) = match &typ { + Type::Array(elements, len) => (elements, *len), + _ => panic!("Expected array type"), + }; + for i in 0..len { for (element_index, element_type) in element_types.iter().enumerate() { let index = ((i * element_types.len() + element_index) as u128).into(); @@ -446,7 +442,7 @@ impl<'f> Context<'f> { } } - self.inserter.function.dfg.make_array(merged, element_types) + self.inserter.function.dfg.make_array(merged, typ) } /// Merge two numeric values a and b from separate basic blocks to a single value. This @@ -1333,8 +1329,10 @@ mod test { let b3 = builder.insert_block(); let element_type = Rc::new(vec![Type::field()]); + let array_type = Type::Array(element_type.clone(), 1); + let zero = builder.field_constant(0_u128); - let zero_array = builder.array_constant(im::Vector::unit(zero), element_type.clone()); + let zero_array = builder.array_constant(im::Vector::unit(zero), array_type); let i_zero = builder.numeric_constant(0_u128, Type::unsigned(32)); let pedersen = builder.import_intrinsic_id(Intrinsic::BlackBox(acvm::acir::BlackBoxFunc::Pedersen)); diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs index 430b52ce9f6..7aa2f9d176a 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs @@ -217,9 +217,9 @@ impl<'function> PerFunctionContext<'function> { Value::ForeignFunction(function) => { self.context.builder.import_foreign_function(function) } - Value::Array { array, element_type } => { + Value::Array { array, typ } => { let elements = array.iter().map(|value| self.translate_value(*value)).collect(); - self.context.builder.array_constant(elements, element_type.clone()) + self.context.builder.array_constant(elements, typ.clone()) } }; diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs index 145ba25f5a5..15108abc490 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs @@ -212,10 +212,11 @@ mod tests { let two = builder.field_constant(FieldElement::one()); let element_type = Rc::new(vec![Type::field()]); - let array = builder.array_constant(vector![one, two], element_type.clone()); + let array_type = Type::Array(element_type, 2); + let array = builder.array_constant(vector![one, two], array_type.clone()); builder.insert_store(v0, array); - let v1 = builder.insert_load(v0, Type::Array(element_type, 2)); + let v1 = builder.insert_load(v0, array_type); let v2 = builder.insert_array_get(v1, one, Type::field()); builder.terminate_with_return(vec![v2]); diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs index d3d9e56b3af..02350d9ed17 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs @@ -1,4 +1,4 @@ -use std::{borrow::Cow, rc::Rc}; +use std::borrow::Cow; use acvm::FieldElement; use noirc_errors::Location; @@ -17,7 +17,6 @@ use super::{ dfg::InsertInstructionResult, function::RuntimeType, instruction::{InstructionId, Intrinsic}, - types::CompositeType, }, ssa_gen::Ssa, }; @@ -115,12 +114,8 @@ impl FunctionBuilder { } /// Insert an array constant into the current function with the given element values. - pub(crate) fn array_constant( - &mut self, - elements: im::Vector, - element_types: Rc, - ) -> ValueId { - self.current_function.dfg.make_array(elements, element_types) + pub(crate) fn array_constant(&mut self, elements: im::Vector, typ: Type) -> ValueId { + self.current_function.dfg.make_array(elements, typ) } /// Returns the type of the given value. diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs index 13e67f26cc5..2b6db4e7586 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs @@ -2,8 +2,6 @@ mod context; mod program; mod value; -use std::rc::Rc; - pub(crate) use program::Ssa; use context::SharedContext; @@ -16,12 +14,7 @@ use self::{ value::{Tree, Values}, }; -use super::ir::{ - function::RuntimeType, - instruction::BinaryOp, - types::{CompositeType, Type}, - value::ValueId, -}; +use super::ir::{function::RuntimeType, instruction::BinaryOp, types::Type, value::ValueId}; /// Generates SSA for the given monomorphized program. /// @@ -115,8 +108,8 @@ impl<'a> FunctionContext<'a> { match literal { ast::Literal::Array(array) => { let elements = vecmap(&array.contents, |element| self.codegen_expression(element)); - let element_types = Self::convert_type(&array.element_type).flatten(); - self.codegen_array(elements, element_types) + let typ = Self::convert_non_tuple_type(&array.typ); + self.codegen_array(elements, typ) } ast::Literal::Integer(value, typ) => { let typ = Self::convert_non_tuple_type(typ); @@ -129,7 +122,8 @@ impl<'a> FunctionContext<'a> { let elements = vecmap(string.as_bytes(), |byte| { self.builder.numeric_constant(*byte as u128, Type::field()).into() }); - self.codegen_array(elements, vec![Type::char()]) + let typ = Self::convert_non_tuple_type(&ast::Type::String(elements.len() as u64)); + self.codegen_array(elements, typ) } } } @@ -143,7 +137,7 @@ impl<'a> FunctionContext<'a> { /// stored the same as the array [1, 2, 3, 4]. /// /// The value returned from this function is always that of the allocate instruction. - fn codegen_array(&mut self, elements: Vec, element_types: CompositeType) -> Values { + fn codegen_array(&mut self, elements: Vec, typ: Type) -> Values { let mut array = im::Vector::new(); for element in elements { @@ -153,7 +147,7 @@ impl<'a> FunctionContext<'a> { }); } - self.builder.array_constant(array, Rc::new(element_types)).into() + self.builder.array_constant(array, typ).into() } fn codegen_block(&mut self, block: &[Expression]) -> Values { diff --git a/crates/noirc_frontend/src/hir/resolution/resolver.rs b/crates/noirc_frontend/src/hir/resolution/resolver.rs index 27fa91a086b..29b3cc485d5 100644 --- a/crates/noirc_frontend/src/hir/resolution/resolver.rs +++ b/crates/noirc_frontend/src/hir/resolution/resolver.rs @@ -333,11 +333,12 @@ impl<'a> Resolver<'a> { UnresolvedType::FieldElement(comp_time) => Type::FieldElement(comp_time), UnresolvedType::Array(size, elem) => { let elem = Box::new(self.resolve_type_inner(*elem, new_variables)); - if size.is_none() { - return Type::Slice(elem); - } - let resolved_size = self.resolve_array_size(size, new_variables); - Type::Array(Box::new(resolved_size), elem) + let size = if size.is_none() { + Type::NotConstant + } else { + self.resolve_array_size(size, new_variables) + }; + Type::Array(Box::new(size), elem) } UnresolvedType::Expression(expr) => self.convert_expression_type(expr), UnresolvedType::Integer(comp_time, sign, bits) => Type::Integer(comp_time, sign, bits), @@ -780,6 +781,7 @@ impl<'a> Resolver<'a> { | Type::TypeVariable(_, _) | Type::Constant(_) | Type::NamedGeneric(_, _) + | Type::NotConstant | Type::Forall(_, _) => (), Type::Array(length, _) => { @@ -788,10 +790,6 @@ impl<'a> Resolver<'a> { } } - Type::Slice(typ) => { - Self::find_numeric_generics_in_type(typ, found); - } - Type::Tuple(fields) => { for field in fields { Self::find_numeric_generics_in_type(field, found); diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index a2ff1c23a63..2c6578944be 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -48,7 +48,7 @@ impl<'interner> TypeChecker<'interner> { .unwrap_or_else(|| self.interner.next_type_variable()); let arr_type = Type::Array( - Box::new(Type::Constant(arr.len() as u64)), + Box::new(Type::constant_variable(arr.len() as u64, self.interner)), Box::new(first_elem_type.clone()), ); @@ -78,6 +78,12 @@ impl<'interner> TypeChecker<'interner> { } HirLiteral::Array(HirArrayLiteral::Repeated { repeated_element, length }) => { let elem_type = self.check_expression(&repeated_element); + let length = match length { + Type::Constant(length) => { + Type::constant_variable(length, self.interner) + } + other => other, + }; Type::Array(Box::new(length), Box::new(elem_type)) } HirLiteral::Bool(_) => Type::Bool(CompTime::new(self.interner)), @@ -109,7 +115,7 @@ impl<'interner> TypeChecker<'interner> { let function = self.check_expression(&call_expr.func); let args = vecmap(&call_expr.arguments, |arg| { let typ = self.check_expression(arg); - (typ, self.interner.expr_span(arg)) + (typ, *arg, self.interner.expr_span(arg)) }); let span = self.interner.expr_span(expr_id); self.bind_function_type(function, args, span) @@ -119,14 +125,16 @@ impl<'interner> TypeChecker<'interner> { let method_name = method_call.method.0.contents.as_str(); match self.lookup_method(&object_type, method_name, expr_id) { Some(method_id) => { - let mut args = - vec![(object_type, self.interner.expr_span(&method_call.object))]; + let mut args = vec![( + object_type, + method_call.object, + self.interner.expr_span(&method_call.object), + )]; - let mut arg_types = vecmap(&method_call.arguments, |arg| { + for arg in &method_call.arguments { let typ = self.check_expression(arg); - (typ, self.interner.expr_span(arg)) - }); - args.append(&mut arg_types); + args.push((typ, *arg, self.interner.expr_span(arg))); + } // Desugar the method call into a normal, resolved function call // so that the backend doesn't need to worry about methods @@ -276,7 +284,7 @@ impl<'interner> TypeChecker<'interner> { &mut self, method_call: &mut HirMethodCallExpression, function_type: &Type, - argument_types: &mut [(Type, noirc_errors::Span)], + argument_types: &mut [(Type, ExprId, noirc_errors::Span)], ) { let expected_object_type = match function_type { Type::Function(args, _) => args.get(0), @@ -328,7 +336,6 @@ impl<'interner> TypeChecker<'interner> { // XXX: We can check the array bounds here also, but it may be better to constant fold first // and have ConstId instead of ExprId for constants Type::Array(_, base_type) => *base_type, - Type::Slice(base_type) => *base_type, Type::Error => Type::Error, typ => { let span = self.interner.expr_span(&index_expr.collection); @@ -400,7 +407,7 @@ impl<'interner> TypeChecker<'interner> { &mut self, function_ident_id: &ExprId, func_id: &FuncId, - arguments: Vec<(Type, Span)>, + arguments: Vec<(Type, ExprId, Span)>, span: Span, ) -> Type { if func_id == &FuncId::dummy_id() { @@ -497,7 +504,7 @@ impl<'interner> TypeChecker<'interner> { let arg_type = self.check_expression(&arg); let span = self.interner.expr_span(expr_id); - self.make_subtype_of(&arg_type, ¶m_type, span, || { + self.make_subtype_of(&arg_type, ¶m_type, arg, || { TypeCheckError::TypeMismatch { expected_typ: param_type.to_string(), expr_typ: arg_type.to_string(), @@ -794,7 +801,12 @@ impl<'interner> TypeChecker<'interner> { } } - fn bind_function_type(&mut self, function: Type, args: Vec<(Type, Span)>, span: Span) -> Type { + fn bind_function_type( + &mut self, + function: Type, + args: Vec<(Type, ExprId, Span)>, + span: Span, + ) -> Type { // Could do a single unification for the entire function type, but matching beforehand // lets us issue a more precise error on the individual argument that fails to type check. match function { @@ -804,7 +816,7 @@ impl<'interner> TypeChecker<'interner> { } let ret = self.interner.next_type_variable(); - let args = vecmap(args, |(arg, _)| arg); + let args = vecmap(args, |(arg, _, _)| arg); let expected = Type::Function(args, Box::new(ret.clone())); if let Err(error) = binding.borrow_mut().bind_to(expected, span) { @@ -822,14 +834,18 @@ impl<'interner> TypeChecker<'interner> { return Type::Error; } - for (param, (arg, arg_span)) in parameters.iter().zip(args) { - arg.make_subtype_of(param, arg_span, &mut self.errors, || { - TypeCheckError::TypeMismatch { + for (param, (arg, arg_id, arg_span)) in parameters.iter().zip(args) { + arg.make_subtype_with_coercions( + param, + arg_id, + self.interner, + &mut self.errors, + || TypeCheckError::TypeMismatch { expected_typ: param.to_string(), expr_typ: arg.to_string(), expr_span: arg_span, - } - }); + }, + ); } *ret diff --git a/crates/noirc_frontend/src/hir/type_check/mod.rs b/crates/noirc_frontend/src/hir/type_check/mod.rs index a36c1ea67bc..26d0e36abf9 100644 --- a/crates/noirc_frontend/src/hir/type_check/mod.rs +++ b/crates/noirc_frontend/src/hir/type_check/mod.rs @@ -63,13 +63,17 @@ pub fn type_check_func(interner: &mut NodeInterner, func_id: FuncId) -> Vec TypeChecker<'interner> { &mut self, actual: &Type, expected: &Type, - span: Span, + expression: ExprId, make_error: impl FnOnce() -> TypeCheckError, ) { - actual.make_subtype_of(expected, span, &mut self.errors, make_error); + actual.make_subtype_with_coercions( + expected, + expression, + self.interner, + &mut self.errors, + make_error, + ); } } diff --git a/crates/noirc_frontend/src/hir/type_check/stmt.rs b/crates/noirc_frontend/src/hir/type_check/stmt.rs index 003334ade4e..3130a8616de 100644 --- a/crates/noirc_frontend/src/hir/type_check/stmt.rs +++ b/crates/noirc_frontend/src/hir/type_check/stmt.rs @@ -108,7 +108,7 @@ impl<'interner> TypeChecker<'interner> { }); let span = self.interner.expr_span(&assign_stmt.expression); - self.make_subtype_of(&expr_type, &lvalue_type, span, || { + self.make_subtype_of(&expr_type, &lvalue_type, assign_stmt.expression, || { TypeCheckError::TypeMismatchWithSource { rhs: expr_type.clone(), lhs: lvalue_type.clone(), @@ -192,7 +192,6 @@ impl<'interner> TypeChecker<'interner> { let typ = match result { Type::Array(_, elem_type) => *elem_type, - Type::Slice(elem_type) => *elem_type, Type::Error => Type::Error, other => { // TODO: Need a better span here @@ -260,7 +259,7 @@ impl<'interner> TypeChecker<'interner> { // Now check if LHS is the same type as the RHS // Importantly, we do not coerce any types implicitly let expr_span = self.interner.expr_span(&rhs_expr); - self.make_subtype_of(&expr_type, &annotated_type, expr_span, || { + self.make_subtype_of(&expr_type, &annotated_type, rhs_expr, || { TypeCheckError::TypeMismatch { expected_typ: annotated_type.to_string(), expr_typ: expr_type.to_string(), diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs index 143e59f9434..6e1113345a8 100644 --- a/crates/noirc_frontend/src/hir_def/types.rs +++ b/crates/noirc_frontend/src/hir_def/types.rs @@ -5,13 +5,18 @@ use std::{ rc::Rc, }; -use crate::{hir::type_check::TypeCheckError, node_interner::NodeInterner}; +use crate::{ + hir::type_check::TypeCheckError, + node_interner::{ExprId, NodeInterner}, +}; use iter_extended::vecmap; use noirc_abi::AbiType; use noirc_errors::Span; use crate::{node_interner::StructId, Ident, Signedness}; +use super::expr::{HirCallExpression, HirExpression, HirIdent}; + #[derive(Debug, PartialEq, Eq, Clone, Hash)] pub enum Type { /// A primitive Field type, and whether or not it is known at compile-time. @@ -21,9 +26,6 @@ pub enum Type { /// is either a type variable of some kind or a Type::Constant. Array(Box, Box), - /// Slice(E) is a slice with elements of type E. - Slice(Box), - /// A primitive integer type with the given sign, bit count, and whether it is known at compile-time. /// E.g. `u32` would be `Integer(CompTime::No(None), Unsigned, 32)` Integer(CompTime, Signedness, u32), @@ -81,6 +83,11 @@ pub enum Type { /// bind to an integer without special checks to bind it to a non-type. Constant(u64), + /// The type of a slice is an array of size NotConstant. + /// The size of an array literal is resolved to this if it ever uses operations + /// involving slices. + NotConstant, + /// The result of some type error. Remembering type errors as their own type variant lets /// us avoid issuing repeat type errors for the same item. For example, a lambda with /// an invalid type would otherwise issue a new error each time it is called @@ -275,12 +282,18 @@ pub enum BinaryTypeOperator { pub enum TypeVariableKind { /// Can bind to any type Normal, + /// A generic integer or field type. This is a more specific kind of TypeVariable /// that can only be bound to Type::Field, Type::Integer, or other polymorphic integers. /// This is the type of undecorated integer literals like `46`. Typing them in this way /// allows them to be polymorphic over the actual integer/field type used without requiring /// type annotations on each integer literal. IntegerOrField(CompTime), + + /// A potentially constant array size. This will only bind to itself, Type::NotConstant, or + /// Type::Constant(n) with a matching size. This defaults to Type::Constant(n) if still unbound + /// during monomorphization. + Constant(u64), } /// A TypeVariable is a mutable reference that is either @@ -544,12 +557,18 @@ impl Type { Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), TypeVariableKind::Normal) } + /// Returns a TypeVariable(_, TypeVariableKind::Constant(length)) to bind to + /// a constant integer for e.g. an array length. + pub fn constant_variable(length: u64, interner: &mut NodeInterner) -> Type { + let id = interner.next_type_variable_id(); + let kind = TypeVariableKind::Constant(length); + Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), kind) + } + pub fn polymorphic_integer(interner: &mut NodeInterner) -> Type { let id = interner.next_type_variable_id(); - Type::TypeVariable( - Shared::new(TypeBinding::Unbound(id)), - TypeVariableKind::IntegerOrField(CompTime::new(interner)), - ) + let kind = TypeVariableKind::IntegerOrField(CompTime::new(interner)); + Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), kind) } /// A bit of an awkward name for this function - this function returns @@ -595,14 +614,13 @@ impl Type { | Type::TypeVariable(_, _) | Type::Constant(_) | Type::NamedGeneric(_, _) + | Type::NotConstant | Type::Forall(_, _) => false, Type::Array(length, elem) => { elem.contains_numeric_typevar(target_id) || named_generic_id_matches_target(length) } - Type::Slice(elem) => elem.contains_numeric_typevar(target_id), - Type::Tuple(fields) => { fields.iter().any(|field| field.contains_numeric_typevar(target_id)) } @@ -642,12 +660,18 @@ impl std::fmt::Display for Type { Type::FieldElement(comp_time) => { write!(f, "{comp_time}Field") } - Type::Array(len, typ) => write!(f, "[{typ}; {len}]"), - Type::Slice(typ) => write!(f, "[{typ}]"), + Type::Array(len, typ) => { + if matches!(len.follow_bindings(), Type::NotConstant) { + write!(f, "[{typ}]") + } else { + write!(f, "[{typ}; {len}]") + } + } Type::Integer(comp_time, sign, num_bits) => match sign { Signedness::Signed => write!(f, "{comp_time}i{num_bits}"), Signedness::Unsigned => write!(f, "{comp_time}u{num_bits}"), }, + Type::TypeVariable(id, TypeVariableKind::Normal) => write!(f, "{}", id.borrow()), Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(_)) => { if let TypeBinding::Unbound(_) = &*binding.borrow() { // Show a Field by default if this TypeVariableKind::IntegerOrField is unbound, since that is @@ -658,6 +682,14 @@ impl std::fmt::Display for Type { write!(f, "{}", binding.borrow()) } } + Type::TypeVariable(binding, TypeVariableKind::Constant(n)) => { + if let TypeBinding::Unbound(_) = &*binding.borrow() { + // TypeVariableKind::Constant(n) binds to Type::Constant(n) by default, so just show that. + write!(f, "{n}") + } else { + write!(f, "{}", binding.borrow()) + } + } Type::Struct(s, args) => { let args = vecmap(args, |arg| arg.to_string()); if args.is_empty() { @@ -674,7 +706,6 @@ impl std::fmt::Display for Type { Type::String(len) => write!(f, "str<{len}>"), Type::Unit => write!(f, "()"), Type::Error => write!(f, "error"), - Type::TypeVariable(id, TypeVariableKind::Normal) => write!(f, "{}", id.borrow()), Type::NamedGeneric(binding, name) => match &*binding.borrow() { TypeBinding::Bound(binding) => binding.fmt(f), TypeBinding::Unbound(_) if name.is_empty() => write!(f, "_"), @@ -692,6 +723,7 @@ impl std::fmt::Display for Type { Type::MutableReference(element) => { write!(f, "&mut {element}") } + Type::NotConstant => write!(f, "_"), } } } @@ -770,6 +802,62 @@ impl Type { } } + /// Try to bind a MaybeConstant variable to self, succeeding if self is a Constant, + /// MaybeConstant, or type variable. + pub fn try_bind_to_maybe_constant( + &self, + var: &TypeVariable, + target_length: u64, + ) -> Result<(), SpanKind> { + let target_id = match &*var.borrow() { + TypeBinding::Bound(_) => unreachable!(), + TypeBinding::Unbound(id) => *id, + }; + + match self { + Type::Constant(length) if *length == target_length => { + *var.borrow_mut() = TypeBinding::Bound(self.clone()); + Ok(()) + } + Type::NotConstant => { + *var.borrow_mut() = TypeBinding::Bound(Type::NotConstant); + Ok(()) + } + Type::TypeVariable(binding, kind) => { + let borrow = binding.borrow(); + match &*borrow { + TypeBinding::Bound(typ) => typ.try_bind_to_maybe_constant(var, target_length), + // Avoid infinitely recursive bindings + TypeBinding::Unbound(id) if *id == target_id => Ok(()), + TypeBinding::Unbound(_) => match kind { + TypeVariableKind::Normal => { + drop(borrow); + let clone = Type::TypeVariable( + var.clone(), + TypeVariableKind::Constant(target_length), + ); + *binding.borrow_mut() = TypeBinding::Bound(clone); + Ok(()) + } + TypeVariableKind::Constant(length) if *length == target_length => { + drop(borrow); + let clone = Type::TypeVariable( + var.clone(), + TypeVariableKind::Constant(target_length), + ); + *binding.borrow_mut() = TypeBinding::Bound(clone); + Ok(()) + } + TypeVariableKind::Constant(_) | TypeVariableKind::IntegerOrField(_) => { + Err(SpanKind::None) + } + }, + } + } + _ => Err(SpanKind::None), + } + } + /// Try to bind a PolymorphicInt variable to self, succeeding if self is an integer, field, /// other PolymorphicInt type, or type variable. If use_subtype is true, the CompTime fields /// of each will be checked via sub-typing rather than unification. @@ -930,11 +1018,13 @@ impl Type { /// any unified bindings are on success. fn try_unify(&self, other: &Type, span: Span) -> Result<(), SpanKind> { use Type::*; + use TypeVariableKind as Kind; + match (self, other) { (Error, _) | (_, Error) => Ok(()), - (TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime)), other) - | (other, TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime))) => { + (TypeVariable(binding, Kind::IntegerOrField(comptime)), other) + | (other, TypeVariable(binding, Kind::IntegerOrField(comptime))) => { // If it is already bound, unify against what it is bound to if let TypeBinding::Bound(link) = &*binding.borrow() { return link.try_unify(other, span); @@ -944,7 +1034,8 @@ impl Type { other.try_bind_to_polymorphic_int(binding, comptime, false, span) } - (TypeVariable(binding, _), other) | (other, TypeVariable(binding, _)) => { + (TypeVariable(binding, Kind::Normal), other) + | (other, TypeVariable(binding, Kind::Normal)) => { if let TypeBinding::Bound(link) = &*binding.borrow() { return link.try_unify(other, span); } @@ -952,13 +1043,20 @@ impl Type { other.try_bind_to(binding) } + (TypeVariable(binding, Kind::Constant(length)), other) + | (other, TypeVariable(binding, Kind::Constant(length))) => { + if let TypeBinding::Bound(link) = &*binding.borrow() { + return link.try_unify(other, span); + } + + other.try_bind_to_maybe_constant(binding, *length) + } + (Array(len_a, elem_a), Array(len_b, elem_b)) => { len_a.try_unify(len_b, span)?; elem_a.try_unify(elem_b, span) } - (Slice(elem_a), Slice(elem_b)) => elem_a.try_unify(elem_b, span), - (Tuple(elements_a), Tuple(elements_b)) => { if elements_a.len() != elements_b.len() { Err(SpanKind::None) @@ -1048,7 +1146,60 @@ impl Type { } } - fn is_subtype_of(&self, other: &Type, span: Span) -> Result<(), SpanKind> { + /// Similar to `make_subtype_of` but if the check fails this will attempt to coerce the + /// argument to the target type. When this happens, the given expression is wrapped in + /// a new expression to convert its type. E.g. `array` -> `array.as_slice()` + /// + /// Currently the only type coercion in Noir is `[T; N]` into `[T]` via `.as_slice()`. + pub fn make_subtype_with_coercions( + &self, + expected: &Type, + expression: ExprId, + interner: &mut NodeInterner, + errors: &mut Vec, + make_error: impl FnOnce() -> TypeCheckError, + ) { + let span = interner.expr_span(&expression); + if let Err(err_span) = self.is_subtype_of(expected, span) { + if !self.try_array_to_slice_coercion(expected, expression, span, interner) { + Self::issue_errors(expected, err_span, errors, make_error); + } + } + } + + /// Try to apply the array to slice coercion to this given type pair and expression. + /// If self can be converted to target this way, do so and return true to indicate success. + fn try_array_to_slice_coercion( + &self, + target: &Type, + expression: ExprId, + span: Span, + interner: &mut NodeInterner, + ) -> bool { + let this = self.follow_bindings(); + let target = target.follow_bindings(); + + if let (Type::Array(size1, element1), Type::Array(size2, element2)) = (&this, &target) { + let size1 = size1.follow_bindings(); + let size2 = size2.follow_bindings(); + + // If we have an array and our target is a slice + if matches!(size1, Type::Constant(_)) && matches!(size2, Type::NotConstant) { + // Still have to ensure the element types match. + // Don't need to issue an error here if not, it will be done in make_subtype_of_with_coercions + if element1.is_subtype_of(element2, span).is_ok() { + convert_array_expression_to_slice(expression, this, target, interner); + return true; + } + } + } + false + } + + /// Checks if self is a subtype of `other`. Returns Ok(()) if it is and Err(_) if not. + /// Note that this function may permanently bind type variables regardless of whether it + /// returned Ok or Err. + pub fn is_subtype_of(&self, other: &Type, span: Span) -> Result<(), SpanKind> { use Type::*; match (self, other) { (Error, _) | (_, Error) => Ok(()), @@ -1072,14 +1223,14 @@ impl Type { other.try_bind_to_polymorphic_int(binding, comptime, false, span) } - (TypeVariable(binding, _), other) => { + (TypeVariable(binding, TypeVariableKind::Normal), other) => { if let TypeBinding::Bound(link) = &*binding.borrow() { return link.is_subtype_of(other, span); } other.try_bind_to(binding) } - (other, TypeVariable(binding, _)) => { + (other, TypeVariable(binding, TypeVariableKind::Normal)) => { if let TypeBinding::Bound(link) = &*binding.borrow() { return other.is_subtype_of(link, span); } @@ -1087,15 +1238,26 @@ impl Type { other.try_bind_to(binding) } + (TypeVariable(binding, TypeVariableKind::Constant(length)), other) => { + if let TypeBinding::Bound(link) = &*binding.borrow() { + return link.is_subtype_of(other, span); + } + + other.try_bind_to_maybe_constant(binding, *length) + } + (other, TypeVariable(binding, TypeVariableKind::Constant(length))) => { + if let TypeBinding::Bound(link) = &*binding.borrow() { + return other.is_subtype_of(link, span); + } + + other.try_bind_to_maybe_constant(binding, *length) + } + (Array(len_a, elem_a), Array(len_b, elem_b)) => { len_a.is_subtype_of(len_b, span)?; elem_a.is_subtype_of(elem_b, span) } - (Slice(elem_a), Slice(elem_b)) => elem_a.is_subtype_of(elem_b, span), - - (Array(_, elem_a), Slice(elem_b)) => elem_a.is_subtype_of(elem_b, span), - (Tuple(elements_a), Tuple(elements_b)) => { if elements_a.len() != elements_b.len() { Err(SpanKind::None) @@ -1188,13 +1350,14 @@ impl Type { /// If this type is a Type::Constant (used in array lengths), or is bound /// to a Type::Constant, return the constant as a u64. pub fn evaluate_to_u64(&self) -> Option { - match self { - Type::NamedGeneric(binding, _) | Type::TypeVariable(binding, _) => { - match &*binding.borrow() { - TypeBinding::Bound(binding) => binding.evaluate_to_u64(), - TypeBinding::Unbound(_) => None, - } + if let Some(binding) = self.get_inner_type_variable() { + if let TypeBinding::Bound(binding) = &*binding.borrow() { + return binding.evaluate_to_u64(); } + } + + match self { + Type::TypeVariable(_, TypeVariableKind::Constant(size)) => Some(*size), Type::Array(len, _elem) => len.evaluate_to_u64(), Type::Constant(x) => Some(*x), _ => None, @@ -1247,8 +1410,8 @@ impl Type { Type::NamedGeneric(..) => unreachable!(), Type::Forall(..) => unreachable!(), Type::Function(_, _) => unreachable!(), - Type::Slice(_) => unreachable!("slices cannot be used in the abi"), Type::MutableReference(_) => unreachable!("&mut cannot be used in the abi"), + Type::NotConstant => unreachable!(), } } @@ -1330,10 +1493,6 @@ impl Type { let element = Box::new(element.substitute(type_bindings)); Type::Array(size, element) } - Type::Slice(element) => { - let element = Box::new(element.substitute(type_bindings)); - Type::Slice(element) - } Type::String(size) => { let size = Box::new(size.substitute(type_bindings)); Type::String(size) @@ -1374,6 +1533,7 @@ impl Type { | Type::Bool(_) | Type::Constant(_) | Type::Error + | Type::NotConstant | Type::Unit => self.clone(), } } @@ -1382,7 +1542,6 @@ impl Type { fn occurs(&self, target_id: TypeVariableId) -> bool { match self { Type::Array(len, elem) => len.occurs(target_id) || elem.occurs(target_id), - Type::Slice(element) => element.occurs(target_id), Type::String(len) => len.occurs(target_id), Type::Struct(_, generic_args) => generic_args.iter().any(|arg| arg.occurs(target_id)), Type::Tuple(fields) => fields.iter().any(|field| field.occurs(target_id)), @@ -1405,6 +1564,7 @@ impl Type { | Type::Bool(_) | Type::Constant(_) | Type::Error + | Type::NotConstant | Type::Unit => false, } } @@ -1421,7 +1581,6 @@ impl Type { Array(size, elem) => { Array(Box::new(size.follow_bindings()), Box::new(elem.follow_bindings())) } - Slice(elem) => Slice(Box::new(elem.follow_bindings())), String(size) => String(Box::new(size.follow_bindings())), Struct(def, args) => { let args = vecmap(args, |arg| arg.follow_bindings()); @@ -1446,13 +1605,44 @@ impl Type { // Expect that this function should only be called on instantiated types Forall(..) => unreachable!(), - FieldElement(_) | Integer(_, _, _) | Bool(_) | Constant(_) | Unit | Error => { - self.clone() - } + FieldElement(_) + | Integer(_, _, _) + | Bool(_) + | Constant(_) + | Unit + | Error + | NotConstant => self.clone(), } } } +/// Wraps a given `expression` in `expression.as_slice()` +fn convert_array_expression_to_slice( + expression: ExprId, + array_type: Type, + target_type: Type, + interner: &mut NodeInterner, +) { + let as_slice_method = interner + .lookup_primitive_method(&array_type, "as_slice") + .expect("Expected 'as_slice' method to be present in Noir's stdlib"); + + let as_slice_id = interner.function_definition_id(as_slice_method); + let location = interner.expr_location(&expression); + let as_slice = HirExpression::Ident(HirIdent { location, id: as_slice_id }); + let func = interner.push_expr(as_slice); + + let arguments = vec![expression]; + let call = HirExpression::Call(HirCallExpression { func, arguments, location }); + let call = interner.push_expr(call); + + interner.push_expr_location(call, location.span, location.file); + interner.push_expr_location(func, location.span, location.file); + + interner.push_expr_type(&call, target_type.clone()); + interner.push_expr_type(&func, Type::Function(vec![array_type], Box::new(target_type))); +} + impl BinaryTypeOperator { /// Return the actual rust numeric function associated with this operator pub fn function(self) -> fn(u64, u64) -> u64 { @@ -1465,3 +1655,14 @@ impl BinaryTypeOperator { } } } + +impl TypeVariableKind { + /// Returns the default type this type variable should be bound to if it is still unbound + /// during monomorphization. + pub(crate) fn default_type(&self) -> Type { + match self { + TypeVariableKind::IntegerOrField(_) | TypeVariableKind::Normal => Type::field(None), + TypeVariableKind::Constant(length) => Type::Constant(*length), + } + } +} diff --git a/crates/noirc_frontend/src/monomorphization/ast.rs b/crates/noirc_frontend/src/monomorphization/ast.rs index 7cac2ed8e4f..488d05c6509 100644 --- a/crates/noirc_frontend/src/monomorphization/ast.rs +++ b/crates/noirc_frontend/src/monomorphization/ast.rs @@ -119,7 +119,7 @@ pub struct Cast { #[derive(Debug, Clone)] pub struct ArrayLiteral { pub contents: Vec, - pub element_type: Type, + pub typ: Type, } #[derive(Debug, Clone)] diff --git a/crates/noirc_frontend/src/monomorphization/mod.rs b/crates/noirc_frontend/src/monomorphization/mod.rs index d9ee9666e3c..bb0228091da 100644 --- a/crates/noirc_frontend/src/monomorphization/mod.rs +++ b/crates/noirc_frontend/src/monomorphization/mod.rs @@ -22,8 +22,7 @@ use crate::{ }, node_interner::{self, DefinitionKind, NodeInterner, StmtId}, token::Attribute, - CompTime, ContractFunctionType, FunctionKind, Type, TypeBinding, TypeBindings, - TypeVariableKind, + ContractFunctionType, FunctionKind, TypeBinding, TypeBindings, TypeVariableKind, }; use self::ast::{Definition, FuncId, Function, LocalId, Program}; @@ -270,7 +269,7 @@ impl<'interner> Monomorphizer<'interner> { HirExpression::Literal(HirLiteral::Array(array)) => match array { HirArrayLiteral::Standard(array) => self.standard_array(expr, array), HirArrayLiteral::Repeated { repeated_element, length } => { - self.repeated_array(repeated_element, length) + self.repeated_array(expr, repeated_element, length) } }, HirExpression::Literal(HirLiteral::Unit) => ast::Expression::Block(vec![]), @@ -355,25 +354,26 @@ impl<'interner> Monomorphizer<'interner> { array: node_interner::ExprId, array_elements: Vec, ) -> ast::Expression { - let element_type = - Self::convert_type(&unwrap_array_element_type(&self.interner.id_type(array))); + let typ = Self::convert_type(&self.interner.id_type(array)); let contents = vecmap(array_elements, |id| self.expr(id)); - ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, element_type })) + ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, typ })) } fn repeated_array( &mut self, + array: node_interner::ExprId, repeated_element: node_interner::ExprId, length: HirType, ) -> ast::Expression { - let element_type = Self::convert_type(&self.interner.id_type(repeated_element)); + let typ = Self::convert_type(&self.interner.id_type(array)); + let contents = self.expr(repeated_element); let length = length .evaluate_to_u64() .expect("Length of array is unknown when evaluating numeric generic"); let contents = vec![contents; length as usize]; - ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, element_type })) + ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, typ })) } fn index(&mut self, id: node_interner::ExprId, index: HirIndexExpression) -> ast::Expression { @@ -590,33 +590,49 @@ impl<'interner> Monomorphizer<'interner> { HirType::Unit => ast::Type::Unit, HirType::Array(length, element) => { - let length = length.evaluate_to_u64().unwrap_or(0); - let element = Self::convert_type(element.as_ref()); - ast::Type::Array(length, Box::new(element)) - } + let element = Box::new(Self::convert_type(element.as_ref())); - HirType::Slice(element) => { - let element = Self::convert_type(element.as_ref()); - ast::Type::Slice(Box::new(element)) + if let Some(length) = length.evaluate_to_u64() { + ast::Type::Array(length, element) + } else { + ast::Type::Slice(element) + } } - HirType::TypeVariable(binding, _) | HirType::NamedGeneric(binding, _) => { + HirType::NamedGeneric(binding, _) => { if let TypeBinding::Bound(binding) = &*binding.borrow() { return Self::convert_type(binding); } - // Default any remaining unbound type variables to Field. + // Default any remaining unbound type variables. // This should only happen if the variable in question is unused // and within a larger generic type. // NOTE: Make sure to review this if there is ever type-directed dispatch, // like automatic solving of traits. It should be fine since it is strictly // after type checking, but care should be taken that it doesn't change which // impls are chosen. - *binding.borrow_mut() = - TypeBinding::Bound(HirType::FieldElement(CompTime::No(None))); + *binding.borrow_mut() = TypeBinding::Bound(HirType::field(None)); ast::Type::Field } + HirType::TypeVariable(binding, kind) => { + if let TypeBinding::Bound(binding) = &*binding.borrow() { + return Self::convert_type(binding); + } + + // Default any remaining unbound type variables. + // This should only happen if the variable in question is unused + // and within a larger generic type. + // NOTE: Make sure to review this if there is ever type-directed dispatch, + // like automatic solving of traits. It should be fine since it is strictly + // after type checking, but care should be taken that it doesn't change which + // impls are chosen. + let default = kind.default_type(); + let monomorphized_default = Self::convert_type(&default); + *binding.borrow_mut() = TypeBinding::Bound(default); + monomorphized_default + } + HirType::Struct(def, args) => { let fields = def.borrow().get_fields(args); let fields = vecmap(fields, |(_, field)| Self::convert_type(&field)); @@ -639,7 +655,10 @@ impl<'interner> Monomorphizer<'interner> { ast::Type::MutableReference(Box::new(element)) } - HirType::Forall(_, _) | HirType::Constant(_) | HirType::Error => { + HirType::Forall(_, _) + | HirType::Constant(_) + | HirType::NotConstant + | HirType::Error => { unreachable!("Unexpected type {} found", typ) } } @@ -667,8 +686,12 @@ impl<'interner> Monomorphizer<'interner> { } } - self.try_evaluate_call(&func, &call.arguments, &return_type) - .unwrap_or(ast::Expression::Call(ast::Call { func, arguments, return_type, location })) + self.try_evaluate_call(&func, &return_type).unwrap_or(ast::Expression::Call(ast::Call { + func, + arguments, + return_type, + location, + })) } /// Adds a function argument that contains type metadata that is required to tell @@ -707,25 +730,12 @@ impl<'interner> Monomorphizer<'interner> { fn try_evaluate_call( &mut self, func: &ast::Expression, - arguments: &[node_interner::ExprId], result_type: &ast::Type, ) -> Option { if let ast::Expression::Ident(ident) = func { if let Definition::Builtin(opcode) = &ident.definition { // TODO(#1736): Move this builtin to the SSA pass return match opcode.as_str() { - "array_len" => { - let typ = self.interner.id_type(arguments[0]); - if let Type::Array(_, _) = typ { - let len = typ.evaluate_to_u64().unwrap(); - Some(ast::Expression::Literal(ast::Literal::Integer( - (len as u128).into(), - ast::Type::Field, - ))) - } else { - None - } - } "modulus_num_bits" => Some(ast::Expression::Literal(ast::Literal::Integer( (FieldElement::max_num_bits() as u128).into(), ast::Type::Field, @@ -755,17 +765,17 @@ impl<'interner> Monomorphizer<'interner> { } fn modulus_array_literal(&self, bytes: Vec, arr_elem_bits: u32) -> ast::Expression { + use ast::*; + let int_type = Type::Integer(crate::Signedness::Unsigned, arr_elem_bits); + let bytes_as_expr = vecmap(bytes, |byte| { - ast::Expression::Literal(ast::Literal::Integer( - (byte as u128).into(), - ast::Type::Integer(crate::Signedness::Unsigned, arr_elem_bits), - )) + Expression::Literal(Literal::Integer((byte as u128).into(), int_type.clone())) }); - let arr_literal = ast::ArrayLiteral { - contents: bytes_as_expr, - element_type: ast::Type::Integer(crate::Signedness::Unsigned, arr_elem_bits), - }; - ast::Expression::Literal(ast::Literal::Array(arr_literal)) + + let typ = Type::Array(bytes_as_expr.len() as u64, Box::new(int_type)); + + let arr_literal = ArrayLiteral { typ, contents: bytes_as_expr }; + Expression::Literal(Literal::Array(arr_literal)) } fn queue_function( @@ -906,7 +916,7 @@ impl<'interner> Monomorphizer<'interner> { let element = self.zeroed_value_of_type(element_type.as_ref()); ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents: vec![element; *length as usize], - element_type: element_type.as_ref().clone(), + typ: ast::Type::Array(*length, element_type.clone()), })) } ast::Type::String(length) => { @@ -921,7 +931,7 @@ impl<'interner> Monomorphizer<'interner> { ast::Type::Slice(element_type) => { ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents: vec![], - element_type: *element_type.clone(), + typ: ast::Type::Slice(element_type.clone()), })) } ast::Type::MutableReference(element) => { @@ -992,20 +1002,6 @@ fn unwrap_struct_type(typ: &HirType) -> Vec<(String, HirType)> { } } -fn unwrap_array_element_type(typ: &HirType) -> HirType { - match typ { - HirType::Array(_, elem) => *elem.clone(), - HirType::Slice(elem) => *elem.clone(), - HirType::TypeVariable(binding, TypeVariableKind::Normal) => match &*binding.borrow() { - TypeBinding::Bound(binding) => unwrap_array_element_type(binding), - TypeBinding::Unbound(_) => unreachable!(), - }, - other => { - unreachable!("unwrap_array_element_type: expected an array or slice, found {:?}", other) - } - } -} - fn perform_instantiation_bindings(bindings: &TypeBindings) { for (var, binding) in bindings.values() { *var.borrow_mut() = TypeBinding::Bound(binding.clone()); diff --git a/crates/noirc_frontend/src/node_interner.rs b/crates/noirc_frontend/src/node_interner.rs index fa2ce49ed11..f01c5f22a50 100644 --- a/crates/noirc_frontend/src/node_interner.rs +++ b/crates/noirc_frontend/src/node_interner.rs @@ -608,7 +608,6 @@ enum TypeMethodKey { /// accept only fields or integers, it is just that their names may not clash. FieldOrInt, Array, - Slice, Bool, String, Unit, @@ -622,7 +621,6 @@ fn get_type_method_key(typ: &Type) -> Option { match &typ { Type::FieldElement(_) => Some(FieldOrInt), Type::Array(_, _) => Some(Array), - Type::Slice(_) => Some(Slice), Type::Integer(_, _, _) => Some(FieldOrInt), Type::TypeVariable(_, TypeVariableKind::IntegerOrField(_)) => Some(FieldOrInt), Type::Bool(_) => Some(Bool), @@ -638,6 +636,7 @@ fn get_type_method_key(typ: &Type) -> Option { | Type::Forall(_, _) | Type::Constant(_) | Type::Error + | Type::NotConstant | Type::Struct(_, _) => None, } } diff --git a/noir_stdlib/src/array.nr b/noir_stdlib/src/array.nr index 9e44aa03fcc..db349317f91 100644 --- a/noir_stdlib/src/array.nr +++ b/noir_stdlib/src/array.nr @@ -22,6 +22,15 @@ impl [T; N] { a } + // Converts an array into a slice. + fn as_slice(self) -> [T] { + let mut slice = []; + for elem in self { + slice = slice.push_back(elem); + } + slice + } + // Apply a function to each element of an array, returning a new array // containing the mapped elements. fn map(self, f: fn(T) -> U) -> [U; N] { diff --git a/noir_stdlib/src/ecdsa_secp256k1.nr b/noir_stdlib/src/ecdsa_secp256k1.nr index efeceef5df2..c46380e1988 100644 --- a/noir_stdlib/src/ecdsa_secp256k1.nr +++ b/noir_stdlib/src/ecdsa_secp256k1.nr @@ -1,2 +1,2 @@ #[foreign(ecdsa_secp256k1)] -fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8]) -> bool {} +fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8; N]) -> bool {} diff --git a/noir_stdlib/src/ecdsa_secp256r1.nr b/noir_stdlib/src/ecdsa_secp256r1.nr index 44df07d3590..77744384f52 100644 --- a/noir_stdlib/src/ecdsa_secp256r1.nr +++ b/noir_stdlib/src/ecdsa_secp256r1.nr @@ -1,2 +1,2 @@ #[foreign(ecdsa_secp256r1)] -fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8]) -> bool {} +fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8; N]) -> bool {} diff --git a/noir_stdlib/src/hash/poseidon.nr b/noir_stdlib/src/hash/poseidon.nr index 416f740bbdf..cb1e34927b4 100644 --- a/noir_stdlib/src/hash/poseidon.nr +++ b/noir_stdlib/src/hash/poseidon.nr @@ -101,7 +101,7 @@ fn check_security(rate: Field, width: Field, security: Field) -> bool { } // A*x where A is an n x n matrix in row-major order and x an n-vector -fn apply_matrix(a: [Field], x: [Field; N]) -> [Field; N] { +fn apply_matrix(a: [Field; M], x: [Field; N]) -> [Field; N] { let mut y = x; for i in 0..x.len() { diff --git a/noir_stdlib/src/merkle.nr b/noir_stdlib/src/merkle.nr index 1f1a45ffe17..07588a52a5a 100644 --- a/noir_stdlib/src/merkle.nr +++ b/noir_stdlib/src/merkle.nr @@ -3,7 +3,7 @@ // XXX: In the future we can add an arity parameter // Returns the merkle root of the tree from the provided leaf, its hashpath, using a pedersen hash function. -fn compute_merkle_root(leaf: Field, index: Field, hash_path: [Field]) -> Field { +fn compute_merkle_root(leaf: Field, index: Field, hash_path: [Field; N]) -> Field { let n = hash_path.len(); let index_bits = index.to_le_bits(n as u32); let mut current = leaf; @@ -18,4 +18,4 @@ fn compute_merkle_root(leaf: Field, index: Field, hash_path: [Field]) -> Field { current = crate::hash::pedersen([hash_left, hash_right])[0]; }; current -} \ No newline at end of file +} diff --git a/noir_stdlib/src/schnorr.nr b/noir_stdlib/src/schnorr.nr index 5000efd3be4..1e69bcec821 100644 --- a/noir_stdlib/src/schnorr.nr +++ b/noir_stdlib/src/schnorr.nr @@ -1,2 +1,2 @@ #[foreign(schnorr_verify)] -fn verify_signature(_public_key_x: Field, _public_key_y: Field, _signature: [u8; 64], _message: [u8]) -> bool {} +fn verify_signature(_public_key_x: Field, _public_key_y: Field, _signature: [u8; 64], _message: [u8; N]) -> bool {} diff --git a/noir_stdlib/src/slice.nr b/noir_stdlib/src/slice.nr index 186d535a264..8e344a40f5e 100644 --- a/noir_stdlib/src/slice.nr +++ b/noir_stdlib/src/slice.nr @@ -32,74 +32,5 @@ impl [T] { /// the removed element #[builtin(slice_remove)] fn remove(_self: Self, _index: Field) -> (Self, T) { } - - #[builtin(array_len)] - fn len(_self: Self) -> comptime Field {} - - #[builtin(arraysort)] - fn sort(_self: Self) -> Self {} - - // Sort with a custom sorting function. - fn sort_via(mut a: Self, ordering: fn(T, T) -> bool) -> Self { - for i in 1 .. a.len() { - for j in 0..i { - if ordering(a[i], a[j]) { - let old_a_j = a[j]; - a[j] = a[i]; - a[i] = old_a_j; - } - } - } - a - } - - // Apply a function to each element of a slice, returning a new slice - // containing the mapped elements. - fn map(self, f: fn(T) -> U) -> [U] { - let mut ret: [U] = []; - for elem in self { - ret = ret.push_back(f(elem)); - } - ret - } - - // Apply a function to each element of the slice and an accumulator value, - // returning the final accumulated value. This function is also sometimes - // called `foldl`, `fold_left`, `reduce`, or `inject`. - fn fold(self, mut accumulator: U, f: fn(U, T) -> U) -> U { - for elem in self { - accumulator = f(accumulator, elem); - } - accumulator - } - - // Apply a function to each element of the slice and an accumulator value, - // returning the final accumulated value. Unlike fold, reduce uses the first - // element of the given slice as its starting accumulator value. - fn reduce(self, f: fn(T, T) -> T) -> T { - let mut accumulator = self[0]; - for i in 1 .. self.len() { - accumulator = f(accumulator, self[i]); - } - accumulator - } - - // Returns true if all elements in the array satisfy the predicate - fn all(self, predicate: fn(T) -> bool) -> bool { - let mut ret = true; - for elem in self { - ret &= predicate(elem); - } - ret - } - - // Returns true if any element in the array satisfies the predicate - fn any(self, predicate: fn(T) -> bool) -> bool { - let mut ret = false; - for elem in self { - ret |= predicate(elem); - } - ret - } } From 910f482df6ba287a3d182650b83fdb8c44d12087 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Mon, 31 Jul 2023 09:54:29 +0100 Subject: [PATCH 05/50] chore(nargo): Use Display impl for InputValue (#1990) * use Display impl for InputValue * chore: clean up visibilities --------- Co-authored-by: TomAFrench --- crates/nargo/src/ops/foreign_calls.rs | 8 +++--- crates/noirc_abi/src/input_parser/json.rs | 4 +-- crates/noirc_abi/src/input_parser/mod.rs | 35 +++++++++++++++++++++-- crates/noirc_abi/src/lib.rs | 2 +- 4 files changed, 39 insertions(+), 10 deletions(-) diff --git a/crates/nargo/src/ops/foreign_calls.rs b/crates/nargo/src/ops/foreign_calls.rs index ea7f9be21b4..4bbd4eb58bc 100644 --- a/crates/nargo/src/ops/foreign_calls.rs +++ b/crates/nargo/src/ops/foreign_calls.rs @@ -3,7 +3,7 @@ use acvm::{ pwg::ForeignCallWaitInfo, }; use iter_extended::vecmap; -use noirc_abi::{decode_string_value, decode_value, input_parser::json::JsonTypes, AbiType}; +use noirc_abi::{decode_string_value, input_parser::InputValueDisplay, AbiType}; use crate::errors::ForeignCallError; @@ -68,11 +68,11 @@ impl ForeignCall { // We must use a flat map here as each value in a struct will be in a separate input value let mut input_values_as_fields = input_values.iter().flat_map(|values| values.iter().map(|value| value.to_field())); - let decoded_value = decode_value(&mut input_values_as_fields, &abi_type)?; - let json_value = JsonTypes::try_from_input_value(&decoded_value, &abi_type)?; + let input_value_display = + InputValueDisplay::try_from_fields(&mut input_values_as_fields, abi_type)?; - println!("{json_value}"); + println!("{input_value_display}"); Ok(()) } } diff --git a/crates/noirc_abi/src/input_parser/json.rs b/crates/noirc_abi/src/input_parser/json.rs index 7a0cd76698d..6468b48c857 100644 --- a/crates/noirc_abi/src/input_parser/json.rs +++ b/crates/noirc_abi/src/input_parser/json.rs @@ -59,7 +59,7 @@ pub(crate) fn serialize_to_json( #[derive(Debug, Deserialize, Serialize, Clone)] #[serde(untagged)] -pub enum JsonTypes { +pub(super) enum JsonTypes { // This is most likely going to be a hex string // But it is possible to support UTF-8 String(String), @@ -78,7 +78,7 @@ pub enum JsonTypes { } impl JsonTypes { - pub fn try_from_input_value( + pub(super) fn try_from_input_value( value: &InputValue, abi_type: &AbiType, ) -> Result { diff --git a/crates/noirc_abi/src/input_parser/mod.rs b/crates/noirc_abi/src/input_parser/mod.rs index 6818f40786c..e4adbb3d8cf 100644 --- a/crates/noirc_abi/src/input_parser/mod.rs +++ b/crates/noirc_abi/src/input_parser/mod.rs @@ -1,4 +1,4 @@ -pub mod json; +mod json; mod toml; use std::collections::BTreeMap; @@ -6,8 +6,8 @@ use std::collections::BTreeMap; use acvm::FieldElement; use serde::Serialize; -use crate::errors::InputParserError; -use crate::{Abi, AbiType}; +use crate::errors::{AbiError, InputParserError}; +use crate::{decode_value, Abi, AbiType}; /// This is what all formats eventually transform into /// For example, a toml file will parse into TomlTypes /// and those TomlTypes will be mapped to Value @@ -67,6 +67,35 @@ impl InputValue { } } +/// In order to display an `InputValue` we need an `AbiType` to accurately +/// convert the value into a human-readable format. +pub struct InputValueDisplay { + input_value: InputValue, + abi_type: AbiType, +} + +impl InputValueDisplay { + pub fn try_from_fields( + field_iterator: &mut impl Iterator, + abi_type: AbiType, + ) -> Result { + let input_value = decode_value(field_iterator, &abi_type)?; + Ok(InputValueDisplay { input_value, abi_type }) + } +} + +impl std::fmt::Display for InputValueDisplay { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + // From the docs: https://doc.rust-lang.org/std/fmt/struct.Error.html + // This type does not support transmission of an error other than that an error + // occurred. Any extra information must be arranged to be transmitted through + // some other means. + let json_value = json::JsonTypes::try_from_input_value(&self.input_value, &self.abi_type) + .map_err(|_| std::fmt::Error)?; + write!(f, "{}", serde_json::to_string(&json_value).map_err(|_| std::fmt::Error)?) + } +} + /// The different formats that are supported when parsing /// the initial witness values #[cfg_attr(test, derive(strum_macros::EnumIter))] diff --git a/crates/noirc_abi/src/lib.rs b/crates/noirc_abi/src/lib.rs index 86f9edc73bd..5f8c22a6652 100644 --- a/crates/noirc_abi/src/lib.rs +++ b/crates/noirc_abi/src/lib.rs @@ -368,7 +368,7 @@ impl Abi { } } -pub fn decode_value( +fn decode_value( field_iterator: &mut impl Iterator, value_type: &AbiType, ) -> Result { From 6acc242bae48aee7e1de013ceadb6587dc900296 Mon Sep 17 00:00:00 2001 From: jfecher Date: Mon, 31 Jul 2023 09:03:15 -0500 Subject: [PATCH 06/50] fix: Fix methods not mutating fields (#2087) * Fix methods not mutating fields * Update doc comment --- .../tests/test_data/references/src/main.nr | 19 ++++++ .../src/ssa_refactor/ssa_gen/mod.rs | 4 +- crates/noirc_frontend/src/ast/expression.rs | 11 +++- crates/noirc_frontend/src/ast/statement.rs | 2 +- .../noirc_frontend/src/hir/type_check/expr.rs | 61 ++++++++++++++++--- crates/noirc_frontend/src/parser/parser.rs | 2 +- 6 files changed, 85 insertions(+), 14 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/references/src/main.nr b/crates/nargo_cli/tests/test_data/references/src/main.nr index d2c0b7f1244..b112875b9ff 100644 --- a/crates/nargo_cli/tests/test_data/references/src/main.nr +++ b/crates/nargo_cli/tests/test_data/references/src/main.nr @@ -30,6 +30,8 @@ fn main(mut x: Field) { }; *c.bar.array = [3, 4]; assert(*c.bar.array == [3, 4]); + + regression_1887(); } fn add1(x: &mut Field) { @@ -58,3 +60,20 @@ impl S { fn mutate_copy(mut a: Field) { a = 7; } + +// Previously the `foo.bar` in `foo.bar.mutate()` would insert an automatic dereference +// of `foo` which caused the method to wrongly be mutating a copy of bar rather than the original. +fn regression_1887() { + let foo = &mut Foo { bar: Bar { x: 0 } }; + foo.bar.mutate(); + assert(foo.bar.x == 32); +} + +struct Foo { bar: Bar } +struct Bar { x: Field } + +impl Bar { + fn mutate(&mut self) { + self.x = 32; + } +} diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs index 2b6db4e7586..710450eb1e6 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs @@ -185,7 +185,9 @@ impl<'a> FunctionContext<'a> { } }) } - noirc_frontend::UnaryOp::Dereference => self.dereference(&rhs, &unary.result_type), + noirc_frontend::UnaryOp::Dereference { .. } => { + self.dereference(&rhs, &unary.result_type) + } } } diff --git a/crates/noirc_frontend/src/ast/expression.rs b/crates/noirc_frontend/src/ast/expression.rs index e36f5b5d260..1f1d226310f 100644 --- a/crates/noirc_frontend/src/ast/expression.rs +++ b/crates/noirc_frontend/src/ast/expression.rs @@ -271,7 +271,14 @@ pub enum UnaryOp { Minus, Not, MutableReference, - Dereference, + + /// If implicitly_added is true, this operation was implicitly added by the compiler for a + /// field dereference. The compiler may undo some of these implicitly added dereferences if + /// the reference later turns out to be needed (e.g. passing a field by reference to a function + /// requiring an &mut parameter). + Dereference { + implicitly_added: bool, + }, } impl UnaryOp { @@ -496,7 +503,7 @@ impl Display for UnaryOp { UnaryOp::Minus => write!(f, "-"), UnaryOp::Not => write!(f, "!"), UnaryOp::MutableReference => write!(f, "&mut"), - UnaryOp::Dereference => write!(f, "*"), + UnaryOp::Dereference { .. } => write!(f, "*"), } } } diff --git a/crates/noirc_frontend/src/ast/statement.rs b/crates/noirc_frontend/src/ast/statement.rs index 7292d227c3e..e35394e0729 100644 --- a/crates/noirc_frontend/src/ast/statement.rs +++ b/crates/noirc_frontend/src/ast/statement.rs @@ -456,7 +456,7 @@ impl LValue { })), LValue::Dereference(lvalue) => { ExpressionKind::Prefix(Box::new(crate::PrefixExpression { - operator: crate::UnaryOp::Dereference, + operator: crate::UnaryOp::Dereference { implicitly_added: false }, rhs: lvalue.as_expression(span), })) } diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index 2c6578944be..8c396ea6814 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -280,6 +280,12 @@ impl<'interner> TypeChecker<'interner> { /// if the given object type is already a mutable reference. If not, add one. /// This is used to automatically transform a method call: `foo.bar()` into a function /// call: `bar(&mut foo)`. + /// + /// A notable corner case of this function is where it interacts with auto-deref of `.`. + /// If a field is being mutated e.g. `foo.bar.mutate_bar()` where `foo: &mut Foo`, the compiler + /// will insert a dereference before bar `(*foo).bar.mutate_bar()` which would cause us to + /// mutate a copy of bar rather than a reference to it. We must check for this corner case here + /// and remove the implicitly added dereference operator if we find one. fn try_add_mutable_reference_to_object( &mut self, method_call: &mut HirMethodCallExpression, @@ -306,19 +312,56 @@ impl<'interner> TypeChecker<'interner> { } let new_type = Type::MutableReference(Box::new(actual_type)); - argument_types[0].0 = new_type.clone(); - method_call.object = - self.interner.push_expr(HirExpression::Prefix(HirPrefixExpression { - operator: UnaryOp::MutableReference, - rhs: method_call.object, - })); - self.interner.push_expr_type(&method_call.object, new_type); + + // First try to remove a dereference operator that may have been implicitly + // inserted by a field access expression `foo.bar` on a mutable reference `foo`. + if self.try_remove_implicit_dereference(method_call.object).is_none() { + // If that didn't work, then wrap the whole expression in an `&mut` + method_call.object = + self.interner.push_expr(HirExpression::Prefix(HirPrefixExpression { + operator: UnaryOp::MutableReference, + rhs: method_call.object, + })); + self.interner.push_expr_type(&method_call.object, new_type); + } } } } } + /// Given a method object: `(*foo).bar` of a method call `(*foo).bar.baz()`, remove the + /// implicitly added dereference operator if one is found. + /// + /// Returns Some(()) if a dereference was removed and None otherwise. + fn try_remove_implicit_dereference(&mut self, object: ExprId) -> Option<()> { + match self.interner.expression(&object) { + HirExpression::MemberAccess(access) => { + self.try_remove_implicit_dereference(access.lhs)?; + + // Since we removed a dereference, instead of returning the field directly, + // we expect to be returning a reference to the field, so update the type accordingly. + let current_type = self.interner.id_type(object); + let reference_type = Type::MutableReference(Box::new(current_type)); + self.interner.push_expr_type(&object, reference_type); + Some(()) + } + HirExpression::Prefix(prefix) => match prefix.operator { + UnaryOp::Dereference { implicitly_added: true } => { + // Found a dereference we can remove. Now just replace it with its rhs to remove it. + let rhs = self.interner.expression(&prefix.rhs); + self.interner.replace_expr(&object, rhs); + + let rhs_type = self.interner.id_type(prefix.rhs); + self.interner.push_expr_type(&object, rhs_type); + Some(()) + } + _ => None, + }, + _ => None, + } + } + fn check_index_expression(&mut self, index_expr: expr::HirIndexExpression) -> Type { let index_type = self.check_expression(&index_expr.index); let span = self.interner.expr_span(&index_expr.index); @@ -525,7 +568,7 @@ impl<'interner> TypeChecker<'interner> { let dereference_lhs = |this: &mut Self, lhs_type, element| { let old_lhs = *access_lhs; *access_lhs = this.interner.push_expr(HirExpression::Prefix(HirPrefixExpression { - operator: crate::UnaryOp::Dereference, + operator: crate::UnaryOp::Dereference { implicitly_added: true }, rhs: old_lhs, })); this.interner.push_expr_type(&old_lhs, lhs_type); @@ -1006,7 +1049,7 @@ impl<'interner> TypeChecker<'interner> { crate::UnaryOp::MutableReference => { Type::MutableReference(Box::new(rhs_type.follow_bindings())) } - crate::UnaryOp::Dereference => { + crate::UnaryOp::Dereference { implicitly_added: _ } => { let element_type = self.interner.next_type_variable(); unify(Type::MutableReference(Box::new(element_type.clone()))); element_type diff --git a/crates/noirc_frontend/src/parser/parser.rs b/crates/noirc_frontend/src/parser/parser.rs index c8142ffa947..c6d84416975 100644 --- a/crates/noirc_frontend/src/parser/parser.rs +++ b/crates/noirc_frontend/src/parser/parser.rs @@ -1267,7 +1267,7 @@ where { just(Token::Star) .ignore_then(term_parser) - .map(|rhs| ExpressionKind::prefix(UnaryOp::Dereference, rhs)) + .map(|rhs| ExpressionKind::prefix(UnaryOp::Dereference { implicitly_added: false }, rhs)) } /// Atoms are parameterized on whether constructor expressions are allowed or not. From 8981c7d69716ea9b1ecbaece8d7534f41954dcd4 Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Mon, 31 Jul 2023 19:31:03 +0200 Subject: [PATCH 07/50] chore: use witnesses from the generated acir in the ABI (#2095) * Use witnesses from the generated acir in the ABI * Code review --- crates/noirc_evaluator/src/ssa_refactor.rs | 12 ++++++--- .../src/ssa_refactor/abi_gen/mod.rs | 25 ++++++++++++------- .../acir_gen/acir_ir/acir_variable.rs | 23 ++++++++++++++++- .../acir_gen/acir_ir/generated_acir.rs | 3 +++ .../src/ssa_refactor/acir_gen/mod.rs | 16 +++++++----- 5 files changed, 60 insertions(+), 19 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa_refactor.rs b/crates/noirc_evaluator/src/ssa_refactor.rs index fa3b7f05a86..6326b45554d 100644 --- a/crates/noirc_evaluator/src/ssa_refactor.rs +++ b/crates/noirc_evaluator/src/ssa_refactor.rs @@ -77,10 +77,16 @@ pub fn create_circuit( show_output: bool, ) -> Result<(Circuit, DebugInfo, Abi), RuntimeError> { let func_sig = program.main_function_signature.clone(); - let GeneratedAcir { current_witness_index, opcodes, return_witnesses, locations, .. } = - optimize_into_acir(program, show_output, enable_ssa_logging, enable_brillig_logging)?; + let GeneratedAcir { + current_witness_index, + opcodes, + return_witnesses, + locations, + input_witnesses, + .. + } = optimize_into_acir(program, show_output, enable_ssa_logging, enable_brillig_logging)?; - let abi = gen_abi(func_sig, return_witnesses.clone()); + let abi = gen_abi(func_sig, &input_witnesses, return_witnesses.clone()); let public_abi = abi.clone().public_abi(); let public_parameters = diff --git a/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs index db39b1c8110..778d8aba8d5 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs @@ -1,14 +1,18 @@ use std::collections::BTreeMap; use acvm::acir::native_types::Witness; -use iter_extended::{btree_map, vecmap}; +use iter_extended::btree_map; use noirc_abi::{Abi, AbiParameter, FunctionSignature}; /// Arranges a function signature and a generated circuit's return witnesses into a /// `noirc_abi::Abi`. -pub(crate) fn gen_abi(func_sig: FunctionSignature, return_witnesses: Vec) -> Abi { +pub(crate) fn gen_abi( + func_sig: FunctionSignature, + input_witnesses: &[Witness], + return_witnesses: Vec, +) -> Abi { let (parameters, return_type) = func_sig; - let param_witnesses = param_witnesses_from_abi_param(¶meters); + let param_witnesses = param_witnesses_from_abi_param(¶meters, input_witnesses); Abi { parameters, return_type, param_witnesses, return_witnesses } } @@ -16,14 +20,17 @@ pub(crate) fn gen_abi(func_sig: FunctionSignature, return_witnesses: Vec, + input_witnesses: &[Witness], ) -> BTreeMap> { - let mut offset = 1; + let mut idx = 0_usize; + btree_map(abi_params, |param| { let num_field_elements_needed = param.typ.field_count(); - let idx_start = offset; - let idx_end = idx_start + num_field_elements_needed; - let witnesses = vecmap(idx_start..idx_end, Witness); - offset += num_field_elements_needed; - (param.name.clone(), witnesses) + let mut wit = Vec::new(); + for _ in 0..num_field_elements_needed { + wit.push(input_witnesses[idx]); + idx += 1; + } + (param.name.clone(), wit) }) } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index 8c7fe1e9b6a..d953322e567 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -110,6 +110,26 @@ pub(crate) struct AcirContext { } impl AcirContext { + pub(crate) fn current_witness_index(&self) -> Witness { + self.acir_ir.current_witness_index() + } + + pub(crate) fn extract_witness(&self, inputs: &[AcirValue]) -> Vec { + inputs + .iter() + .flat_map(|value| value.clone().flatten()) + .map(|value| { + self.vars + .get(&value.0) + .expect("ICE: undeclared AcirVar") + .to_expression() + .to_witness() + .expect("ICE - cannot extract a witness") + .0 + }) + .collect() + } + /// Adds a constant to the context and assigns a Variable to represent it pub(crate) fn add_constant(&mut self, constant: FieldElement) -> AcirVar { let constant_data = AcirVarData::Const(constant); @@ -808,7 +828,8 @@ impl AcirContext { } /// Terminates the context and takes the resulting `GeneratedAcir` - pub(crate) fn finish(self) -> GeneratedAcir { + pub(crate) fn finish(mut self, inputs: Vec) -> GeneratedAcir { + self.acir_ir.input_witnesses = vecmap(inputs, Witness); self.acir_ir } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index d80537a074a..459458fc03e 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -40,6 +40,9 @@ pub(crate) struct GeneratedAcir { /// abi's return type. pub(crate) return_witnesses: Vec, + /// All witness indices which are inputs to the main function + pub(crate) input_witnesses: Vec, + /// Correspondance between an opcode index (in opcodes) and the source code location which generated it pub(crate) locations: HashMap, diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index 3bf18a2d86a..ad10bed96f9 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -2,6 +2,7 @@ use std::collections::{HashMap, HashSet}; use std::fmt::Debug; +use std::ops::RangeInclusive; use crate::brillig::brillig_ir::BrilligContext; use crate::{ @@ -172,8 +173,7 @@ impl Context { ) -> Result { let dfg = &main_func.dfg; let entry_block = &dfg[main_func.entry_block()]; - - self.convert_ssa_block_params(entry_block.parameters(), dfg)?; + let input_witness = self.convert_ssa_block_params(entry_block.parameters(), dfg)?; for instruction_id in entry_block.instructions() { self.convert_ssa_instruction(*instruction_id, dfg, ssa, &brillig, allow_log_ops)?; @@ -181,7 +181,7 @@ impl Context { self.convert_ssa_return(entry_block.unwrap_terminator(), dfg); - Ok(self.acir_context.finish()) + Ok(self.acir_context.finish(input_witness.collect())) } fn convert_brillig_main( @@ -195,6 +195,7 @@ impl Context { let typ = dfg.type_of_value(*param_id); self.create_value_from_type(&typ, &mut |this, _| Ok(this.acir_context.add_variable())) })?; + let witness_inputs = self.acir_context.extract_witness(&inputs); let outputs: Vec = vecmap(main_func.returns(), |result_id| dfg.type_of_value(*result_id).into()); @@ -213,7 +214,7 @@ impl Context { self.acir_context.return_var(acir_var); } - Ok(self.acir_context.finish()) + Ok(self.acir_context.finish(witness_inputs)) } /// Adds and binds `AcirVar`s for each numeric block parameter or block parameter array element. @@ -221,7 +222,9 @@ impl Context { &mut self, params: &[ValueId], dfg: &DataFlowGraph, - ) -> Result<(), AcirGenError> { + ) -> Result, AcirGenError> { + // The first witness (if any) is the next one + let start_witness = self.acir_context.current_witness_index().0 + 1; for param_id in params { let typ = dfg.type_of_value(*param_id); let value = self.convert_ssa_block_param(&typ)?; @@ -238,7 +241,8 @@ impl Context { } self.ssa_values.insert(*param_id, value); } - Ok(()) + let end_witness = self.acir_context.current_witness_index().0; + Ok(start_witness..=end_witness) } fn convert_ssa_block_param(&mut self, param_type: &Type) -> Result { From 9b417da0eef28a29dbe0f339ee19b8dd9859dc4d Mon Sep 17 00:00:00 2001 From: Ethan-000 Date: Mon, 31 Jul 2023 19:22:40 +0100 Subject: [PATCH 08/50] chore(ssa refactor): Implement `acir_gen` errors (#2071) * implement acir gen errors * comment * remove unwrap * rename to internal error * comment * comment * . * . * . * review * . * chore: fix merge conflict * chore: make multiplication of 2 witnesses more explicit * Update crates/noirc_evaluator/src/errors.rs --------- Co-authored-by: Tom French <15848336+TomAFrench@users.noreply.github.com> Co-authored-by: TomAFrench Co-authored-by: jfecher --- crates/noirc_evaluator/src/errors.rs | 219 +++++++--------- .../src/ssa_refactor/acir_gen/acir_ir.rs | 1 - .../acir_gen/acir_ir/acir_variable.rs | 208 ++++++++++------ .../ssa_refactor/acir_gen/acir_ir/errors.rs | 62 ----- .../acir_gen/acir_ir/generated_acir.rs | 130 ++++++---- .../src/ssa_refactor/acir_gen/acir_ir/sort.rs | 27 +- .../src/ssa_refactor/acir_gen/mod.rs | 235 +++++++++++------- 7 files changed, 459 insertions(+), 423 deletions(-) delete mode 100644 crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs diff --git a/crates/noirc_evaluator/src/errors.rs b/crates/noirc_evaluator/src/errors.rs index 2d8b02008c6..6d53668d7cb 100644 --- a/crates/noirc_evaluator/src/errors.rs +++ b/crates/noirc_evaluator/src/errors.rs @@ -1,151 +1,104 @@ +//! Noir Evaluator has two types of errors +//! +//! [RuntimeError]s that should be displayed to the user +//! +//! [InternalError]s that are used for checking internal logics of the SSA +//! +//! An Error of the former is a user Error +//! +//! An Error of the latter is an error in the implementation of the compiler +use acvm::FieldElement; use noirc_errors::{CustomDiagnostic as Diagnostic, FileDiagnostic, Location}; use thiserror::Error; -#[derive(Debug)] -pub struct RuntimeError { - pub location: Option, - pub kind: RuntimeErrorKind, -} - -impl RuntimeError { - // XXX: In some places, we strip the span because we do not want span to - // be introduced into the binary op or low level function code, for simplicity. - // - // It's possible to have it there, but it means we will need to proliferate the code with span - // - // This does make error reporting, less specific! - pub fn remove_span(self) -> RuntimeErrorKind { - self.kind - } - - pub fn new(kind: RuntimeErrorKind, location: Option) -> RuntimeError { - RuntimeError { location, kind } - } - - // Keep one of the two location which is Some, if possible - // This is used when we optimize instructions so that we do not lose track of location - pub fn merge_location(a: Option, b: Option) -> Option { - match (a, b) { - (Some(loc), _) | (_, Some(loc)) => Some(loc), - (None, None) => None, - } - } +#[derive(Debug, PartialEq, Eq, Clone, Error)] +pub enum RuntimeError { + // We avoid showing the actual lhs and rhs since most of the time they are just 0 + // and 1 respectively. This would confuse users if a constraint such as + // assert(foo < bar) fails with "failed constraint: 0 = 1." + #[error("Failed constraint")] + FailedConstraint { lhs: FieldElement, rhs: FieldElement, location: Option }, + #[error(transparent)] + InternalError(#[from] InternalError), + #[error("Index out of bounds, array has size {index:?}, but index was {array_size:?}")] + IndexOutOfBounds { index: usize, array_size: usize, location: Option }, + #[error("All Witnesses are by default u{num_bits:?} Applying this type does not apply any constraints.\n We also currently do not allow integers of size more than {num_bits:?}, this will be handled by BigIntegers.")] + InvalidRangeConstraint { num_bits: u32, location: Option }, + #[error("Expected array index to fit into a u64")] + TypeConversion { from: String, into: String, location: Option }, + #[error("{name:?} is not initialized")] + UnInitialized { name: String, location: Option }, + #[error("Integer sized {num_bits:?} is over the max supported size of {max_num_bits:?}")] + UnsupportedIntegerSize { num_bits: u32, max_num_bits: u32, location: Option }, } -impl From for RuntimeError { - fn from(kind: RuntimeErrorKind) -> RuntimeError { - RuntimeError { location: None, kind } - } +#[derive(Debug, PartialEq, Eq, Clone, Error)] +pub enum InternalError { + #[error("ICE: Both expressions should have degree<=1")] + DegreeNotReduced { location: Option }, + #[error("Try to get element from empty array")] + EmptyArray { location: Option }, + #[error("ICE: {message:?}")] + General { message: String, location: Option }, + #[error("ICE: {name:?} missing {arg:?} arg")] + MissingArg { name: String, arg: String, location: Option }, + #[error("ICE: {name:?} should be a constant")] + NotAConstant { name: String, location: Option }, + #[error("{name:?} is not implemented yet")] + NotImplemented { name: String, location: Option }, + #[error("ICE: Undeclared AcirVar")] + UndeclaredAcirVar { location: Option }, + #[error("ICE: Expected {expected:?}, found {found:?}")] + UnExpected { expected: String, found: String, location: Option }, } impl From for FileDiagnostic { - fn from(err: RuntimeError) -> Self { - let file_id = err.location.map(|loc| loc.file).unwrap(); - FileDiagnostic { file_id, diagnostic: err.into() } + fn from(error: RuntimeError) -> Self { + match error { + RuntimeError::InternalError(ref ice_error) => match ice_error { + InternalError::DegreeNotReduced { location } + | InternalError::EmptyArray { location } + | InternalError::General { location, .. } + | InternalError::MissingArg { location, .. } + | InternalError::NotAConstant { location, .. } + | InternalError::NotImplemented { location, .. } + | InternalError::UndeclaredAcirVar { location } + | InternalError::UnExpected { location, .. } => { + let file_id = location.map(|loc| loc.file).unwrap(); + FileDiagnostic { file_id, diagnostic: error.into() } + } + }, + RuntimeError::FailedConstraint { location, .. } + | RuntimeError::IndexOutOfBounds { location, .. } + | RuntimeError::InvalidRangeConstraint { location, .. } + | RuntimeError::TypeConversion { location, .. } + | RuntimeError::UnInitialized { location, .. } + | RuntimeError::UnsupportedIntegerSize { location, .. } => { + let file_id = location.map(|loc| loc.file).unwrap(); + FileDiagnostic { file_id, diagnostic: error.into() } + } + } } } -#[derive(Error, Debug)] -pub enum RuntimeErrorKind { - // Array errors - #[error("Out of bounds")] - ArrayOutOfBounds { index: u128, bound: u128 }, - - #[error("index out of bounds: the len is {index} but the index is {bound}")] - IndexOutOfBounds { index: u32, bound: u128 }, - - #[error("cannot call {func_name} function in non main function")] - FunctionNonMainContext { func_name: String }, - - // Environment errors - #[error("Cannot find Array")] - ArrayNotFound { found_type: String, name: String }, - - #[error("Not an object")] - NotAnObject, - - #[error("Invalid id")] - InvalidId, - - #[error("Attempt to divide by zero")] - DivisionByZero, - - #[error("Failed range constraint when constraining to {0} bits")] - FailedRangeConstraint(u32), - - #[error("Unsupported integer size of {num_bits} bits. The maximum supported size is {max_num_bits} bits.")] - UnsupportedIntegerSize { num_bits: u32, max_num_bits: u32 }, - - #[error("Failed constraint")] - FailedConstraint, - - #[error( - "All Witnesses are by default u{0}. Applying this type does not apply any constraints." - )] - DefaultWitnesses(u32), - - #[error("Constraint is always false")] - ConstraintIsAlwaysFalse, - - #[error("ICE: cannot convert signed {0} bit size into field")] - CannotConvertSignedIntoField(u32), - - #[error("we do not allow private ABI inputs to be returned as public outputs")] - PrivateAbiInput, - - #[error("unimplemented")] - Unimplemented(String), - - #[error("Unsupported operation error")] - UnsupportedOp { op: String, first_type: String, second_type: String }, -} - impl From for Diagnostic { fn from(error: RuntimeError) -> Diagnostic { - let span = - if let Some(loc) = error.location { loc.span } else { noirc_errors::Span::new(0..0) }; - match &error.kind { - RuntimeErrorKind::ArrayOutOfBounds { index, bound } => Diagnostic::simple_error( - "index out of bounds".to_string(), - format!("out of bounds error, index is {index} but length is {bound}"), - span, - ), - RuntimeErrorKind::ArrayNotFound { found_type, name } => Diagnostic::simple_error( - format!("cannot find an array with name {name}"), - format!("{found_type} has type"), - span, + match error { + RuntimeError::InternalError(_) => Diagnostic::simple_error( + "Internal Consistency Evaluators Errors: \n + This is likely a bug. Consider Opening an issue at https://github.com/noir-lang/noir/issues".to_owned(), + "".to_string(), + noirc_errors::Span::new(0..0) ), - RuntimeErrorKind::NotAnObject - | RuntimeErrorKind::InvalidId - | RuntimeErrorKind::DivisionByZero - | RuntimeErrorKind::FailedRangeConstraint(_) - | RuntimeErrorKind::UnsupportedIntegerSize { .. } - | RuntimeErrorKind::FailedConstraint - | RuntimeErrorKind::DefaultWitnesses(_) - | RuntimeErrorKind::CannotConvertSignedIntoField(_) - | RuntimeErrorKind::IndexOutOfBounds { .. } - | RuntimeErrorKind::PrivateAbiInput => { - Diagnostic::simple_error("".to_owned(), error.kind.to_string(), span) + RuntimeError::FailedConstraint { location, .. } + | RuntimeError::IndexOutOfBounds { location, .. } + | RuntimeError::InvalidRangeConstraint { location, .. } + | RuntimeError::TypeConversion { location, .. } + | RuntimeError::UnInitialized { location, .. } + | RuntimeError::UnsupportedIntegerSize { location, .. } => { + let span = if let Some(loc) = location { loc.span } else { noirc_errors::Span::new(0..0) }; + Diagnostic::simple_error("".to_owned(), error.to_string(), span) } - RuntimeErrorKind::UnsupportedOp { op, first_type, second_type } => { - Diagnostic::simple_error( - "unsupported operation".to_owned(), - format!("no support for {op} with types {first_type} and {second_type}"), - span, - ) - } - RuntimeErrorKind::ConstraintIsAlwaysFalse if error.location.is_some() => { - Diagnostic::simple_error("".to_owned(), error.kind.to_string(), span) - } - RuntimeErrorKind::ConstraintIsAlwaysFalse => { - Diagnostic::from_message(&error.kind.to_string()) - } - RuntimeErrorKind::Unimplemented(message) => Diagnostic::from_message(message), - RuntimeErrorKind::FunctionNonMainContext { func_name } => Diagnostic::simple_error( - "cannot call function outside of main".to_owned(), - format!("function {func_name} can only be called in main"), - span, - ), } } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs index 6e715002161..96800b22ad0 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs @@ -1,4 +1,3 @@ pub(crate) mod acir_variable; -pub(crate) mod errors; pub(crate) mod generated_acir; pub(crate) mod sort; diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index d953322e567..6d8178b6a2c 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -1,5 +1,6 @@ -use super::{errors::AcirGenError, generated_acir::GeneratedAcir}; +use super::generated_acir::GeneratedAcir; use crate::brillig::brillig_gen::brillig_directive; +use crate::errors::{InternalError, RuntimeError}; use crate::ssa_refactor::acir_gen::{AcirDynamicArray, AcirValue}; use crate::ssa_refactor::ir::types::Type as SsaType; use crate::ssa_refactor::ir::{instruction::Endian, types::NumericType}; @@ -9,7 +10,6 @@ use acvm::acir::{ brillig::Opcode as BrilligOpcode, circuit::brillig::{BrilligInputs, BrilligOutputs}, }; - use acvm::{ acir::{ circuit::opcodes::FunctionInput, @@ -18,7 +18,7 @@ use acvm::{ }, FieldElement, }; -use iter_extended::vecmap; +use iter_extended::{try_vecmap, vecmap}; use noirc_errors::Location; use std::collections::HashMap; use std::{borrow::Cow, hash::Hash}; @@ -182,7 +182,7 @@ impl AcirContext { &mut self, var: AcirVar, predicate: AcirVar, - ) -> Result { + ) -> Result { let var_data = &self.vars[&var]; if let AcirVarData::Const(constant) = var_data { // Note that this will return a 0 if the inverse is not available @@ -199,7 +199,7 @@ impl AcirContext { inverse_code, vec![AcirValue::Var(var, field_type.clone())], vec![field_type], - ); + )?; let inverted_var = Self::expect_one_var(results); let should_be_one = self.mul_var(inverted_var, var)?; @@ -209,7 +209,7 @@ impl AcirContext { } // Constrains `var` to be equal to the constant value `1` - pub(crate) fn assert_eq_one(&mut self, var: AcirVar) -> Result<(), AcirGenError> { + pub(crate) fn assert_eq_one(&mut self, var: AcirVar) -> Result<(), RuntimeError> { let one = self.add_constant(FieldElement::one()); self.assert_eq_var(var, one) } @@ -222,7 +222,7 @@ impl AcirContext { &mut self, var: AcirVar, predicate: AcirVar, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { let pred_mul_var = self.mul_var(var, predicate)?; self.assert_eq_var(pred_mul_var, predicate) } @@ -240,7 +240,7 @@ impl AcirContext { /// Returns an `AcirVar` that is `1` if `lhs` equals `rhs` and /// 0 otherwise. - pub(crate) fn eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { + pub(crate) fn eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; @@ -258,7 +258,7 @@ impl AcirContext { lhs: AcirVar, rhs: AcirVar, typ: AcirType, - ) -> Result { + ) -> Result { let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)]; let outputs = self.black_box_function(BlackBoxFunc::XOR, inputs)?; Ok(outputs[0]) @@ -270,7 +270,7 @@ impl AcirContext { lhs: AcirVar, rhs: AcirVar, typ: AcirType, - ) -> Result { + ) -> Result { let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)]; let outputs = self.black_box_function(BlackBoxFunc::AND, inputs)?; Ok(outputs[0]) @@ -282,7 +282,7 @@ impl AcirContext { lhs: AcirVar, rhs: AcirVar, typ: AcirType, - ) -> Result { + ) -> Result { let bit_size = typ.bit_size(); if bit_size == 1 { // Operands are booleans @@ -305,7 +305,7 @@ impl AcirContext { } /// Constrains the `lhs` and `rhs` to be equal. - pub(crate) fn assert_eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<(), AcirGenError> { + pub(crate) fn assert_eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<(), RuntimeError> { // TODO: could use sub_var and then assert_eq_zero let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; @@ -316,7 +316,7 @@ impl AcirContext { Ok(()) } else { // Constraint is always false - this program is unprovable - Err(AcirGenError::BadConstantEquality { + Err(RuntimeError::FailedConstraint { lhs: *lhs_const, rhs: *rhs_const, location: self.get_location(), @@ -338,7 +338,7 @@ impl AcirContext { rhs: AcirVar, typ: AcirType, predicate: AcirVar, - ) -> Result { + ) -> Result { let numeric_type = match typ { AcirType::NumericType(numeric_type) => numeric_type, AcirType::Array(_, _) => { @@ -365,7 +365,7 @@ impl AcirContext { /// Adds a new Variable to context whose value will /// be constrained to be the multiplication of `lhs` and `rhs` - pub(crate) fn mul_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { + pub(crate) fn mul_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; let result = match (lhs_data, rhs_data) { @@ -412,14 +412,14 @@ impl AcirContext { /// Adds a new Variable to context whose value will /// be constrained to be the subtraction of `lhs` and `rhs` - pub(crate) fn sub_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { + pub(crate) fn sub_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { let neg_rhs = self.neg_var(rhs); self.add_var(lhs, neg_rhs) } /// Adds a new Variable to context whose value will /// be constrained to be the addition of `lhs` and `rhs` - pub(crate) fn add_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { + pub(crate) fn add_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result { let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; let result_data = if let (AcirVarData::Const(lhs_const), AcirVarData::Const(rhs_const)) = @@ -434,7 +434,7 @@ impl AcirContext { } /// Adds a new variable that is constrained to be the logical NOT of `x`. - pub(crate) fn not_var(&mut self, x: AcirVar, typ: AcirType) -> Result { + pub(crate) fn not_var(&mut self, x: AcirVar, typ: AcirType) -> Result { let bit_size = typ.bit_size(); // Subtracting from max flips the bits let max = self.add_constant(FieldElement::from((1_u128 << bit_size) - 1)); @@ -453,7 +453,7 @@ impl AcirContext { lhs: AcirVar, rhs: AcirVar, _typ: AcirType, - ) -> Result { + ) -> Result { let rhs_data = &self.vars[&rhs]; // Compute 2^{rhs} @@ -473,7 +473,7 @@ impl AcirContext { rhs: AcirVar, bit_size: u32, predicate: AcirVar, - ) -> Result<(AcirVar, AcirVar), AcirGenError> { + ) -> Result<(AcirVar, AcirVar), RuntimeError> { let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; let predicate_data = &self.vars[&predicate]; @@ -505,7 +505,7 @@ impl AcirContext { lhs: AcirVar, rhs: AcirVar, bit_size: u32, - ) -> Result<(AcirVar, AcirVar), AcirGenError> { + ) -> Result<(AcirVar, AcirVar), RuntimeError> { let lhs_data = &self.vars[&lhs].clone(); let rhs_data = &self.vars[&rhs].clone(); @@ -529,7 +529,7 @@ impl AcirContext { rhs: AcirVar, bit_size: u32, predicate: AcirVar, - ) -> Result { + ) -> Result { let (_, remainder) = self.euclidean_division_var(lhs, rhs, bit_size, predicate)?; Ok(remainder) } @@ -550,7 +550,7 @@ impl AcirContext { rhs: AcirVar, typ: AcirType, predicate: AcirVar, - ) -> Result { + ) -> Result { let rhs_data = &self.vars[&rhs]; // Compute 2^{rhs} @@ -565,8 +565,11 @@ impl AcirContext { /// Converts the `AcirVar` to a `Witness` if it hasn't been already, and appends it to the /// `GeneratedAcir`'s return witnesses. - pub(crate) fn return_var(&mut self, acir_var: AcirVar) { - let acir_var_data = self.vars.get(&acir_var).expect("ICE: return of undeclared AcirVar"); + pub(crate) fn return_var(&mut self, acir_var: AcirVar) -> Result<(), InternalError> { + let acir_var_data = match self.vars.get(&acir_var) { + Some(acir_var_data) => acir_var_data, + None => return Err(InternalError::UndeclaredAcirVar { location: self.get_location() }), + }; // TODO: Add caching to prevent expressions from being needlessly duplicated let witness = match acir_var_data { AcirVarData::Const(constant) => { @@ -576,6 +579,7 @@ impl AcirContext { AcirVarData::Witness(witness) => *witness, }; self.acir_ir.push_return_witness(witness); + Ok(()) } /// Constrains the `AcirVar` variable to be of type `NumericType`. @@ -583,7 +587,7 @@ impl AcirContext { &mut self, variable: AcirVar, numeric_type: &NumericType, - ) -> Result { + ) -> Result { let data = &self.vars[&variable]; match numeric_type { NumericType::Signed { bit_size } | NumericType::Unsigned { bit_size } => { @@ -606,7 +610,7 @@ impl AcirContext { lhs: AcirVar, rhs: u32, max_bit_size: u32, - ) -> Result { + ) -> Result { let lhs_data = &self.vars[&lhs]; let lhs_expr = lhs_data.to_expression(); @@ -631,7 +635,7 @@ impl AcirContext { rhs: AcirVar, bit_size: u32, predicate: AcirVar, - ) -> Result { + ) -> Result { let lhs_data = &self.vars[&lhs]; let rhs_data = &self.vars[&rhs]; @@ -658,7 +662,7 @@ impl AcirContext { rhs: AcirVar, bit_size: u32, predicate: AcirVar, - ) -> Result { + ) -> Result { // Flip the result of calling more than equal method to // compute less than. let comparison = self.more_than_eq_var(lhs, rhs, bit_size, predicate)?; @@ -673,17 +677,31 @@ impl AcirContext { &mut self, name: BlackBoxFunc, mut inputs: Vec, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { // Separate out any arguments that should be constants let constants = match name { BlackBoxFunc::Pedersen => { // The last argument of pedersen is the domain separator, which must be a constant - let domain_var = - inputs.pop().expect("ICE: Pedersen call requires domain separator").into_var(); - - let domain_constant = self.vars[&domain_var] - .as_constant() - .expect("ICE: Domain separator must be a constant"); + let domain_var = match inputs.pop() { + Some(domain_var) => domain_var.into_var()?, + None => { + return Err(RuntimeError::InternalError(InternalError::MissingArg { + name: "pedersen call".to_string(), + arg: "domain separator".to_string(), + location: self.get_location(), + })) + } + }; + + let domain_constant = match self.vars[&domain_var].as_constant() { + Some(domain_constant) => domain_constant, + None => { + return Err(RuntimeError::InternalError(InternalError::NotAConstant { + name: "domain separator".to_string(), + location: self.get_location(), + })) + } + }; vec![domain_constant] } @@ -694,7 +712,7 @@ impl AcirContext { let inputs = self.prepare_inputs_for_black_box_func_call(inputs)?; // Call Black box with `FunctionInput` - let outputs = self.acir_ir.call_black_box(name, inputs, constants); + let outputs = self.acir_ir.call_black_box(name, inputs, constants)?; // Convert `Witness` values which are now constrained to be the output of the // black box function call into `AcirVar`s. @@ -710,7 +728,7 @@ impl AcirContext { fn prepare_inputs_for_black_box_func_call( &mut self, inputs: Vec, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { let mut witnesses = Vec::new(); for input in inputs { for (input, typ) in input.flatten() { @@ -741,15 +759,26 @@ impl AcirContext { radix_var: AcirVar, limb_count_var: AcirVar, result_element_type: AcirType, - ) -> Result, AcirGenError> { - let radix = - self.vars[&radix_var].as_constant().expect("ICE: radix should be a constant").to_u128() - as u32; + ) -> Result, RuntimeError> { + let radix = match self.vars[&radix_var].as_constant() { + Some(radix) => radix.to_u128() as u32, + None => { + return Err(RuntimeError::InternalError(InternalError::NotAConstant { + name: "radix".to_string(), + location: self.get_location(), + })); + } + }; - let limb_count = self.vars[&limb_count_var] - .as_constant() - .expect("ICE: limb_size should be a constant") - .to_u128() as u32; + let limb_count = match self.vars[&limb_count_var].as_constant() { + Some(limb_count) => limb_count.to_u128() as u32, + None => { + return Err(RuntimeError::InternalError(InternalError::NotAConstant { + name: "limb_size".to_string(), + location: self.get_location(), + })); + } + }; let input_expr = &self.vars[&input_var].to_expression(); @@ -785,13 +814,13 @@ impl AcirContext { input_var: AcirVar, limb_count_var: AcirVar, result_element_type: AcirType, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { let two_var = self.add_constant(FieldElement::from(2_u128)); self.radix_decompose(endian, input_var, two_var, limb_count_var, result_element_type) } /// Prints the given `AcirVar`s as witnesses. - pub(crate) fn print(&mut self, input: Vec) -> Result<(), AcirGenError> { + pub(crate) fn print(&mut self, input: Vec) -> Result<(), RuntimeError> { let input = Self::flatten_values(input); let witnesses = vecmap(input, |acir_var| { @@ -850,24 +879,24 @@ impl AcirContext { code: Vec, inputs: Vec, outputs: Vec, - ) -> Vec { - let b_inputs = vecmap(inputs, |i| match i { + ) -> Result, InternalError> { + let b_inputs = try_vecmap(inputs, |i| match i { AcirValue::Var(var, _) => { - BrilligInputs::Single(self.vars[&var].to_expression().into_owned()) + Ok(BrilligInputs::Single(self.vars[&var].to_expression().into_owned())) } AcirValue::Array(vars) => { let mut var_expressions: Vec = Vec::new(); for var in vars { - self.brillig_array_input(&mut var_expressions, var); + self.brillig_array_input(&mut var_expressions, var)?; } - BrilligInputs::Array(var_expressions) + Ok(BrilligInputs::Array(var_expressions)) } AcirValue::DynamicArray(_) => { let mut var_expressions = Vec::new(); - self.brillig_array_input(&mut var_expressions, i); - BrilligInputs::Array(var_expressions) + self.brillig_array_input(&mut var_expressions, i)?; + Ok(BrilligInputs::Array(var_expressions)) } - }); + })?; let mut b_outputs = Vec::new(); let outputs_var = vecmap(outputs, |output| match output { @@ -886,17 +915,21 @@ impl AcirContext { let predicate = self.vars[&predicate].to_expression().into_owned(); self.acir_ir.brillig(Some(predicate), code, b_inputs, b_outputs); - outputs_var + Ok(outputs_var) } - fn brillig_array_input(&mut self, var_expressions: &mut Vec, input: AcirValue) { + fn brillig_array_input( + &mut self, + var_expressions: &mut Vec, + input: AcirValue, + ) -> Result<(), InternalError> { match input { AcirValue::Var(var, _) => { var_expressions.push(self.vars[&var].to_expression().into_owned()); } AcirValue::Array(vars) => { for var in vars { - self.brillig_array_input(var_expressions, var); + self.brillig_array_input(var_expressions, var)?; } } AcirValue::DynamicArray(AcirDynamicArray { block_id, len }) => { @@ -906,18 +939,19 @@ impl AcirContext { self.add_constant(FieldElement::from(i as u128)), AcirType::NumericType(NumericType::NativeField), ); - let index_var = index.into_var(); + let index_var = index.into_var()?; - let value_read_var = self.read_from_memory(block_id, &index_var); + let value_read_var = self.read_from_memory(block_id, &index_var)?; let value_read = AcirValue::Var( value_read_var, AcirType::NumericType(NumericType::NativeField), ); - self.brillig_array_input(var_expressions, value_read); + self.brillig_array_input(var_expressions, value_read)?; } } } + Ok(()) } /// Recursively create acir values for returned arrays. This is necessary because a brillig returned array can have nested arrays as elements. @@ -959,7 +993,7 @@ impl AcirContext { inputs: Vec, bit_size: u32, predicate: AcirVar, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { let len = inputs.len(); // Convert the inputs into expressions let inputs_expr = vecmap(inputs, |input| self.vars[&input].to_expression().into_owned()); @@ -972,7 +1006,7 @@ impl AcirContext { }); // Enforce the outputs to be a permutation of the inputs - self.acir_ir.permutation(&inputs_expr, &output_expr); + self.acir_ir.permutation(&inputs_expr, &output_expr)?; // Enforce the outputs to be sorted for i in 0..(outputs_var.len() - 1) { @@ -982,9 +1016,12 @@ impl AcirContext { Ok(outputs_var) } /// Converts an AcirVar to a Witness - fn var_to_witness(&mut self, var: AcirVar) -> Witness { - let var_data = self.vars.get(&var).expect("ICE: undeclared AcirVar"); - self.acir_ir.get_or_create_witness(&var_data.to_expression()) + fn var_to_witness(&mut self, var: AcirVar) -> Result { + let var_data = match self.vars.get(&var) { + Some(var_data) => var_data, + None => return Err(InternalError::UndeclaredAcirVar { location: self.get_location() }), + }; + Ok(self.acir_ir.get_or_create_witness(&var_data.to_expression())) } /// Constrain lhs to be less than rhs @@ -994,40 +1031,50 @@ impl AcirContext { rhs: AcirVar, bit_size: u32, predicate: AcirVar, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { let lhs_less_than_rhs = self.more_than_eq_var(rhs, lhs, bit_size, predicate)?; self.maybe_eq_predicate(lhs_less_than_rhs, predicate) } /// Returns a Variable that is constrained to be the result of reading /// from the memory `block_id` at the given `index`. - pub(crate) fn read_from_memory(&mut self, block_id: BlockId, index: &AcirVar) -> AcirVar { + pub(crate) fn read_from_memory( + &mut self, + block_id: BlockId, + index: &AcirVar, + ) -> Result { // Fetch the witness corresponding to the index - let index_witness = self.var_to_witness(*index); + let index_witness = self.var_to_witness(*index)?; // Create a Variable to hold the result of the read and extract the corresponding Witness let value_read_var = self.add_variable(); - let value_read_witness = self.var_to_witness(value_read_var); + let value_read_witness = self.var_to_witness(value_read_var)?; // Add the memory read operation to the list of opcodes let op = MemOp::read_at_mem_index(index_witness.into(), value_read_witness); self.acir_ir.opcodes.push(Opcode::MemoryOp { block_id, op }); - value_read_var + Ok(value_read_var) } /// Constrains the Variable `value` to be the new value located at `index` in the memory `block_id`. - pub(crate) fn write_to_memory(&mut self, block_id: BlockId, index: &AcirVar, value: &AcirVar) { + pub(crate) fn write_to_memory( + &mut self, + block_id: BlockId, + index: &AcirVar, + value: &AcirVar, + ) -> Result<(), InternalError> { // Fetch the witness corresponding to the index // - let index_witness = self.var_to_witness(*index); + let index_witness = self.var_to_witness(*index)?; // Fetch the witness corresponding to the value to be written - let value_write_witness = self.var_to_witness(*value); + let value_write_witness = self.var_to_witness(*value)?; // Add the memory write operation to the list of opcodes let op = MemOp::write_to_mem_index(index_witness.into(), value_write_witness.into()); self.acir_ir.opcodes.push(Opcode::MemoryOp { block_id, op }); + Ok(()) } /// Initializes an array in memory with the given values `optional_values`. @@ -1037,22 +1084,23 @@ impl AcirContext { block_id: BlockId, len: usize, optional_values: Option<&[AcirValue]>, - ) { + ) -> Result<(), InternalError> { // If the optional values are supplied, then we fill the initialized // array with those values. If not, then we fill it with zeros. let initialized_values = match optional_values { None => { let zero = self.add_constant(FieldElement::zero()); - let zero_witness = self.var_to_witness(zero); + let zero_witness = self.var_to_witness(zero)?; vec![zero_witness; len] } - Some(optional_values) => vecmap(optional_values, |value| { - let value = value.clone().into_var(); + Some(optional_values) => try_vecmap(optional_values, |value| { + let value = value.clone().into_var()?; self.var_to_witness(value) - }), + })?, }; self.acir_ir.opcodes.push(Opcode::MemoryInit { block_id, init: initialized_values }); + Ok(()) } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs deleted file mode 100644 index c90f98e15be..00000000000 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs +++ /dev/null @@ -1,62 +0,0 @@ -use acvm::FieldElement; -use noirc_errors::Location; - -use crate::errors::{RuntimeError, RuntimeErrorKind}; - -#[derive(Debug, PartialEq, Eq, Clone)] -pub(crate) enum AcirGenError { - InvalidRangeConstraint { num_bits: u32, location: Option }, - IndexOutOfBounds { index: usize, array_size: usize, location: Option }, - UnsupportedIntegerSize { num_bits: u32, max_num_bits: u32, location: Option }, - BadConstantEquality { lhs: FieldElement, rhs: FieldElement, location: Option }, -} - -impl AcirGenError { - pub(crate) fn message(&self) -> String { - match self { - AcirGenError::InvalidRangeConstraint { num_bits, .. } => { - // Don't apply any constraints if the range is for the maximum number of bits or more. - format!( - "All Witnesses are by default u{num_bits} Applying this type does not apply any constraints.\n We also currently do not allow integers of size more than {num_bits}, this will be handled by BigIntegers.") - } - AcirGenError::IndexOutOfBounds { index, array_size, .. } => { - format!("Index out of bounds, array has size {array_size}, but index was {index}") - } - AcirGenError::UnsupportedIntegerSize { num_bits, max_num_bits, .. } => { - format!("Integer sized {num_bits} is over the max supported size of {max_num_bits}") - } - AcirGenError::BadConstantEquality { lhs, rhs, .. } => { - format!("{lhs} and {rhs} constrained to be equal though they never can be") - } - } - } -} - -impl From for RuntimeError { - fn from(error: AcirGenError) -> Self { - match error { - AcirGenError::InvalidRangeConstraint { num_bits, location } => { - let kind = RuntimeErrorKind::FailedRangeConstraint(num_bits); - RuntimeError::new(kind, location) - } - AcirGenError::IndexOutOfBounds { index, array_size, location } => { - let kind = RuntimeErrorKind::ArrayOutOfBounds { - index: index as u128, - bound: array_size as u128, - }; - RuntimeError::new(kind, location) - } - AcirGenError::UnsupportedIntegerSize { num_bits, max_num_bits, location } => { - let kind = RuntimeErrorKind::UnsupportedIntegerSize { num_bits, max_num_bits }; - RuntimeError::new(kind, location) - } - AcirGenError::BadConstantEquality { lhs: _, rhs: _, location } => { - // We avoid showing the actual lhs and rhs since most of the time they are just 0 - // and 1 respectively. This would confuse users if a constraint such as - // assert(foo < bar) fails with "failed constraint: 0 = 1." - let kind = RuntimeErrorKind::FailedConstraint; - RuntimeError::new(kind, location) - } - } - } -} diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index 459458fc03e..24f001b74db 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -2,9 +2,11 @@ //! program as it is being converted from SSA form. use std::collections::HashMap; -use crate::brillig::brillig_gen::brillig_directive; +use crate::{ + brillig::brillig_gen::brillig_directive, + errors::{InternalError, RuntimeError}, +}; -use super::errors::AcirGenError; use acvm::acir::{ brillig::Opcode as BrilligOpcode, circuit::{ @@ -122,10 +124,10 @@ impl GeneratedAcir { func_name: BlackBoxFunc, mut inputs: Vec, constants: Vec, - ) -> Vec { - intrinsics_check_inputs(func_name, &inputs); + ) -> Result, InternalError> { + intrinsics_check_inputs(func_name, &inputs)?; - let output_count = black_box_expected_output_size(func_name); + let output_count = black_box_expected_output_size(func_name)?; let outputs = vecmap(0..output_count, |_| self.next_witness_index()); // clone is needed since outputs is moved when used in blackbox function. @@ -182,18 +184,30 @@ impl GeneratedAcir { outputs: (outputs[0], outputs[1]), }, BlackBoxFunc::Keccak256 => { - let var_message_size = inputs.pop().expect("ICE: Missing message_size arg"); + let var_message_size = match inputs.pop() { + Some(var_message_size) => var_message_size, + None => { + return Err(InternalError::MissingArg { + name: "".to_string(), + arg: "message_size".to_string(), + location: self.current_location, + }); + } + }; BlackBoxFuncCall::Keccak256VariableLength { inputs, var_message_size, outputs } } // TODO(#1570): Generate ACIR for recursive aggregation BlackBoxFunc::RecursiveAggregation => { - panic!("ICE: Cannot generate ACIR for recursive aggregation") + return Err(InternalError::NotImplemented { + name: "recursive aggregation".to_string(), + location: None, + }) } }; self.opcodes.push(AcirOpcode::BlackBoxFuncCall(black_box_func_call)); - outputs_clone + Ok(outputs_clone) } /// Takes an input expression and returns witnesses that are constrained to be limbs @@ -206,7 +220,7 @@ impl GeneratedAcir { radix: u32, limb_count: u32, bit_size: u32, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { let radix_big = BigUint::from(radix); assert_eq!( BigUint::from(2u128).pow(bit_size), @@ -320,13 +334,13 @@ impl GeneratedAcir { lhs: &Expression, rhs: &Expression, max_bit_size: u32, - ) -> Result<(Expression, Expression), AcirGenError> { + ) -> Result<(Expression, Expression), RuntimeError> { // 2^{max_bit size-1} let max_power_of_two = FieldElement::from(2_i128).pow(&FieldElement::from(max_bit_size as i128 - 1)); // Get the sign bit of rhs by computing rhs / max_power_of_two - let (rhs_leading, _) = self.euclidean_division( + let (rhs_leading_witness, _) = self.euclidean_division( rhs, &max_power_of_two.into(), max_bit_size, @@ -334,7 +348,7 @@ impl GeneratedAcir { )?; // Get the sign bit of lhs by computing lhs / max_power_of_two - let (lhs_leading, _) = self.euclidean_division( + let (lhs_leading_witness, _) = self.euclidean_division( lhs, &max_power_of_two.into(), max_bit_size, @@ -342,8 +356,8 @@ impl GeneratedAcir { )?; // Signed to unsigned: - let unsigned_lhs = self.two_complement(lhs, lhs_leading, max_bit_size); - let unsigned_rhs = self.two_complement(rhs, rhs_leading, max_bit_size); + let unsigned_lhs = self.two_complement(lhs, lhs_leading_witness, max_bit_size); + let unsigned_rhs = self.two_complement(rhs, rhs_leading_witness, max_bit_size); let unsigned_l_witness = self.get_or_create_witness(&unsigned_lhs); let unsigned_r_witness = self.get_or_create_witness(&unsigned_rhs); @@ -357,13 +371,16 @@ impl GeneratedAcir { // Unsigned to signed: derive q and r from q1,r1 and the signs of lhs and rhs // Quotient sign is lhs sign * rhs sign, whose resulting sign bit is the XOR of the sign bits - let q_sign = (&Expression::from(lhs_leading) + &Expression::from(rhs_leading)).add_mul( - -FieldElement::from(2_i128), - &(&Expression::from(lhs_leading) * &Expression::from(rhs_leading)).unwrap(), - ); + let sign_sum = + &Expression::from(lhs_leading_witness) + &Expression::from(rhs_leading_witness); + let sign_prod = (&Expression::from(lhs_leading_witness) + * &Expression::from(rhs_leading_witness)) + .expect("Product of two witnesses so result is degree 2"); + let q_sign = sign_sum.add_mul(-FieldElement::from(2_i128), &sign_prod); + let q_sign_witness = self.get_or_create_witness(&q_sign); let quotient = self.two_complement(&q1.into(), q_sign_witness, max_bit_size); - let remainder = self.two_complement(&r1.into(), lhs_leading, max_bit_size); + let remainder = self.two_complement(&r1.into(), lhs_leading_witness, max_bit_size); Ok((quotient, remainder)) } @@ -377,7 +394,7 @@ impl GeneratedAcir { rhs: &Expression, max_bit_size: u32, predicate: &Expression, - ) -> Result<(Witness, Witness), AcirGenError> { + ) -> Result<(Witness, Witness), RuntimeError> { // lhs = rhs * q + r // // If predicate is zero, `q_witness` and `r_witness` will be 0 @@ -435,7 +452,7 @@ impl GeneratedAcir { rhs: &Expression, offset: &Expression, bits: u32, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { const fn num_bits() -> usize { std::mem::size_of::() * 8 } @@ -635,11 +652,11 @@ impl GeneratedAcir { &mut self, witness: Witness, num_bits: u32, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { // We class this as an error because users should instead // do `as Field`. if num_bits >= FieldElement::max_num_bits() { - return Err(AcirGenError::InvalidRangeConstraint { + return Err(RuntimeError::InvalidRangeConstraint { num_bits: FieldElement::max_num_bits(), location: self.current_location, }); @@ -663,7 +680,7 @@ impl GeneratedAcir { predicate: Option, q_max_bits: u32, r_max_bits: u32, - ) -> Result<(Witness, Witness), AcirGenError> { + ) -> Result<(Witness, Witness), RuntimeError> { let q_witness = self.next_witness_index(); let r_witness = self.next_witness_index(); @@ -691,7 +708,7 @@ impl GeneratedAcir { b: &Expression, max_bits: u32, predicate: Expression, - ) -> Result { + ) -> Result { // Ensure that 2^{max_bits + 1} is less than the field size // // TODO: perhaps this should be a user error, instead of an assert @@ -760,7 +777,11 @@ impl GeneratedAcir { /// /// n.b. A sorting network is a predetermined set of switches, /// the control bits indicate the configuration of each switch: false for pass-through and true for cross-over - pub(crate) fn permutation(&mut self, in_expr: &[Expression], out_expr: &[Expression]) { + pub(crate) fn permutation( + &mut self, + in_expr: &[Expression], + out_expr: &[Expression], + ) -> Result<(), RuntimeError> { let mut bits_len = 0; for i in 0..in_expr.len() { bits_len += ((i + 1) as f32).log2().ceil() as u32; @@ -774,77 +795,80 @@ impl GeneratedAcir { bits: bits.clone(), sort_by: vec![0], })); - let (_, b) = self.permutation_layer(in_expr, &bits, false); + let (_, b) = self.permutation_layer(in_expr, &bits, false)?; // Constrain the network output to out_expr for (b, o) in b.iter().zip(out_expr) { self.push_opcode(AcirOpcode::Arithmetic(b - o)); } + Ok(()) } } /// This function will return the number of inputs that a blackbox function /// expects. Returning `None` if there is no expectation. -fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Option { +fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Result, InternalError> { match name { // Bitwise opcodes will take in 2 parameters - BlackBoxFunc::AND | BlackBoxFunc::XOR => Some(2), + BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(Some(2)), // All of the hash/cipher methods will take in a // variable number of inputs. BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s | BlackBoxFunc::Pedersen - | BlackBoxFunc::HashToField128Security => None, + | BlackBoxFunc::HashToField128Security => Ok(None), // Can only apply a range constraint to one // witness at a time. - BlackBoxFunc::RANGE => Some(1), + BlackBoxFunc::RANGE => Ok(Some(1)), // Signature verification algorithms will take in a variable // number of inputs, since the message/hashed-message can vary in size. BlackBoxFunc::SchnorrVerify | BlackBoxFunc::EcdsaSecp256k1 - | BlackBoxFunc::EcdsaSecp256r1 => None, + | BlackBoxFunc::EcdsaSecp256r1 => Ok(None), // Inputs for fixed based scalar multiplication // is just a scalar - BlackBoxFunc::FixedBaseScalarMul => Some(1), + BlackBoxFunc::FixedBaseScalarMul => Ok(Some(1)), // TODO(#1570): Generate ACIR for recursive aggregation // RecursiveAggregation has variable inputs and we could return `None` here, - // but as it is not fully implemented we panic for now - BlackBoxFunc::RecursiveAggregation => { - panic!("ICE: Cannot generate ACIR for recursive aggregation") - } + // but as it is not fully implemented we return an ICE error for now + BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented { + name: "recursive aggregation".to_string(), + location: None, + }), } } /// This function will return the number of outputs that a blackbox function /// expects. Returning `None` if there is no expectation. -fn black_box_expected_output_size(name: BlackBoxFunc) -> u32 { +fn black_box_expected_output_size(name: BlackBoxFunc) -> Result { match name { // Bitwise opcodes will return 1 parameter which is the output // or the operation. - BlackBoxFunc::AND | BlackBoxFunc::XOR => 1, + BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(1), // 32 byte hash algorithms - BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => 32, + BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => Ok(32), // Hash to field returns a field element - BlackBoxFunc::HashToField128Security => 1, + BlackBoxFunc::HashToField128Security => Ok(1), // Pedersen returns a point - BlackBoxFunc::Pedersen => 2, + BlackBoxFunc::Pedersen => Ok(2), // Can only apply a range constraint to one // witness at a time. - BlackBoxFunc::RANGE => 0, + BlackBoxFunc::RANGE => Ok(0), // Signature verification algorithms will return a boolean BlackBoxFunc::SchnorrVerify | BlackBoxFunc::EcdsaSecp256k1 - | BlackBoxFunc::EcdsaSecp256r1 => 1, + | BlackBoxFunc::EcdsaSecp256r1 => Ok(1), // Output of fixed based scalar mul over the embedded curve // will be 2 field elements representing the point. - BlackBoxFunc::FixedBaseScalarMul => 2, + BlackBoxFunc::FixedBaseScalarMul => Ok(2), // TODO(#1570): Generate ACIR for recursive aggregation - BlackBoxFunc::RecursiveAggregation => { - panic!("ICE: Cannot generate ACIR for recursive aggregation") - } + BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented { + name: "recursive aggregation".to_string(), + location: None, + }), } } @@ -863,12 +887,16 @@ fn black_box_expected_output_size(name: BlackBoxFunc) -> u32 { /// #[foreign(sha256)] /// fn sha256(_input : [u8; N]) -> [u8; 32] {} /// `` -fn intrinsics_check_inputs(name: BlackBoxFunc, inputs: &[FunctionInput]) { - let expected_num_inputs = match black_box_func_expected_input_size(name) { +fn intrinsics_check_inputs( + name: BlackBoxFunc, + inputs: &[FunctionInput], +) -> Result<(), InternalError> { + let expected_num_inputs = match black_box_func_expected_input_size(name)? { Some(expected_num_inputs) => expected_num_inputs, - None => return, + None => return Ok(()), }; let got_num_inputs = inputs.len(); assert_eq!(expected_num_inputs,inputs.len(),"Tried to call black box function {name} with {got_num_inputs} inputs, but this function's definition requires {expected_num_inputs} inputs"); + Ok(()) } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs index 622bf24ba65..42a6a5f1a4a 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs @@ -1,3 +1,5 @@ +use crate::errors::InternalError; + use super::generated_acir::GeneratedAcir; use acvm::acir::native_types::{Expression, Witness}; @@ -13,10 +15,10 @@ impl GeneratedAcir { in_expr: &[Expression], bits: &[Witness], generate_witness: bool, - ) -> (Vec, Vec) { + ) -> Result<(Vec, Vec), InternalError> { let n = in_expr.len(); if n == 1 { - return (Vec::new(), in_expr.to_vec()); + return Ok((Vec::new(), in_expr.to_vec())); } let n1 = n / 2; @@ -46,14 +48,17 @@ impl GeneratedAcir { in_sub2.push(&in_expr[2 * i + 1] - &intermediate); } if n % 2 == 1 { - in_sub2.push(in_expr.last().unwrap().clone()); + in_sub2.push(match in_expr.last() { + Some(in_expr) => in_expr.clone(), + None => return Err(InternalError::EmptyArray { location: self.current_location }), + }); } let mut out_expr = Vec::new(); // compute results for the sub networks let bits1 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2..] }; - let (w1, b1) = self.permutation_layer(&in_sub1, bits1, generate_witness); + let (w1, b1) = self.permutation_layer(&in_sub1, bits1, generate_witness)?; let bits2 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2 + w1.len()..] }; - let (w2, b2) = self.permutation_layer(&in_sub2, bits2, generate_witness); + let (w2, b2) = self.permutation_layer(&in_sub2, bits2, generate_witness)?; // apply the output switches for i in 0..(n - 1) / 2 { let c = if generate_witness { self.next_witness_index() } else { bits[n1 + i] }; @@ -63,11 +68,17 @@ impl GeneratedAcir { out_expr.push(&b2[i] - &intermediate); } if n % 2 == 0 { - out_expr.push(b1.last().unwrap().clone()); + out_expr.push(match b1.last() { + Some(b1) => b1.clone(), + None => return Err(InternalError::EmptyArray { location: self.current_location }), + }); } - out_expr.push(b2.last().unwrap().clone()); + out_expr.push(match b2.last() { + Some(b2) => b2.clone(), + None => return Err(InternalError::EmptyArray { location: self.current_location }), + }); conf.extend(w1); conf.extend(w2); - (conf, out_expr) + Ok((conf, out_expr)) } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index ad10bed96f9..1fce4cd76ad 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -1,19 +1,11 @@ //! This file holds the pass to convert from Noir's SSA IR to ACIR. +mod acir_ir; use std::collections::{HashMap, HashSet}; use std::fmt::Debug; use std::ops::RangeInclusive; -use crate::brillig::brillig_ir::BrilligContext; -use crate::{ - brillig::{brillig_gen::brillig_fn::FunctionContext as BrilligFunctionContext, Brillig}, - errors::RuntimeError, -}; - -use self::acir_ir::{ - acir_variable::{AcirContext, AcirType, AcirVar}, - errors::AcirGenError, -}; +use self::acir_ir::acir_variable::{AcirContext, AcirType, AcirVar}; use super::{ ir::{ dfg::DataFlowGraph, @@ -27,17 +19,17 @@ use super::{ }, ssa_gen::Ssa, }; +use crate::brillig::brillig_ir::BrilligContext; +use crate::brillig::{brillig_gen::brillig_fn::FunctionContext as BrilligFunctionContext, Brillig}; +use crate::errors::{InternalError, RuntimeError}; +pub(crate) use acir_ir::generated_acir::GeneratedAcir; use acvm::{ acir::{brillig::Opcode, circuit::opcodes::BlockId, native_types::Expression}, FieldElement, }; use iter_extended::{try_vecmap, vecmap}; - -pub(crate) use acir_ir::generated_acir::GeneratedAcir; use noirc_abi::AbiDistinctness; -mod acir_ir; - /// Context struct for the acir generation pass. /// May be similar to the Evaluator struct in the current SSA IR. struct Context { @@ -87,12 +79,13 @@ pub(crate) enum AcirValue { } impl AcirValue { - fn into_var(self) -> AcirVar { + fn into_var(self) -> Result { match self { - AcirValue::Var(var, _) => var, - AcirValue::DynamicArray(_) | AcirValue::Array(_) => { - panic!("Called AcirValue::into_var on an array") - } + AcirValue::Var(var, _) => Ok(var), + AcirValue::DynamicArray(_) | AcirValue::Array(_) => Err(InternalError::General { + message: "Called AcirValue::into_var on an array".to_string(), + location: None, + }), } } @@ -156,7 +149,7 @@ impl Context { ssa: Ssa, brillig: Brillig, allow_log_ops: bool, - ) -> Result { + ) -> Result { let main_func = ssa.main(); match main_func.runtime() { RuntimeType::Acir => self.convert_acir_main(main_func, &ssa, brillig, allow_log_ops), @@ -170,7 +163,7 @@ impl Context { ssa: &Ssa, brillig: Brillig, allow_log_ops: bool, - ) -> Result { + ) -> Result { let dfg = &main_func.dfg; let entry_block = &dfg[main_func.entry_block()]; let input_witness = self.convert_ssa_block_params(entry_block.parameters(), dfg)?; @@ -179,7 +172,7 @@ impl Context { self.convert_ssa_instruction(*instruction_id, dfg, ssa, &brillig, allow_log_ops)?; } - self.convert_ssa_return(entry_block.unwrap_terminator(), dfg); + self.convert_ssa_return(entry_block.unwrap_terminator(), dfg)?; Ok(self.acir_context.finish(input_witness.collect())) } @@ -188,7 +181,7 @@ impl Context { mut self, main_func: &Function, brillig: Brillig, - ) -> Result { + ) -> Result { let dfg = &main_func.dfg; let inputs = try_vecmap(dfg[main_func.entry_block()].parameters(), |param_id| { @@ -200,10 +193,14 @@ impl Context { let outputs: Vec = vecmap(main_func.returns(), |result_id| dfg.type_of_value(*result_id).into()); - let code = self.gen_brillig_for(main_func, &brillig); + let code = self.gen_brillig_for(main_func, &brillig)?; - let output_values = - self.acir_context.brillig(self.current_side_effects_enabled_var, code, inputs, outputs); + let output_values = self.acir_context.brillig( + self.current_side_effects_enabled_var, + code, + inputs, + outputs, + )?; let output_vars: Vec<_> = output_values .iter() .flat_map(|value| value.clone().flatten()) @@ -211,7 +208,7 @@ impl Context { .collect(); for acir_var in output_vars { - self.acir_context.return_var(acir_var); + self.acir_context.return_var(acir_var)?; } Ok(self.acir_context.finish(witness_inputs)) @@ -222,7 +219,7 @@ impl Context { &mut self, params: &[ValueId], dfg: &DataFlowGraph, - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { // The first witness (if any) is the next one let start_witness = self.acir_context.current_witness_index().0 + 1; for param_id in params { @@ -233,7 +230,7 @@ impl Context { AcirValue::Array(values) => { let block_id = BlockId(param_id.to_usize() as u32); let v = vecmap(values, |v| v.clone()); - self.initialize_array(block_id, values.len(), Some(&v)); + self.initialize_array(block_id, values.len(), Some(&v))?; } AcirValue::DynamicArray(_) => unreachable!( "The dynamic array type is created in Acir gen and therefore cannot be a block parameter" @@ -245,15 +242,15 @@ impl Context { Ok(start_witness..=end_witness) } - fn convert_ssa_block_param(&mut self, param_type: &Type) -> Result { + fn convert_ssa_block_param(&mut self, param_type: &Type) -> Result { self.create_value_from_type(param_type, &mut |this, typ| this.add_numeric_input_var(&typ)) } fn create_value_from_type( &mut self, param_type: &Type, - make_var: &mut impl FnMut(&mut Self, NumericType) -> Result, - ) -> Result { + make_var: &mut impl FnMut(&mut Self, NumericType) -> Result, + ) -> Result { match param_type { Type::Numeric(numeric_type) => { let typ = AcirType::new(*numeric_type); @@ -282,7 +279,7 @@ impl Context { fn add_numeric_input_var( &mut self, numeric_type: &NumericType, - ) -> Result { + ) -> Result { let acir_var = self.acir_context.add_variable(); if matches!(numeric_type, NumericType::Signed { .. } | NumericType::Unsigned { .. }) { self.acir_context.range_constrain_var(acir_var, numeric_type)?; @@ -298,7 +295,7 @@ impl Context { ssa: &Ssa, brillig: &Brillig, allow_log_ops: bool, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { let instruction = &dfg[instruction_id]; self.acir_context.set_location(dfg.get_location(&instruction_id)); match instruction { @@ -307,7 +304,7 @@ impl Context { self.define_result_var(dfg, instruction_id, result_acir_var); } Instruction::Constrain(value_id) => { - let constrain_condition = self.convert_numeric_value(*value_id, dfg); + let constrain_condition = self.convert_numeric_value(*value_id, dfg)?; self.acir_context.assert_eq_one(constrain_condition)?; } Instruction::Cast(value_id, typ) => { @@ -326,11 +323,11 @@ impl Context { RuntimeType::Brillig => { let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg)); - let code = self.gen_brillig_for(func, brillig); + let code = self.gen_brillig_for(func, brillig)?; let outputs: Vec = vecmap(result_ids, |result_id| dfg.type_of_value(*result_id).into()); - let output_values = self.acir_context.brillig(self.current_side_effects_enabled_var, code, inputs, outputs); + let output_values = self.acir_context.brillig(self.current_side_effects_enabled_var, code, inputs, outputs)?; // Compiler sanity check assert_eq!(result_ids.len(), output_values.len(), "ICE: The number of Brillig output values should match the result ids in SSA"); @@ -378,7 +375,7 @@ impl Context { self.define_result_var(dfg, instruction_id, result_acir_var); } Instruction::EnableSideEffects { condition } => { - let acir_var = self.convert_numeric_value(*condition, dfg); + let acir_var = self.convert_numeric_value(*condition, dfg)?; self.current_side_effects_enabled_var = acir_var; } Instruction::ArrayGet { array, index } => { @@ -401,7 +398,11 @@ impl Context { Ok(()) } - fn gen_brillig_for(&self, func: &Function, brillig: &Brillig) -> Vec { + fn gen_brillig_for( + &self, + func: &Function, + brillig: &Brillig, + ) -> Result, InternalError> { // Create the entry point artifact let mut entry_point = BrilligContext::new_entry_point_artifact( BrilligFunctionContext::parameters(func), @@ -410,13 +411,20 @@ impl Context { ); // Link the entry point with all dependencies while let Some(unresolved_fn_label) = entry_point.first_unresolved_function_call() { - let artifact = &brillig - .find_by_function_label(unresolved_fn_label.clone()) - .unwrap_or_else(|| panic!("Cannot find linked fn {unresolved_fn_label}")); + let artifact = &brillig.find_by_function_label(unresolved_fn_label.clone()); + let artifact = match artifact { + Some(artifact) => artifact, + None => { + return Err(InternalError::General { + message: format!("Cannot find linked fn {unresolved_fn_label}"), + location: None, + }) + } + }; entry_point.link_with(artifact); } // Generate the final bytecode - entry_point.finish() + Ok(entry_point.finish()) } /// Handles an ArrayGet or ArraySet instruction. @@ -429,23 +437,37 @@ impl Context { index: ValueId, store_value: Option, dfg: &DataFlowGraph, - ) -> Result<(), AcirGenError> { + ) -> Result<(), RuntimeError> { let index_const = dfg.get_numeric_constant(index); match self.convert_value(array, dfg) { - AcirValue::Var(acir_var, _) => panic!("Expected an array value, found: {acir_var:?}"), + AcirValue::Var(acir_var, _) => { + return Err(RuntimeError::InternalError(InternalError::UnExpected { + expected: "an array value".to_string(), + found: format!("{acir_var:?}"), + location: self.acir_context.get_location(), + })) + } AcirValue::Array(array) => { if let Some(index_const) = index_const { let array_size = array.len(); - let index = - index_const.try_to_u64().expect("Expected array index to fit into a u64") - as usize; + let index = match index_const.try_to_u64() { + Some(index_const) => index_const as usize, + None => { + let location = self.acir_context.get_location(); + return Err(RuntimeError::TypeConversion { + from: "array index".to_string(), + into: "u64".to_string(), + location, + }); + } + }; if index >= array_size { // Ignore the error if side effects are disabled. if self.acir_context.is_constant_one(&self.current_side_effects_enabled_var) { let location = self.acir_context.get_location(); - return Err(AcirGenError::IndexOutOfBounds { + return Err(RuntimeError::IndexOutOfBounds { index, array_size, location, @@ -474,9 +496,9 @@ impl Context { } if let Some(store) = store_value { - self.array_set(instruction, array, index, store, dfg); + self.array_set(instruction, array, index, store, dfg)?; } else { - self.array_get(instruction, array, index, dfg); + self.array_get(instruction, array, index, dfg)?; } Ok(()) @@ -489,7 +511,7 @@ impl Context { array: ValueId, index: ValueId, dfg: &DataFlowGraph, - ) { + ) -> Result<(), RuntimeError> { let array = dfg.resolve(array); let block_id = BlockId(array.to_usize() as u32); if !self.initialized_arrays.contains(&block_id) { @@ -497,14 +519,19 @@ impl Context { Value::Array { array, .. } => { let values: Vec = array.iter().map(|i| self.convert_value(*i, dfg)).collect(); - self.initialize_array(block_id, array.len(), Some(&values)); + self.initialize_array(block_id, array.len(), Some(&values))?; + } + _ => { + return Err(RuntimeError::UnInitialized { + name: "array".to_string(), + location: self.acir_context.get_location(), + }) } - _ => panic!("reading uninitialized array"), } } - let index_var = self.convert_value(index, dfg).into_var(); - let read = self.acir_context.read_from_memory(block_id, &index_var); + let index_var = self.convert_value(index, dfg).into_var()?; + let read = self.acir_context.read_from_memory(block_id, &index_var)?; let typ = match dfg.type_of_value(array) { Type::Array(typ, _) => { if typ.len() != 1 { @@ -518,6 +545,7 @@ impl Context { }; let typ = AcirType::from(typ); self.define_result(dfg, instruction, AcirValue::Var(read, typ)); + Ok(()) } /// Copy the array and generates a write opcode on the new array @@ -530,7 +558,7 @@ impl Context { index: ValueId, store_value: ValueId, dfg: &DataFlowGraph, - ) { + ) -> Result<(), InternalError> { // Fetch the internal SSA ID for the array let array = dfg.resolve(array); let array_ssa_id = array.to_usize() as u32; @@ -554,9 +582,14 @@ impl Context { Value::Array { array, .. } => { let values: Vec = array.iter().map(|i| self.convert_value(*i, dfg)).collect(); - self.initialize_array(block_id, array.len(), Some(&values)); + self.initialize_array(block_id, array.len(), Some(&values))?; + } + _ => { + return Err(InternalError::General { + message: format!("Array {array} should be initialized"), + location: self.acir_context.get_location(), + }) } - _ => panic!("Array {} should be initialized", array), } } @@ -570,7 +603,7 @@ impl Context { let result_block_id = BlockId(result_array_id); // Initialize the new array with zero values - self.initialize_array(result_block_id, len, None); + self.initialize_array(result_block_id, len, None)?; // Copy the values from the old array into the newly created zeroed array for i in 0..len { @@ -578,26 +611,33 @@ impl Context { self.acir_context.add_constant(FieldElement::from(i as u128)), AcirType::NumericType(NumericType::NativeField), ); - let var = index.into_var(); - let read = self.acir_context.read_from_memory(block_id, &var); - self.acir_context.write_to_memory(result_block_id, &var, &read); + let var = index.into_var()?; + let read = self.acir_context.read_from_memory(block_id, &var)?; + self.acir_context.write_to_memory(result_block_id, &var, &read)?; } // Write the new value into the new array at the specified index - let index_var = self.convert_value(index, dfg).into_var(); - let value_var = self.convert_value(store_value, dfg).into_var(); - self.acir_context.write_to_memory(result_block_id, &index_var, &value_var); + let index_var = self.convert_value(index, dfg).into_var()?; + let value_var = self.convert_value(store_value, dfg).into_var()?; + self.acir_context.write_to_memory(result_block_id, &index_var, &value_var)?; let result_value = AcirValue::DynamicArray(AcirDynamicArray { block_id: result_block_id, len }); self.define_result(dfg, instruction, result_value); + Ok(()) } /// Initializes an array with the given values and caches the fact that we /// have initialized this array. - fn initialize_array(&mut self, array: BlockId, len: usize, values: Option<&[AcirValue]>) { - self.acir_context.initialize_array(array, len, values); + fn initialize_array( + &mut self, + array: BlockId, + len: usize, + values: Option<&[AcirValue]>, + ) -> Result<(), InternalError> { + self.acir_context.initialize_array(array, len, values)?; self.initialized_arrays.insert(array); + Ok(()) } /// Remember the result of an instruction returning a single value @@ -624,7 +664,11 @@ impl Context { } /// Converts an SSA terminator's return values into their ACIR representations - fn convert_ssa_return(&mut self, terminator: &TerminatorInstruction, dfg: &DataFlowGraph) { + fn convert_ssa_return( + &mut self, + terminator: &TerminatorInstruction, + dfg: &DataFlowGraph, + ) -> Result<(), InternalError> { let return_values = match terminator { TerminatorInstruction::Return { return_values } => return_values, _ => unreachable!("ICE: Program must have a singular return"), @@ -634,8 +678,9 @@ impl Context { // will expand the array if there is one. let return_acir_vars = self.flatten_value_list(return_values, dfg); for acir_var in return_acir_vars { - self.acir_context.return_var(acir_var); + self.acir_context.return_var(acir_var)?; } + Ok(()) } /// Gets the cached `AcirVar` that was converted from the corresponding `ValueId`. If it does @@ -679,11 +724,25 @@ impl Context { acir_value } - fn convert_numeric_value(&mut self, value_id: ValueId, dfg: &DataFlowGraph) -> AcirVar { + fn convert_numeric_value( + &mut self, + value_id: ValueId, + dfg: &DataFlowGraph, + ) -> Result { match self.convert_value(value_id, dfg) { - AcirValue::Var(acir_var, _) => acir_var, - AcirValue::Array(array) => panic!("Expected a numeric value, found: {array:?}"), - AcirValue::DynamicArray(_) => panic!("Expected a numeric value, found an array"), + AcirValue::Var(acir_var, _) => Ok(acir_var), + AcirValue::Array(array) => { + return Err(InternalError::UnExpected { + expected: "a numeric value".to_string(), + found: format!("{array:?}"), + location: self.acir_context.get_location(), + }) + } + AcirValue::DynamicArray(_) => Err(InternalError::UnExpected { + expected: "a numeric value".to_string(), + found: "an array".to_string(), + location: self.acir_context.get_location(), + }), } } @@ -692,9 +751,9 @@ impl Context { &mut self, binary: &Binary, dfg: &DataFlowGraph, - ) -> Result { - let lhs = self.convert_numeric_value(binary.lhs, dfg); - let rhs = self.convert_numeric_value(binary.rhs, dfg); + ) -> Result { + let lhs = self.convert_numeric_value(binary.lhs, dfg)?; + let rhs = self.convert_numeric_value(binary.rhs, dfg)?; let binary_type = self.type_of_binary_operation(binary, dfg); match &binary_type { @@ -705,7 +764,7 @@ impl Context { // truncation technique: result % 2^bit_size to be valid. let max_integer_bit_size = FieldElement::max_num_bits() / 2; if *bit_size > max_integer_bit_size { - return Err(AcirGenError::UnsupportedIntegerSize { + return Err(RuntimeError::UnsupportedIntegerSize { num_bits: *bit_size, max_num_bits: max_integer_bit_size, location: self.acir_context.get_location(), @@ -813,7 +872,7 @@ impl Context { value_id: &ValueId, typ: &Type, dfg: &DataFlowGraph, - ) -> Result { + ) -> Result { let (variable, incoming_type) = match self.convert_value(*value_id, dfg) { AcirValue::Var(variable, typ) => (variable, typ), AcirValue::DynamicArray(_) | AcirValue::Array(_) => { @@ -851,8 +910,8 @@ impl Context { bit_size: u32, max_bit_size: u32, dfg: &DataFlowGraph, - ) -> Result { - let mut var = self.convert_numeric_value(value_id, dfg); + ) -> Result { + let mut var = self.convert_numeric_value(value_id, dfg)?; let truncation_target = match &dfg[value_id] { Value::Instruction { instruction, .. } => &dfg[*instruction], _ => unreachable!("ICE: Truncates are only ever applied to the result of a binary op"), @@ -879,7 +938,7 @@ impl Context { dfg: &DataFlowGraph, allow_log_ops: bool, result_ids: &[ValueId], - ) -> Result, AcirGenError> { + ) -> Result, RuntimeError> { match intrinsic { Intrinsic::BlackBox(black_box) => { let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg)); @@ -889,16 +948,16 @@ impl Context { Ok(Self::convert_vars_to_values(vars, dfg, result_ids)) } Intrinsic::ToRadix(endian) => { - let field = self.convert_value(arguments[0], dfg).into_var(); - let radix = self.convert_value(arguments[1], dfg).into_var(); - let limb_size = self.convert_value(arguments[2], dfg).into_var(); + let field = self.convert_value(arguments[0], dfg).into_var()?; + let radix = self.convert_value(arguments[1], dfg).into_var()?; + let limb_size = self.convert_value(arguments[2], dfg).into_var()?; let result_type = Self::array_element_type(dfg, result_ids[0]); self.acir_context.radix_decompose(endian, field, radix, limb_size, result_type) } Intrinsic::ToBits(endian) => { - let field = self.convert_value(arguments[0], dfg).into_var(); - let bit_size = self.convert_value(arguments[1], dfg).into_var(); + let field = self.convert_value(arguments[0], dfg).into_var()?; + let bit_size = self.convert_value(arguments[1], dfg).into_var()?; let result_type = Self::array_element_type(dfg, result_ids[0]); self.acir_context.bit_decompose(endian, field, bit_size, result_type) @@ -1020,7 +1079,7 @@ impl Context { } /// Creates a default, meaningless value meant only to be a valid value of the given type. - fn create_default_value(&mut self, param_type: &Type) -> Result { + fn create_default_value(&mut self, param_type: &Type) -> Result { self.create_value_from_type(param_type, &mut |this, _| { Ok(this.acir_context.add_constant(FieldElement::zero())) }) From 9e2cf6f25f775d927b67c12aba1698c5635242e3 Mon Sep 17 00:00:00 2001 From: kek kek kek Date: Tue, 1 Aug 2023 01:57:31 -0700 Subject: [PATCH 09/50] feat: Add `deprecated` attribute (#2041) * impl deprecated attribute * add note * add tests * simplify * use secondary_message --- crates/noirc_frontend/src/ast/function.rs | 2 +- .../src/hir/type_check/errors.rs | 8 +++ .../noirc_frontend/src/hir/type_check/expr.rs | 23 ++++++- crates/noirc_frontend/src/lexer/lexer.rs | 23 +++++-- crates/noirc_frontend/src/lexer/token.rs | 65 +++++++++++++------ 5 files changed, 96 insertions(+), 25 deletions(-) diff --git a/crates/noirc_frontend/src/ast/function.rs b/crates/noirc_frontend/src/ast/function.rs index de4e4f6f4d2..02af960f7a8 100644 --- a/crates/noirc_frontend/src/ast/function.rs +++ b/crates/noirc_frontend/src/ast/function.rs @@ -82,7 +82,7 @@ impl From for NoirFunction { Some(Attribute::Foreign(_)) => FunctionKind::LowLevel, Some(Attribute::Test) => FunctionKind::Normal, Some(Attribute::Oracle(_)) => FunctionKind::Oracle, - None => FunctionKind::Normal, + Some(Attribute::Deprecated(_)) | None => FunctionKind::Normal, }; NoirFunction { def: fd, kind } diff --git a/crates/noirc_frontend/src/hir/type_check/errors.rs b/crates/noirc_frontend/src/hir/type_check/errors.rs index 3c7e34b5699..4f032503f3d 100644 --- a/crates/noirc_frontend/src/hir/type_check/errors.rs +++ b/crates/noirc_frontend/src/hir/type_check/errors.rs @@ -94,6 +94,8 @@ pub enum TypeCheckError { }, #[error("Cannot infer type of expression, type annotations needed before this point")] TypeAnnotationsNeeded { span: Span }, + #[error("use of deprecated function {name}")] + CallDeprecated { name: String, note: Option, span: Span }, #[error("{0}")] ResolverError(ResolverError), } @@ -205,6 +207,12 @@ impl From for Diagnostic { Diagnostic::simple_error(message, String::new(), span) } + TypeCheckError::CallDeprecated { span, ref note, .. } => { + let primary_message = error.to_string(); + let secondary_message = note.clone().unwrap_or_default(); + + Diagnostic::simple_warning(primary_message, secondary_message, span) + } } } } diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index 8c396ea6814..b19833fb311 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -10,13 +10,32 @@ use crate::{ }, types::Type, }, - node_interner::{ExprId, FuncId}, + node_interner::{DefinitionKind, ExprId, FuncId}, + token::Attribute::Deprecated, CompTime, Shared, TypeBinding, TypeVariableKind, UnaryOp, }; use super::{errors::TypeCheckError, TypeChecker}; impl<'interner> TypeChecker<'interner> { + fn check_if_deprecated(&mut self, expr: &ExprId) { + if let HirExpression::Ident(expr::HirIdent { location, id }) = + self.interner.expression(expr) + { + if let Some(DefinitionKind::Function(func_id)) = + self.interner.try_definition(id).map(|def| &def.kind) + { + let meta = self.interner.function_meta(func_id); + if let Some(Deprecated(note)) = meta.attributes { + self.errors.push(TypeCheckError::CallDeprecated { + name: self.interner.definition_name(id).to_string(), + note, + span: location.span, + }); + } + } + } + } /// Infers a type for a given expression, and return this type. /// As a side-effect, this function will also remember this type in the NodeInterner /// for the given expr_id key. @@ -112,6 +131,8 @@ impl<'interner> TypeChecker<'interner> { } HirExpression::Index(index_expr) => self.check_index_expression(index_expr), HirExpression::Call(call_expr) => { + self.check_if_deprecated(&call_expr.func); + let function = self.check_expression(&call_expr.func); let args = vecmap(&call_expr.arguments, |arg| { let typ = self.check_expression(arg); diff --git a/crates/noirc_frontend/src/lexer/lexer.rs b/crates/noirc_frontend/src/lexer/lexer.rs index 30866be52ce..e376d85ddf0 100644 --- a/crates/noirc_frontend/src/lexer/lexer.rs +++ b/crates/noirc_frontend/src/lexer/lexer.rs @@ -244,10 +244,7 @@ impl<'a> Lexer<'a> { } self.next_char(); - let (word, start, end) = self.eat_while(None, |ch| { - (ch.is_ascii_alphabetic() || ch.is_numeric() || ch == '_' || ch == '(' || ch == ')') - && (ch != ']') - }); + let (word, start, end) = self.eat_while(None, |ch| ch != ']'); if !self.peek_char_is(']') { return Err(LexerErrorKind::UnexpectedCharacter { @@ -427,6 +424,24 @@ fn invalid_attribute() { assert!(token.is_err()); } +#[test] +fn deprecated_attribute() { + let input = r#"#[deprecated]"#; + let mut lexer = Lexer::new(input); + + let token = lexer.next().unwrap().unwrap(); + assert_eq!(token.token(), &Token::Attribute(Attribute::Deprecated(None))); +} + +#[test] +fn deprecated_attribute_with_note() { + let input = r#"#[deprecated("hello")]"#; + let mut lexer = Lexer::new(input); + + let token = lexer.next().unwrap().unwrap(); + assert_eq!(token.token(), &Token::Attribute(Attribute::Deprecated("hello".to_string().into()))); +} + #[test] fn test_custom_gate_syntax() { let input = "#[foreign(sha256)]#[foreign(blake2s)]#[builtin(sum)]"; diff --git a/crates/noirc_frontend/src/lexer/token.rs b/crates/noirc_frontend/src/lexer/token.rs index a58a9cbe249..b39d1640c57 100644 --- a/crates/noirc_frontend/src/lexer/token.rs +++ b/crates/noirc_frontend/src/lexer/token.rs @@ -322,6 +322,7 @@ pub enum Attribute { Foreign(String), Builtin(String), Oracle(String), + Deprecated(Option), Test, } @@ -332,6 +333,8 @@ impl fmt::Display for Attribute { Attribute::Builtin(ref k) => write!(f, "#[builtin({k})]"), Attribute::Oracle(ref k) => write!(f, "#[oracle({k})]"), Attribute::Test => write!(f, "#[test]"), + Attribute::Deprecated(None) => write!(f, "#[deprecated]"), + Attribute::Deprecated(Some(ref note)) => write!(f, r#"#[deprecated("{note}")]"#), } } } @@ -345,29 +348,52 @@ impl Attribute { .filter(|string_segment| !string_segment.is_empty()) .collect(); - if word_segments.len() != 2 { - if word_segments.len() == 1 && word_segments[0] == "test" { - return Ok(Token::Attribute(Attribute::Test)); - } else { - return Err(LexerErrorKind::MalformedFuncAttribute { - span, - found: word.to_owned(), - }); - } - } - - let attribute_type = word_segments[0]; - let attribute_name = word_segments[1]; + let validate = |slice: &str| { + let is_valid = slice + .chars() + .all(|ch| { + ch.is_ascii_alphabetic() + || ch.is_numeric() + || ch == '_' + || ch == '(' + || ch == ')' + }) + .then_some(()); + + is_valid.ok_or(LexerErrorKind::MalformedFuncAttribute { span, found: word.to_owned() }) + }; - let tok = match attribute_type { - "foreign" => Token::Attribute(Attribute::Foreign(attribute_name.to_string())), - "builtin" => Token::Attribute(Attribute::Builtin(attribute_name.to_string())), - "oracle" => Token::Attribute(Attribute::Oracle(attribute_name.to_string())), + let attribute = match &word_segments[..] { + ["foreign", name] => { + validate(name)?; + Attribute::Foreign(name.to_string()) + } + ["builtin", name] => { + validate(name)?; + Attribute::Builtin(name.to_string()) + } + ["oracle", name] => { + validate(name)?; + Attribute::Oracle(name.to_string()) + } + ["deprecated"] => Attribute::Deprecated(None), + ["deprecated", name] => { + if !name.starts_with('"') && !name.ends_with('"') { + return Err(LexerErrorKind::MalformedFuncAttribute { + span, + found: word.to_owned(), + }); + } + + Attribute::Deprecated(name.trim_matches('"').to_string().into()) + } + ["test"] => Attribute::Test, _ => { return Err(LexerErrorKind::MalformedFuncAttribute { span, found: word.to_owned() }) } }; - Ok(tok) + + Ok(Token::Attribute(attribute)) } pub fn builtin(self) -> Option { @@ -399,7 +425,8 @@ impl AsRef for Attribute { Attribute::Foreign(string) => string, Attribute::Builtin(string) => string, Attribute::Oracle(string) => string, - Attribute::Test => "", + Attribute::Deprecated(Some(string)) => string, + Attribute::Test | Attribute::Deprecated(None) => "", } } } From 550e627104b3e2ee181de2eb8c6dc95cc775ebfd Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Tue, 1 Aug 2023 12:57:58 +0100 Subject: [PATCH 10/50] chore: refresh ACIR test artifacts (#2091) --- .../tests/test_data/1_mul/target/main.json | 2 +- .../tests/test_data/1_mul/target/witness.tr | Bin 112 -> 114 bytes .../tests/test_data/2_div/target/main.json | 2 +- .../tests/test_data/2_div/target/witness.tr | Bin 123 -> 164 bytes .../tests/test_data/5_over/target/main.json | 2 +- .../tests/test_data/5_over/target/witness.tr | Bin 110 -> 112 bytes .../tests/test_data/6_array/target/main.json | 2 +- .../tests/test_data/6_array/target/witness.tr | Bin 2108 -> 2124 bytes .../test_data/8_integration/target/main.json | 2 +- .../test_data/8_integration/target/witness.tr | Bin 7995 -> 8074 bytes .../test_data/9_conditional/target/main.json | 2 +- .../test_data/9_conditional/target/witness.tr | Bin 31584 -> 32163 bytes .../brillig_fns_as_values/target/main.json | 2 +- .../test_data/brillig_slices/target/main.json | 2 +- .../signed_division/target/main.json | 2 +- .../signed_division/target/witness.tr | Bin 398 -> 383 bytes .../test_data/simple_bitwise/target/main.json | 2 +- .../simple_bitwise/target/witness.tr | Bin 191 -> 191 bytes 18 files changed, 10 insertions(+), 10 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/main.json b/crates/nargo_cli/tests/test_data/1_mul/target/main.json index 632c0e6b6a0..f53b31bda01 100644 --- a/crates/nargo_cli/tests/test_data/1_mul/target/main.json +++ b/crates/nargo_cli/tests/test_data/1_mul/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WYTW6DMBSEJwESGhrapNsuOIKNIZhdr1JUcv8jFFQ7UCu7zEPBEjKW4P3MvI8FHwA+8bc2w7V1ezE7b4Nz5M7+2Y17/8vt6rGlfR5w4yoE68G42t/EQ4xkpgO78JsgcWBE4s4QNCGMa9Slqvqm7LXR36psO1urqu4uVltd2/qntMb0trJN27WNanVlen2tW3N1gXeQMTTi1Fm6OnVM7Dkh+sLUTwrgxM0mmQMxgPdDjBQLADwmKjABnEIOYG8CG+AXrAPgPbHnlOgLUz8pgFM3m2QOxAA+DDEyLADwmKjABHAGOYC9CWyAX7EOgA/EnjOiL0z9pADO3GySORAD+DjEyLEAwGOiAhPAOeQA9iawAX7DOgA+EnvOib48uX63niNizzmxrneifhHuQA8+i8ya5/WeZvex27d3ZmIn0BOCPKGOoh9UKZNOAnHP4A2/VN9nvkf/Pk7PrGk0q9H/YAzXLy9W07upFAAA","proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WYTW6DMBSEJ+EvhAZVVdVuuuAIGEMwu16lqOT+RyiodiBWdpmHgiVkLMH7mXkfCz4BfOF/7cZrb/dicd5758Ce3bM7+/633cvHlnJ5wI1bwlsPxlXuJhxjRAsd2IVfBQk9IyJ7hqAJflxdnut6aKtBafVTVl1vmrJu+rNRRjWm+a2M1oOpTdv1XVt2qtaDujSdvtjAr5AxNODUWdk6VUjsOSL6wtRPCuDIziaZAzGA4zFGghUAnhIVmAFOIAewM4EN8Bu2AXBM7Dkh+sLUTwrgxM4mmQMxgA9jjBQrADwlKjADnEIOYGcCG+B3bAPgA7HnlOgLUz8pgFM7m2QOxAA+jjEyrADwlKjADHAGOYCdCWyAP7ANgI/EnjOiL0+u37XngNhzRqzrhahfgDvQg88is+ZlvafFfWj3/Z2ZiAV6gpfH1zGH4AdVyqSTQNwcvOGX6jvne3TzcXpmTYNFje4Ho7/+AAxbTEGpFAAA","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr b/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr index a539f87a55498eeaff3e546ac9126cea0091fa70..e01c75d888ce2976c0dd635f2e1bbb759ee25b29 100644 GIT binary patch literal 114 zcmV-&0FD12iwFP!00002|E-eA34kyV0KIQTf>_5c>LWi}5&Q2U2}uW;g^+y>13RXO zQ~LL&UGnCtIM!VQEVZA8zu~;3}vtNR*0Ky0}dH?_b literal 112 zcmV-$0FVD4iwFP!00002|E<$W3cw%?h2hTg=t&aVF5LAhrT4#sir&CKAZGQE2Zk? zM}9~%`e*!o&+bpdQYJV{rZ_9ifYuym@d9WqfgM-Cxz<2ygR^K0w06Lbd*ECLoRyEj zjwhgX2JY(uw64I8x1J@GWAqZ7g0EGV^iwFP!00002|E;}YRTwED#z70|23c%?KzR*PeC2Vikt9R zvp+k1#Rf{^xdOP}vnHa?k7PFgIp;pliUncm%jOdKV?p1nioD Q|1vn2oVhhsZkPiA0A^1vzW@LL diff --git a/crates/nargo_cli/tests/test_data/6_array/target/main.json b/crates/nargo_cli/tests/test_data/6_array/target/main.json index d49d0955347..3a434bc8f7a 100644 --- a/crates/nargo_cli/tests/test_data/6_array/target/main.json +++ b/crates/nargo_cli/tests/test_data/6_array/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"y","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"t","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"t":[12],"x":[1,2,3,4,5],"y":[6,7,8,9,10],"z":[11]},"return_type":null,"return_witnesses":[]},"bytecode":"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\ No newline at end of file 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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"public"}],"param_witnesses":{"a":[1],"c":[2,3,4,5],"result":[11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"x":[6,7,8,9,10]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file 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Document `GeneratedAcir::more_than_eq_comparison` (#2085) * document comparison * code review * Update crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs --------- Co-authored-by: Tom French <15848336+TomAFrench@users.noreply.github.com> --- .../acir_gen/acir_ir/generated_acir.rs | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index 24f001b74db..c368a042dc9 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -700,8 +700,20 @@ impl GeneratedAcir { /// - `1` if lhs >= rhs /// - `0` otherwise /// - /// See [R1CS Workshop - Section 10](https://github.com/mir-protocol/r1cs-workshop/blob/master/workshop.pdf) - /// for an explanation. + /// We essentially computes the sign bit of `b-a` + /// For this we sign-extend `b-a` with `c = 2^{max_bits} - (b - a)`, since both `a` and `b` are less than `2^{max_bits}` + /// Then we get the bit sign of `c`, the 2-complement representation of `(b-a)`, which is a `max_bits+1` integer, + /// by doing the euclidean division `c / 2^{max_bits}` + /// + /// To see why it really works; + /// We first note that `c` is an integer of `(max_bits+1)` bits. Therefore, + /// if `b-a>0`, then `c < 2^{max_bits}`, so the division by `2^{max_bits}` will give `0` + /// If `b-a<=0`, then `c >= 2^{max_bits}`, so the division by `2^{max_bits}` will give `1`. + /// + /// In other words, `1` means `a >= b` and `0` means `b > a`. + /// The important thing here is that `c` does not overflow nor underflow the field; + /// - By construction we have `c >= 0`, so there is no underflow + /// - We assert at the beginning that `2^{max_bits+1}` does not overflow the field, so neither c. pub(crate) fn more_than_eq_comparison( &mut self, a: &Expression, From e4185d7686087fd4278ff5f04087541271d29086 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jos=C3=A9=20Pedro=20Sousa?= Date: Tue, 1 Aug 2023 13:01:30 +0100 Subject: [PATCH 12/50] chore: Update `noir-source-resolver` to v1.1.3 (#1912) chore: updating noir-source-resolver --- crates/wasm/package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/crates/wasm/package.json b/crates/wasm/package.json index a09d0885a21..4aa881ddea6 100644 --- a/crates/wasm/package.json +++ b/crates/wasm/package.json @@ -14,7 +14,7 @@ "module": "./web/noir_wasm.js", "sideEffects": false, "peerDependencies": { - "@noir-lang/noir-source-resolver": "1.1.2" + "@noir-lang/noir-source-resolver": "1.1.3" }, "repository": { "type": "git", From a484a31267f52c6cffecfc849e72f6d6cd6686d8 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Tue, 1 Aug 2023 13:28:47 +0100 Subject: [PATCH 13/50] chore: clippy fixes (#2101) --- crates/fm/src/lib.rs | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/crates/fm/src/lib.rs b/crates/fm/src/lib.rs index 368043ea601..dc78db87684 100644 --- a/crates/fm/src/lib.rs +++ b/crates/fm/src/lib.rs @@ -149,7 +149,7 @@ mod tests { fn create_dummy_file(dir: &TempDir, file_name: &Path) { let file_path = dir.path().join(file_name); - let _file = std::fs::File::create(file_path.clone()).unwrap(); + let _file = std::fs::File::create(file_path).unwrap(); } #[test] @@ -175,7 +175,7 @@ mod tests { let mut fm = FileManager::new(dir.path()); - let file_id = fm.add_file(&file_name).unwrap(); + let file_id = fm.add_file(file_name).unwrap(); assert!(fm.path(file_id).ends_with("foo")); } @@ -189,7 +189,7 @@ mod tests { let file_name = Path::new("lib.nr"); create_dummy_file(&dir, file_name); - let file_id = fm.add_file(&file_name).unwrap(); + let file_id = fm.add_file(file_name).unwrap(); // Create a sub directory // we now have: @@ -238,7 +238,7 @@ mod tests { let second_file_name = PathBuf::from(sub_sub_dir.path()).join("./../../lib.nr"); // Add both files to the file manager - let file_id = fm.add_file(&file_name).unwrap(); + let file_id = fm.add_file(file_name).unwrap(); let second_file_id = fm.add_file(&second_file_name).unwrap(); assert_eq!(file_id, second_file_id); From ab61e3ab70aa0f7a037e0ad4a430975f50266097 Mon Sep 17 00:00:00 2001 From: jfecher Date: Tue, 1 Aug 2023 09:52:19 -0500 Subject: [PATCH 14/50] fix: Implement `.len()` in Acir-Gen (#2077) * Start experiment to merge array and slice types * Finish merger of slices and arrays * Implement missing try_bind function * Add missed case for NotConstant * Fix some tests * Fix poseidon test * Fix evaluation of slice length * Fix tests * Fix 2070 --- crates/nargo_cli/tests/test_data/array_len/Prover.toml | 1 + crates/nargo_cli/tests/test_data/array_len/src/main.nr | 7 ++++++- .../src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs | 5 +++++ crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs | 8 ++++++++ 4 files changed, 20 insertions(+), 1 deletion(-) diff --git a/crates/nargo_cli/tests/test_data/array_len/Prover.toml b/crates/nargo_cli/tests/test_data/array_len/Prover.toml index 3c3295e6848..a5ffe607b73 100644 --- a/crates/nargo_cli/tests/test_data/array_len/Prover.toml +++ b/crates/nargo_cli/tests/test_data/array_len/Prover.toml @@ -1,2 +1,3 @@ len3 = [1, 2, 3] len4 = [1, 2, 3, 4] +x = 123 diff --git a/crates/nargo_cli/tests/test_data/array_len/src/main.nr b/crates/nargo_cli/tests/test_data/array_len/src/main.nr index 2c3cc0aee60..65c2295cefb 100644 --- a/crates/nargo_cli/tests/test_data/array_len/src/main.nr +++ b/crates/nargo_cli/tests/test_data/array_len/src/main.nr @@ -12,7 +12,7 @@ fn nested_call(b: [Field; N]) -> Field { len_plus_1(b) } -fn main(len3: [u8; 3], len4: [Field; 4]) { +fn main(x: Field, len3: [u8; 3], len4: [Field; 4]) { assert(len_plus_1(len3) == 4); assert(len_plus_1(len4) == 5); assert(add_lens(len3, len4) == 7); @@ -20,4 +20,9 @@ fn main(len3: [u8; 3], len4: [Field; 4]) { // std::array::len returns a comptime value assert(len4[len3.len()] == 4); + + // Regression for #1023, ensure .len still works after calling to_le_bytes on a witness. + // This was needed because normally .len is evaluated before acir-gen where to_le_bytes + // on a witness is only evaluated during/after acir-gen. + assert(x.to_le_bytes(8).len() != 0); } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index 6d8178b6a2c..25d92ed8b85 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -55,6 +55,11 @@ impl AcirType { } } + /// Returns a field type + pub(crate) fn field() -> Self { + AcirType::NumericType(NumericType::NativeField) + } + /// Returns a boolean type fn boolean() -> Self { AcirType::NumericType(NumericType::Unsigned { bit_size: 1 }) diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index 1fce4cd76ad..da8409431ce 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -996,6 +996,14 @@ impl Context { Ok(Self::convert_vars_to_values(out_vars, dfg, result_ids)) } + Intrinsic::ArrayLen => { + let len = match self.convert_value(arguments[0], dfg) { + AcirValue::Var(_, _) => unreachable!("Non-array passed to array.len() method"), + AcirValue::Array(values) => (values.len() as u128).into(), + AcirValue::DynamicArray(array) => (array.len as u128).into(), + }; + Ok(vec![AcirValue::Var(self.acir_context.add_constant(len), AcirType::field())]) + } _ => todo!("expected a black box function"), } } From e85e4850546552b7240466031e770c2667280444 Mon Sep 17 00:00:00 2001 From: jfecher Date: Tue, 1 Aug 2023 09:54:22 -0500 Subject: [PATCH 15/50] fix: Mutating a variable no longer mutates its copy (#2057) * Fix 2054 * Rename function --- .../tests/test_data/references/src/main.nr | 10 ++++++ .../src/ssa_refactor/ssa_gen/mod.rs | 31 ++++++++++++++++--- 2 files changed, 37 insertions(+), 4 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/references/src/main.nr b/crates/nargo_cli/tests/test_data/references/src/main.nr index b112875b9ff..f70293cb5a6 100644 --- a/crates/nargo_cli/tests/test_data/references/src/main.nr +++ b/crates/nargo_cli/tests/test_data/references/src/main.nr @@ -32,6 +32,7 @@ fn main(mut x: Field) { assert(*c.bar.array == [3, 4]); regression_1887(); + regression_2054(); } fn add1(x: &mut Field) { @@ -77,3 +78,12 @@ impl Bar { self.x = 32; } } + +// Ensure that mutating a variable does not also mutate its copy +fn regression_2054() { + let mut x = 2; + let z = x; + + x += 1; + assert(z == 2); +} diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs index 710450eb1e6..d6169dfd218 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs @@ -89,8 +89,13 @@ impl<'a> FunctionContext<'a> { self.codegen_expression(expr).into_leaf().eval(self) } - /// Codegen for identifiers - fn codegen_ident(&mut self, ident: &ast::Ident) -> Values { + /// Codegen a reference to an ident. + /// The only difference between this and codegen_ident is that if the variable is mutable + /// as in `let mut var = ...;` the `Value::Mutable` will be returned directly instead of + /// being automatically loaded from. This is needed when taking the reference of a variable + /// to reassign to it. Note that mutable references `let x = &mut ...;` do not require this + /// since they are not automatically loaded from and must be explicitly dereferenced. + fn codegen_ident_reference(&mut self, ident: &ast::Ident) -> Values { match &ident.definition { ast::Definition::Local(id) => self.lookup(*id), ast::Definition::Function(id) => self.get_or_queue_function(*id), @@ -104,6 +109,11 @@ impl<'a> FunctionContext<'a> { } } + /// Codegen an identifier, automatically loading its value if it is mutable. + fn codegen_ident(&mut self, ident: &ast::Ident) -> Values { + self.codegen_ident_reference(ident).map(|value| value.eval(self).into()) + } + fn codegen_literal(&mut self, literal: &ast::Literal) -> Values { match literal { ast::Literal::Array(array) => { @@ -159,20 +169,21 @@ impl<'a> FunctionContext<'a> { } fn codegen_unary(&mut self, unary: &ast::Unary) -> Values { - let rhs = self.codegen_expression(&unary.rhs); match unary.operator { noirc_frontend::UnaryOp::Not => { + let rhs = self.codegen_expression(&unary.rhs); let rhs = rhs.into_leaf().eval(self); self.builder.insert_not(rhs).into() } noirc_frontend::UnaryOp::Minus => { + let rhs = self.codegen_expression(&unary.rhs); let rhs = rhs.into_leaf().eval(self); let typ = self.builder.type_of_value(rhs); let zero = self.builder.numeric_constant(0u128, typ); self.builder.insert_binary(zero, BinaryOp::Sub, rhs).into() } noirc_frontend::UnaryOp::MutableReference => { - rhs.map(|rhs| { + self.codegen_reference(&unary.rhs).map(|rhs| { match rhs { value::Value::Normal(value) => { let alloc = self.builder.insert_allocate(); @@ -186,11 +197,23 @@ impl<'a> FunctionContext<'a> { }) } noirc_frontend::UnaryOp::Dereference { .. } => { + let rhs = self.codegen_expression(&unary.rhs); self.dereference(&rhs, &unary.result_type) } } } + fn codegen_reference(&mut self, expr: &Expression) -> Values { + match expr { + Expression::Ident(ident) => self.codegen_ident_reference(ident), + Expression::ExtractTupleField(tuple, index) => { + let tuple = self.codegen_reference(tuple); + Self::get_field(tuple, *index) + } + other => self.codegen_expression(other), + } + } + fn codegen_binary(&mut self, binary: &ast::Binary) -> Values { let lhs = self.codegen_non_tuple_expression(&binary.lhs); let rhs = self.codegen_non_tuple_expression(&binary.rhs); From 5cb816664e03992a766ba9dcb2650e9596fbb291 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Tue, 1 Aug 2023 19:10:18 +0100 Subject: [PATCH 16/50] feat(acir_gen): RecursiveAggregation opcode and updates to black box func call generation (#2097) * update black box opcodes to accept multiple variables inputs and variable outputs, add RecursiveAggregation opcode * remove old method and comment * remove config change * remove NotImplemented InternalError --- crates/noirc_evaluator/src/errors.rs | 3 - .../acir_gen/acir_ir/acir_variable.rs | 15 +- .../acir_gen/acir_ir/generated_acir.rs | 173 +++++++++++------- .../src/ssa_refactor/acir_gen/mod.rs | 6 +- noir_stdlib/src/lib.nr | 4 +- 5 files changed, 122 insertions(+), 79 deletions(-) diff --git a/crates/noirc_evaluator/src/errors.rs b/crates/noirc_evaluator/src/errors.rs index 6d53668d7cb..27a87ccce36 100644 --- a/crates/noirc_evaluator/src/errors.rs +++ b/crates/noirc_evaluator/src/errors.rs @@ -44,8 +44,6 @@ pub enum InternalError { MissingArg { name: String, arg: String, location: Option }, #[error("ICE: {name:?} should be a constant")] NotAConstant { name: String, location: Option }, - #[error("{name:?} is not implemented yet")] - NotImplemented { name: String, location: Option }, #[error("ICE: Undeclared AcirVar")] UndeclaredAcirVar { location: Option }, #[error("ICE: Expected {expected:?}, found {found:?}")] @@ -61,7 +59,6 @@ impl From for FileDiagnostic { | InternalError::General { location, .. } | InternalError::MissingArg { location, .. } | InternalError::NotAConstant { location, .. } - | InternalError::NotImplemented { location, .. } | InternalError::UndeclaredAcirVar { location } | InternalError::UnExpected { location, .. } => { let file_id = location.map(|loc| loc.file).unwrap(); diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index 25d92ed8b85..9177dc9ae6c 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -265,7 +265,7 @@ impl AcirContext { typ: AcirType, ) -> Result { let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)]; - let outputs = self.black_box_function(BlackBoxFunc::XOR, inputs)?; + let outputs = self.black_box_function(BlackBoxFunc::XOR, inputs, 1)?; Ok(outputs[0]) } @@ -277,7 +277,7 @@ impl AcirContext { typ: AcirType, ) -> Result { let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)]; - let outputs = self.black_box_function(BlackBoxFunc::AND, inputs)?; + let outputs = self.black_box_function(BlackBoxFunc::AND, inputs, 1)?; Ok(outputs[0]) } @@ -304,7 +304,7 @@ impl AcirContext { let a = self.sub_var(max, lhs)?; let b = self.sub_var(max, rhs)?; let inputs = vec![AcirValue::Var(a, typ.clone()), AcirValue::Var(b, typ)]; - let outputs = self.black_box_function(BlackBoxFunc::AND, inputs)?; + let outputs = self.black_box_function(BlackBoxFunc::AND, inputs, 1)?; self.sub_var(max, outputs[0]) } } @@ -682,6 +682,7 @@ impl AcirContext { &mut self, name: BlackBoxFunc, mut inputs: Vec, + output_count: usize, ) -> Result, RuntimeError> { // Separate out any arguments that should be constants let constants = match name { @@ -717,7 +718,7 @@ impl AcirContext { let inputs = self.prepare_inputs_for_black_box_func_call(inputs)?; // Call Black box with `FunctionInput` - let outputs = self.acir_ir.call_black_box(name, inputs, constants)?; + let outputs = self.acir_ir.call_black_box(name, &inputs, constants, output_count)?; // Convert `Witness` values which are now constrained to be the output of the // black box function call into `AcirVar`s. @@ -733,9 +734,10 @@ impl AcirContext { fn prepare_inputs_for_black_box_func_call( &mut self, inputs: Vec, - ) -> Result, RuntimeError> { + ) -> Result>, RuntimeError> { let mut witnesses = Vec::new(); for input in inputs { + let mut single_val_witnesses = Vec::new(); for (input, typ) in input.flatten() { let var_data = &self.vars[&input]; @@ -745,8 +747,9 @@ impl AcirContext { let expr = var_data.to_expression(); let witness = self.acir_ir.get_or_create_witness(&expr); let num_bits = typ.bit_size(); - witnesses.push(FunctionInput { witness, num_bits }); + single_val_witnesses.push(FunctionInput { witness, num_bits }); } + witnesses.push(single_val_witnesses); } Ok(witnesses) } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs index c368a042dc9..738387fbaab 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs @@ -122,12 +122,14 @@ impl GeneratedAcir { pub(crate) fn call_black_box( &mut self, func_name: BlackBoxFunc, - mut inputs: Vec, + inputs: &[Vec], constants: Vec, + output_count: usize, ) -> Result, InternalError> { - intrinsics_check_inputs(func_name, &inputs)?; + let input_count = inputs.iter().fold(0usize, |sum, val| sum + val.len()); + intrinsics_check_inputs(func_name, input_count); + intrinsics_check_outputs(func_name, output_count); - let output_count = black_box_expected_output_size(func_name)?; let outputs = vecmap(0..output_count, |_| self.next_witness_index()); // clone is needed since outputs is moved when used in blackbox function. @@ -135,57 +137,60 @@ impl GeneratedAcir { let black_box_func_call = match func_name { BlackBoxFunc::AND => { - BlackBoxFuncCall::AND { lhs: inputs[0], rhs: inputs[1], output: outputs[0] } + BlackBoxFuncCall::AND { lhs: inputs[0][0], rhs: inputs[1][0], output: outputs[0] } } BlackBoxFunc::XOR => { - BlackBoxFuncCall::XOR { lhs: inputs[0], rhs: inputs[1], output: outputs[0] } + BlackBoxFuncCall::XOR { lhs: inputs[0][0], rhs: inputs[1][0], output: outputs[0] } } - BlackBoxFunc::RANGE => BlackBoxFuncCall::RANGE { input: inputs[0] }, - BlackBoxFunc::SHA256 => BlackBoxFuncCall::SHA256 { inputs, outputs }, - BlackBoxFunc::Blake2s => BlackBoxFuncCall::Blake2s { inputs, outputs }, - BlackBoxFunc::HashToField128Security => { - BlackBoxFuncCall::HashToField128Security { inputs, output: outputs[0] } + BlackBoxFunc::RANGE => BlackBoxFuncCall::RANGE { input: inputs[0][0] }, + BlackBoxFunc::SHA256 => BlackBoxFuncCall::SHA256 { inputs: inputs[0].clone(), outputs }, + BlackBoxFunc::Blake2s => { + BlackBoxFuncCall::Blake2s { inputs: inputs[0].clone(), outputs } } + BlackBoxFunc::HashToField128Security => BlackBoxFuncCall::HashToField128Security { + inputs: inputs[0].clone(), + output: outputs[0], + }, BlackBoxFunc::SchnorrVerify => BlackBoxFuncCall::SchnorrVerify { - public_key_x: inputs[0], - public_key_y: inputs[1], + public_key_x: inputs[0][0], + public_key_y: inputs[1][0], // Schnorr signature is an r & s, 32 bytes each - signature: inputs[2..66].to_vec(), - message: inputs[66..].to_vec(), + signature: inputs[2].clone(), + message: inputs[3].clone(), output: outputs[0], }, BlackBoxFunc::Pedersen => BlackBoxFuncCall::Pedersen { - inputs, + inputs: inputs[0].clone(), outputs: (outputs[0], outputs[1]), domain_separator: constants[0].to_u128() as u32, }, BlackBoxFunc::EcdsaSecp256k1 => BlackBoxFuncCall::EcdsaSecp256k1 { // 32 bytes for each public key co-ordinate - public_key_x: inputs[0..32].to_vec(), - public_key_y: inputs[32..64].to_vec(), + public_key_x: inputs[0].clone(), + public_key_y: inputs[1].clone(), // (r,s) are both 32 bytes each, so signature // takes up 64 bytes - signature: inputs[64..128].to_vec(), - hashed_message: inputs[128..].to_vec(), + signature: inputs[2].clone(), + hashed_message: inputs[3].clone(), output: outputs[0], }, BlackBoxFunc::EcdsaSecp256r1 => BlackBoxFuncCall::EcdsaSecp256r1 { // 32 bytes for each public key co-ordinate - public_key_x: inputs[0..32].to_vec(), - public_key_y: inputs[32..64].to_vec(), + public_key_x: inputs[0].clone(), + public_key_y: inputs[1].clone(), // (r,s) are both 32 bytes each, so signature // takes up 64 bytes - signature: inputs[64..128].to_vec(), - hashed_message: inputs[128..].to_vec(), + signature: inputs[2].clone(), + hashed_message: inputs[3].clone(), output: outputs[0], }, BlackBoxFunc::FixedBaseScalarMul => BlackBoxFuncCall::FixedBaseScalarMul { - input: inputs[0], + input: inputs[0][0], outputs: (outputs[0], outputs[1]), }, BlackBoxFunc::Keccak256 => { - let var_message_size = match inputs.pop() { - Some(var_message_size) => var_message_size, + let var_message_size = match inputs.to_vec().pop() { + Some(var_message_size) => var_message_size[0], None => { return Err(InternalError::MissingArg { name: "".to_string(), @@ -194,14 +199,31 @@ impl GeneratedAcir { }); } }; - BlackBoxFuncCall::Keccak256VariableLength { inputs, var_message_size, outputs } + BlackBoxFuncCall::Keccak256VariableLength { + inputs: inputs[0].clone(), + var_message_size, + outputs, + } } - // TODO(#1570): Generate ACIR for recursive aggregation BlackBoxFunc::RecursiveAggregation => { - return Err(InternalError::NotImplemented { - name: "recursive aggregation".to_string(), - location: None, - }) + let has_previous_aggregation = self.opcodes.iter().any(|op| { + matches!( + op, + AcirOpcode::BlackBoxFuncCall(BlackBoxFuncCall::RecursiveAggregation { .. }) + ) + }); + + let input_aggregation_object = + if !has_previous_aggregation { None } else { Some(inputs[4].clone()) }; + + BlackBoxFuncCall::RecursiveAggregation { + verification_key: inputs[0].clone(), + proof: inputs[1].clone(), + public_inputs: inputs[2].clone(), + key_hash: inputs[3][0], + input_aggregation_object, + output_aggregation_object: outputs, + } } }; @@ -819,68 +841,60 @@ impl GeneratedAcir { /// This function will return the number of inputs that a blackbox function /// expects. Returning `None` if there is no expectation. -fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Result, InternalError> { +fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Option { match name { // Bitwise opcodes will take in 2 parameters - BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(Some(2)), + BlackBoxFunc::AND | BlackBoxFunc::XOR => Some(2), // All of the hash/cipher methods will take in a // variable number of inputs. BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s | BlackBoxFunc::Pedersen - | BlackBoxFunc::HashToField128Security => Ok(None), + | BlackBoxFunc::HashToField128Security => None, // Can only apply a range constraint to one // witness at a time. - BlackBoxFunc::RANGE => Ok(Some(1)), + BlackBoxFunc::RANGE => Some(1), // Signature verification algorithms will take in a variable // number of inputs, since the message/hashed-message can vary in size. BlackBoxFunc::SchnorrVerify | BlackBoxFunc::EcdsaSecp256k1 - | BlackBoxFunc::EcdsaSecp256r1 => Ok(None), + | BlackBoxFunc::EcdsaSecp256r1 => None, // Inputs for fixed based scalar multiplication // is just a scalar - BlackBoxFunc::FixedBaseScalarMul => Ok(Some(1)), - // TODO(#1570): Generate ACIR for recursive aggregation - // RecursiveAggregation has variable inputs and we could return `None` here, - // but as it is not fully implemented we return an ICE error for now - BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented { - name: "recursive aggregation".to_string(), - location: None, - }), + BlackBoxFunc::FixedBaseScalarMul => Some(1), + // Recursive aggregation has a variable number of inputs + BlackBoxFunc::RecursiveAggregation => None, } } /// This function will return the number of outputs that a blackbox function /// expects. Returning `None` if there is no expectation. -fn black_box_expected_output_size(name: BlackBoxFunc) -> Result { +fn black_box_expected_output_size(name: BlackBoxFunc) -> Option { match name { // Bitwise opcodes will return 1 parameter which is the output // or the operation. - BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(1), + BlackBoxFunc::AND | BlackBoxFunc::XOR => Some(1), // 32 byte hash algorithms - BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => Ok(32), + BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => Some(32), // Hash to field returns a field element - BlackBoxFunc::HashToField128Security => Ok(1), + BlackBoxFunc::HashToField128Security => Some(1), // Pedersen returns a point - BlackBoxFunc::Pedersen => Ok(2), + BlackBoxFunc::Pedersen => Some(2), // Can only apply a range constraint to one // witness at a time. - BlackBoxFunc::RANGE => Ok(0), + BlackBoxFunc::RANGE => Some(0), // Signature verification algorithms will return a boolean BlackBoxFunc::SchnorrVerify | BlackBoxFunc::EcdsaSecp256k1 - | BlackBoxFunc::EcdsaSecp256r1 => Ok(1), + | BlackBoxFunc::EcdsaSecp256r1 => Some(1), // Output of fixed based scalar mul over the embedded curve // will be 2 field elements representing the point. - BlackBoxFunc::FixedBaseScalarMul => Ok(2), - // TODO(#1570): Generate ACIR for recursive aggregation - BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented { - name: "recursive aggregation".to_string(), - location: None, - }), + BlackBoxFunc::FixedBaseScalarMul => Some(2), + // Recursive aggregation has a variable number of outputs + BlackBoxFunc::RecursiveAggregation => None, } } @@ -899,16 +913,41 @@ fn black_box_expected_output_size(name: BlackBoxFunc) -> Result(_input : [u8; N]) -> [u8; 32] {} /// `` -fn intrinsics_check_inputs( - name: BlackBoxFunc, - inputs: &[FunctionInput], -) -> Result<(), InternalError> { - let expected_num_inputs = match black_box_func_expected_input_size(name)? { +fn intrinsics_check_inputs(name: BlackBoxFunc, input_count: usize) { + let expected_num_inputs = match black_box_func_expected_input_size(name) { + Some(expected_num_inputs) => expected_num_inputs, + None => return, + }; + + assert_eq!(expected_num_inputs,input_count,"Tried to call black box function {name} with {input_count} inputs, but this function's definition requires {expected_num_inputs} inputs"); +} + +/// Checks that the number of outputs being used to call the blackbox function +/// is correct according to the function definition. +/// +/// Some functions expect a variable number of outputs and in such a case, +/// this method will do nothing. An example of this is recursive aggregation. +/// In that case, this function will not check anything. +/// +/// Since we expect black box functions to be called behind a Noir shim function, +/// we trigger a compiler error if the inputs do not match. +/// +/// An example of Noir shim function is the following: +/// `` +/// #[foreign(sha256)] +/// fn verify_proof( +/// _verification_key : [Field], +/// _proof : [Field], +/// _public_inputs : [Field], +/// _key_hash : Field, +/// _input_aggregation_object : [Field; N] +/// ) -> [Field; N] {} +/// `` +fn intrinsics_check_outputs(name: BlackBoxFunc, output_count: usize) { + let expected_num_outputs = match black_box_expected_output_size(name) { Some(expected_num_inputs) => expected_num_inputs, - None => return Ok(()), + None => return, }; - let got_num_inputs = inputs.len(); - assert_eq!(expected_num_inputs,inputs.len(),"Tried to call black box function {name} with {got_num_inputs} inputs, but this function's definition requires {expected_num_inputs} inputs"); - Ok(()) + assert_eq!(expected_num_outputs,output_count,"Tried to call black box function {name} with {output_count} inputs, but this function's definition requires {expected_num_outputs} inputs"); } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index da8409431ce..5253cb71875 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -943,7 +943,11 @@ impl Context { Intrinsic::BlackBox(black_box) => { let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg)); - let vars = self.acir_context.black_box_function(black_box, inputs)?; + let output_count = result_ids.iter().fold(0usize, |sum, result_id| { + sum + dfg.try_get_array_length(*result_id).unwrap_or(1) + }); + + let vars = self.acir_context.black_box_function(black_box, inputs, output_count)?; Ok(Self::convert_vars_to_values(vars, dfg, result_ids)) } diff --git a/noir_stdlib/src/lib.nr b/noir_stdlib/src/lib.nr index f6c01ecdfaa..e654a20b1d8 100644 --- a/noir_stdlib/src/lib.nr +++ b/noir_stdlib/src/lib.nr @@ -18,11 +18,11 @@ mod compat; // Oracle calls are required to be wrapped in an unconstrained function // Thus, the only argument to the `println` oracle is expected to always be an ident #[oracle(println)] -unconstrained fn println_oracle(_input: T) {} +unconstrained fn println_oracle(_input: T) {} unconstrained fn println(input: T) { println_oracle(input); } #[foreign(recursive_aggregation)] -fn verify_proof(_verification_key : [Field], _proof : [Field], _public_inputs : [Field], _key_hash : Field, _input_aggregation_object : [Field]) -> [Field] {} +fn verify_proof(_verification_key : [Field], _proof : [Field], _public_inputs : [Field], _key_hash : Field, _input_aggregation_object : [Field; N]) -> [Field; N] {} From 3c827217900d19a710ee8a49d782ed3d43a6336c Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Tue, 1 Aug 2023 19:54:33 +0100 Subject: [PATCH 17/50] feat: Format strings for prints (#1952) * initial stdlib methods to start refactoring logign * foreign call enum * working println and println_format w/ brillig oracles * fix up brillig_oracle test * uncomment regression test for slice return from foreign calls in brillig * cargo clippy * got structs serialized correctly without aos_to_soa * remove dbg * working println_format * cargo clippy * rename enable_slices to experimental_ssa * remove dbg and fix format_field_string * initial work towards FmtStr literal * working format strins with one unified println method, still have some cleanup to-do, use Display/Debug for pretty printing * remove old comment * moved resolution of string to fmt string only when passing literals to functions * delete temp intrinsic for println new * remove unnecessary subtype * remove debugging code w/ def id as part of mono pass Ident * cleanup formatting stuff * cargo clippy * resolver test for fmt string * remove TODO comment * cargo clippy * pr comments * expose full fmtstr type to the user * add back fmt string resolver test * don't allow comparison of format strings * use JsonType Display trait * add issue for printing func params * remove Token::F variant * remove old append_abi_arg func * add comments to append_abi-arg * fix: format printing function parameters, store exprs rather than idents as part of HirLiteral::FmtStr * remove ve old comment about not being able to use witness values in fmt strings * push fix for asfs{x}{x} case and more specific regex for idents * Update crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs Co-authored-by: jfecher * remove is_match check * breakout literal fmt str case in resolver to its own func * update resolve_fmt_strings test * switch to_owned placement in resolve_fmt_str_literal * Update crates/noirc_frontend/src/ast/mod.rs Co-authored-by: jfecher * fix find_numeric_generics_in_type * add case of fmt string in if statement * add contains_numeric_typevar cases for string and fmtstring * add unify and subtype checks and fix resolver fmt string test * working generic fmtstr types * separate fmtstr codegen into variables * Update crates/noirc_frontend/src/parser/parser.rs * Update crates/noirc_abi/src/input_parser/json.rs Co-authored-by: jfecher * Update crates/noirc_frontend/src/ast/mod.rs Co-authored-by: jfecher * Update crates/noirc_frontend/src/monomorphization/mod.rs Co-authored-by: jfecher * Update crates/noirc_frontend/src/monomorphization/mod.rs Co-authored-by: jfecher * Update crates/noirc_frontend/src/monomorphization/mod.rs Co-authored-by: jfecher * Update crates/noirc_frontend/src/parser/parser.rs Co-authored-by: jfecher * keep the size of fmtrstr type as mandatory * print original fmt string in monomorphization printer * print literal update for fmtstr * add parens to f-string literal printer --------- Co-authored-by: jfecher --- Cargo.lock | 2 + crates/nargo/Cargo.toml | 3 +- crates/nargo/src/ops/foreign_calls.rs | 89 +++++++++++++++---- .../tests/test_data/debug_logs/src/main.nr | 48 +++++++++- .../src/ssa_refactor/ssa_gen/context.rs | 12 +++ .../src/ssa_refactor/ssa_gen/mod.rs | 12 +++ crates/noirc_frontend/Cargo.toml | 1 + crates/noirc_frontend/src/ast/expression.rs | 6 ++ crates/noirc_frontend/src/ast/mod.rs | 6 +- .../src/hir/resolution/errors.rs | 7 ++ .../src/hir/resolution/resolver.rs | 86 +++++++++++++++++- .../noirc_frontend/src/hir/type_check/expr.rs | 5 ++ crates/noirc_frontend/src/hir_def/expr.rs | 1 + crates/noirc_frontend/src/hir_def/types.rs | 43 ++++++++- crates/noirc_frontend/src/lexer/lexer.rs | 17 +++- crates/noirc_frontend/src/lexer/token.rs | 7 +- .../src/monomorphization/ast.rs | 7 +- .../src/monomorphization/mod.rs | 75 ++++++++++++++-- .../src/monomorphization/printer.rs | 5 ++ crates/noirc_frontend/src/node_interner.rs | 9 +- crates/noirc_frontend/src/parser/parser.rs | 15 ++++ 21 files changed, 414 insertions(+), 42 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index 4e1510c8df9..1b7a70b2063 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1982,6 +1982,7 @@ dependencies = [ "noirc_abi", "noirc_driver", "noirc_errors", + "regex", "rustc_version", "serde", "serde_json", @@ -2128,6 +2129,7 @@ dependencies = [ "iter-extended", "noirc_abi", "noirc_errors", + "regex", "rustc-hash", "serde", "serde_json", diff --git a/crates/nargo/Cargo.toml b/crates/nargo/Cargo.toml index 6c053cba931..afbafdff931 100644 --- a/crates/nargo/Cargo.toml +++ b/crates/nargo/Cargo.toml @@ -20,4 +20,5 @@ serde.workspace = true serde_json.workspace = true thiserror.workspace = true noirc_errors.workspace = true -base64.workspace = true \ No newline at end of file +base64.workspace = true +regex = "1.9.1" diff --git a/crates/nargo/src/ops/foreign_calls.rs b/crates/nargo/src/ops/foreign_calls.rs index 4bbd4eb58bc..2abc62b1032 100644 --- a/crates/nargo/src/ops/foreign_calls.rs +++ b/crates/nargo/src/ops/foreign_calls.rs @@ -4,6 +4,7 @@ use acvm::{ }; use iter_extended::vecmap; use noirc_abi::{decode_string_value, input_parser::InputValueDisplay, AbiType}; +use regex::{Captures, Regex}; use crate::errors::ForeignCallError; @@ -63,31 +64,89 @@ impl ForeignCall { } fn execute_println(foreign_call_inputs: &[Vec]) -> Result<(), ForeignCallError> { - let (abi_type, input_values) = fetch_abi_type(foreign_call_inputs)?; + let (is_fmt_str, foreign_call_inputs) = + foreign_call_inputs.split_last().ok_or(ForeignCallError::MissingForeignCallInputs)?; - // We must use a flat map here as each value in a struct will be in a separate input value - let mut input_values_as_fields = - input_values.iter().flat_map(|values| values.iter().map(|value| value.to_field())); - - let input_value_display = - InputValueDisplay::try_from_fields(&mut input_values_as_fields, abi_type)?; - - println!("{input_value_display}"); + let output_string = if is_fmt_str[0].to_field().is_one() { + convert_fmt_string_inputs(foreign_call_inputs)? + } else { + convert_string_inputs(foreign_call_inputs)? + }; + println!("{output_string}"); Ok(()) } } -/// Fetch the abi type from the foreign call input -/// The remaining input values should hold the values to be printed -fn fetch_abi_type( - foreign_call_inputs: &[Vec], -) -> Result<(AbiType, &[Vec]), ForeignCallError> { +fn convert_string_inputs(foreign_call_inputs: &[Vec]) -> Result { + // Fetch the abi type from the foreign call input + // The remaining input values should hold what is to be printed let (abi_type_as_values, input_values) = foreign_call_inputs.split_last().ok_or(ForeignCallError::MissingForeignCallInputs)?; + let abi_type = fetch_abi_type(abi_type_as_values)?; + + // We must use a flat map here as each value in a struct will be in a separate input value + let mut input_values_as_fields = + input_values.iter().flat_map(|values| vecmap(values, |value| value.to_field())); + + let input_value_display = + InputValueDisplay::try_from_fields(&mut input_values_as_fields, abi_type)?; + + Ok(input_value_display.to_string()) +} + +fn convert_fmt_string_inputs( + foreign_call_inputs: &[Vec], +) -> Result { + let (message_as_values, input_and_abi_values) = + foreign_call_inputs.split_first().ok_or(ForeignCallError::MissingForeignCallInputs)?; + + let message_as_fields = vecmap(message_as_values, |value| value.to_field()); + let message_as_string = decode_string_value(&message_as_fields); + + let (num_values, input_and_abi_values) = + input_and_abi_values.split_first().ok_or(ForeignCallError::MissingForeignCallInputs)?; + + let mut output_strings = Vec::new(); + let num_values = num_values[0].to_field().to_u128() as usize; + + let mut abi_types = Vec::new(); + for abi_values in input_and_abi_values.iter().skip(input_and_abi_values.len() - num_values) { + let abi_type = fetch_abi_type(abi_values)?; + abi_types.push(abi_type); + } + + for i in 0..num_values { + let abi_type = &abi_types[i]; + let type_size = abi_type.field_count() as usize; + + let mut input_values_as_fields = input_and_abi_values[i..(i + type_size)] + .iter() + .flat_map(|values| vecmap(values, |value| value.to_field())); + + let input_value_display = + InputValueDisplay::try_from_fields(&mut input_values_as_fields, abi_type.clone())?; + + output_strings.push(input_value_display.to_string()); + } + + let mut output_strings_iter = output_strings.into_iter(); + let re = Regex::new(r"\{([a-zA-Z0-9_]+)\}") + .expect("ICE: an invalid regex pattern was used for checking format strings"); + + let formatted_str = re.replace_all(&message_as_string, |_: &Captures| { + output_strings_iter + .next() + .expect("ICE: there are more regex matches than fields supplied to the format string") + }); + + Ok(formatted_str.into_owned()) +} + +fn fetch_abi_type(abi_type_as_values: &[Value]) -> Result { let abi_type_as_fields = vecmap(abi_type_as_values, |value| value.to_field()); let abi_type_as_string = decode_string_value(&abi_type_as_fields); let abi_type: AbiType = serde_json::from_str(&abi_type_as_string) .map_err(|err| ForeignCallError::InputParserError(err.into()))?; - Ok((abi_type, input_values)) + Ok(abi_type) } diff --git a/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr b/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr index 29386feb98c..c8d37a938c7 100644 --- a/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr +++ b/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr @@ -1,14 +1,56 @@ use dep::std; fn main(x : Field, y : pub Field) { + let string = "i: {i}, j: {j}"; + std::println(string); + + // A `fmtstr` lets you easily perform string interpolation. + let fmt_str: fmtstr<14, (Field, Field)> = f"i: {x}, j: {y}"; + let fmt_str = string_identity(fmt_str); + std::println(fmt_str); + + let fmt_str_no_type = f"i: {x}, j: {y}"; + std::println(fmt_str_no_type); + + let fmt_str_generic = string_with_generics(fmt_str_no_type); + std::println(fmt_str_generic); + + let s = myStruct { y: x, x: y }; + std::println(s); + + std::println(f"randomstring{x}{x}"); + + let fmt_str = string_with_partial_generics(f"i: {x}, s: {s}"); + std::println(fmt_str); - std::println("*** println ***"); std::println(x); std::println([x, y]); - let s = myStruct { y: x, x: y }; let foo = fooStruct { my_struct: s, foo: 15 }; - std::println(foo); + std::println(f"s: {s}, foo: {foo}"); + + std::println(f"x: 0, y: 1"); + + let s_2 = myStruct { x: 20, y: 30 }; + std::println(f"s1: {s}, s2: {s_2}"); + + let bar = fooStruct { my_struct: s_2, foo: 20 }; + std::println(f"foo1: {foo}, foo2: {bar}"); + + let struct_string = if x != 5 { f"{foo}" } else { f"{bar}" }; + std::println(struct_string); +} + +fn string_identity(string: fmtstr<14, (Field, Field)>) -> fmtstr<14, (Field, Field)> { + string +} + +fn string_with_generics(string: fmtstr) -> fmtstr { + string +} + +fn string_with_partial_generics(string: fmtstr) -> fmtstr { + string } struct myStruct { diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs index 769ee6aa09f..c485200a53e 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs @@ -177,6 +177,15 @@ impl<'a> FunctionContext<'a> { ast::Type::MutableReference(element) => { Self::map_type_helper(element, &mut |_| f(Type::Reference)) } + ast::Type::FmtString(len, fields) => { + // A format string is represented by multiple values + // The message string, the number of fields to be formatted, and + // then the encapsulated fields themselves + let final_fmt_str_fields = + vec![ast::Type::String(*len), ast::Type::Field, *fields.clone()]; + let fmt_str_tuple = ast::Type::Tuple(final_fmt_str_fields); + Self::map_type_helper(&fmt_str_tuple, f) + } other => Tree::Leaf(f(Self::convert_non_tuple_type(other))), } } @@ -204,6 +213,9 @@ impl<'a> FunctionContext<'a> { ast::Type::Integer(Signedness::Unsigned, bits) => Type::unsigned(*bits), ast::Type::Bool => Type::unsigned(1), ast::Type::String(len) => Type::Array(Rc::new(vec![Type::char()]), *len as usize), + ast::Type::FmtString(_, _) => { + panic!("convert_non_tuple_type called on a fmt string: {typ}") + } ast::Type::Unit => panic!("convert_non_tuple_type called on a unit type"), ast::Type::Tuple(_) => panic!("convert_non_tuple_type called on a tuple: {typ}"), ast::Type::Function(_, _) => Type::Function, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs index d6169dfd218..0c0dd35211b 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs @@ -135,6 +135,18 @@ impl<'a> FunctionContext<'a> { let typ = Self::convert_non_tuple_type(&ast::Type::String(elements.len() as u64)); self.codegen_array(elements, typ) } + ast::Literal::FmtStr(string, number_of_fields, fields) => { + // A caller needs multiple pieces of information to make use of a format string + // The message string, the number of fields to be formatted, and the fields themselves + let string = Expression::Literal(ast::Literal::Str(string.clone())); + let number_of_fields = Expression::Literal(ast::Literal::Integer( + (*number_of_fields as u128).into(), + ast::Type::Field, + )); + let fields = *fields.clone(); + let fmt_str_tuple = &[string, number_of_fields, fields]; + self.codegen_tuple(fmt_str_tuple) + } } } diff --git a/crates/noirc_frontend/Cargo.toml b/crates/noirc_frontend/Cargo.toml index a9a62673af6..1f902d2d399 100644 --- a/crates/noirc_frontend/Cargo.toml +++ b/crates/noirc_frontend/Cargo.toml @@ -20,6 +20,7 @@ serde.workspace = true serde_json.workspace = true rustc-hash = "1.1.0" small-ord-set = "0.1.3" +regex = "1.9.1" [dev-dependencies] strum = "0.24" diff --git a/crates/noirc_frontend/src/ast/expression.rs b/crates/noirc_frontend/src/ast/expression.rs index 1f1d226310f..b1829e8c1ee 100644 --- a/crates/noirc_frontend/src/ast/expression.rs +++ b/crates/noirc_frontend/src/ast/expression.rs @@ -72,6 +72,10 @@ impl ExpressionKind { ExpressionKind::Literal(Literal::Str(contents)) } + pub fn format_string(contents: String) -> ExpressionKind { + ExpressionKind::Literal(Literal::FmtStr(contents)) + } + pub fn constructor((type_name, fields): (Path, Vec<(Ident, Expression)>)) -> ExpressionKind { ExpressionKind::Constructor(Box::new(ConstructorExpression { type_name, fields })) } @@ -298,6 +302,7 @@ pub enum Literal { Bool(bool), Integer(FieldElement), Str(String), + FmtStr(String), Unit, } @@ -473,6 +478,7 @@ impl Display for Literal { Literal::Bool(boolean) => write!(f, "{}", if *boolean { "true" } else { "false" }), Literal::Integer(integer) => write!(f, "{}", integer.to_u128()), Literal::Str(string) => write!(f, "\"{string}\""), + Literal::FmtStr(string) => write!(f, "f\"{string}\""), Literal::Unit => write!(f, "()"), } } diff --git a/crates/noirc_frontend/src/ast/mod.rs b/crates/noirc_frontend/src/ast/mod.rs index ed73cce486a..b52c3e685d3 100644 --- a/crates/noirc_frontend/src/ast/mod.rs +++ b/crates/noirc_frontend/src/ast/mod.rs @@ -36,6 +36,7 @@ pub enum UnresolvedType { Bool(CompTime), Expression(UnresolvedTypeExpression), String(Option), + FormatString(UnresolvedTypeExpression, Box), Unit, /// A Named UnresolvedType can be a struct type or a type variable @@ -102,9 +103,10 @@ impl std::fmt::Display for UnresolvedType { Expression(expression) => expression.fmt(f), Bool(is_const) => write!(f, "{is_const}bool"), String(len) => match len { - None => write!(f, "str[]"), - Some(len) => write!(f, "str[{len}]"), + None => write!(f, "str<_>"), + Some(len) => write!(f, "str<{len}>"), }, + FormatString(len, elements) => write!(f, "fmt<{len}, {elements}"), Function(args, ret) => { let args = vecmap(args, ToString::to_string); write!(f, "fn({}) -> {ret}", args.join(", ")) diff --git a/crates/noirc_frontend/src/hir/resolution/errors.rs b/crates/noirc_frontend/src/hir/resolution/errors.rs index 82688928575..e9cf8f31393 100644 --- a/crates/noirc_frontend/src/hir/resolution/errors.rs +++ b/crates/noirc_frontend/src/hir/resolution/errors.rs @@ -74,6 +74,8 @@ pub enum ResolverError { MutableReferenceToArrayElement { span: Span }, #[error("Function is not defined in a contract yet sets is_internal")] ContractFunctionInternalInNormalFunction { span: Span }, + #[error("Numeric constants should be printed without formatting braces")] + NumericConstantInFormatString { name: String, span: Span }, } impl ResolverError { @@ -283,6 +285,11 @@ impl From for Diagnostic { "Non-contract functions cannot be 'internal'".into(), span, ), + ResolverError::NumericConstantInFormatString { name, span } => Diagnostic::simple_error( + format!("cannot find `{name}` in this scope "), + "Numeric constants should be printed without formatting braces".to_string(), + span, + ), } } } diff --git a/crates/noirc_frontend/src/hir/resolution/resolver.rs b/crates/noirc_frontend/src/hir/resolution/resolver.rs index 29b3cc485d5..fe19cb633e4 100644 --- a/crates/noirc_frontend/src/hir/resolution/resolver.rs +++ b/crates/noirc_frontend/src/hir/resolution/resolver.rs @@ -18,6 +18,7 @@ use crate::hir_def::expr::{ HirMethodCallExpression, HirPrefixExpression, }; use crate::token::Attribute; +use regex::Regex; use std::collections::{HashMap, HashSet}; use std::rc::Rc; @@ -347,6 +348,11 @@ impl<'a> Resolver<'a> { let resolved_size = self.resolve_array_size(size, new_variables); Type::String(Box::new(resolved_size)) } + UnresolvedType::FormatString(size, fields) => { + let resolved_size = self.convert_expression_type(size); + let fields = self.resolve_type_inner(*fields, new_variables); + Type::FmtString(Box::new(resolved_size), Box::new(fields)) + } UnresolvedType::Unit => Type::Unit, UnresolvedType::Unspecified => Type::Error, UnresolvedType::Error => Type::Error, @@ -775,7 +781,6 @@ impl<'a> Resolver<'a> { Type::FieldElement(_) | Type::Integer(_, _, _) | Type::Bool(_) - | Type::String(_) | Type::Unit | Type::Error | Type::TypeVariable(_, _) @@ -784,10 +789,11 @@ impl<'a> Resolver<'a> { | Type::NotConstant | Type::Forall(_, _) => (), - Type::Array(length, _) => { + Type::Array(length, element_type) => { if let Type::NamedGeneric(type_variable, name) = length.as_ref() { found.insert(name.to_string(), type_variable.clone()); } + Self::find_numeric_generics_in_type(element_type, found); } Type::Tuple(fields) => { @@ -813,6 +819,17 @@ impl<'a> Resolver<'a> { } } Type::MutableReference(element) => Self::find_numeric_generics_in_type(element, found), + Type::String(length) => { + if let Type::NamedGeneric(type_variable, name) = length.as_ref() { + found.insert(name.to_string(), type_variable.clone()); + } + } + Type::FmtString(length, fields) => { + if let Type::NamedGeneric(type_variable, name) = length.as_ref() { + found.insert(name.to_string(), type_variable.clone()); + } + Self::find_numeric_generics_in_type(fields, found); + } } } @@ -904,6 +921,7 @@ impl<'a> Resolver<'a> { } Literal::Integer(integer) => HirLiteral::Integer(integer), Literal::Str(str) => HirLiteral::Str(str), + Literal::FmtStr(str) => self.resolve_fmt_str_literal(str, expr.span), Literal::Unit => HirLiteral::Unit, }), ExpressionKind::Variable(path) => { @@ -939,6 +957,7 @@ impl<'a> Resolver<'a> { ExpressionKind::Call(call_expr) => { // Get the span and name of path for error reporting let func = self.resolve_expression(*call_expr.func); + let arguments = vecmap(call_expr.arguments, |arg| self.resolve_expression(arg)); let location = Location::new(expr.span, self.file); HirExpression::Call(HirCallExpression { func, arguments, location }) @@ -1288,6 +1307,36 @@ impl<'a> Resolver<'a> { let module_id = self.path_resolver.module_id(); module_id.module(self.def_maps).is_contract } + + fn resolve_fmt_str_literal(&mut self, str: String, call_expr_span: Span) -> HirLiteral { + let re = Regex::new(r"\{([a-zA-Z0-9_]+)\}") + .expect("ICE: an invalid regex pattern was used for checking format strings"); + let mut fmt_str_idents = Vec::new(); + for field in re.find_iter(&str) { + let matched_str = field.as_str(); + let ident_name = &matched_str[1..(matched_str.len() - 1)]; + + let scope_tree = self.scopes.current_scope_tree(); + let variable = scope_tree.find(ident_name); + if let Some((old_value, _)) = variable { + old_value.num_times_used += 1; + let expr_id = self.interner.push_expr(HirExpression::Ident(old_value.ident)); + self.interner.push_expr_location(expr_id, call_expr_span, self.file); + fmt_str_idents.push(expr_id); + } else if ident_name.parse::().is_ok() { + self.errors.push(ResolverError::NumericConstantInFormatString { + name: ident_name.to_owned(), + span: call_expr_span, + }); + } else { + self.errors.push(ResolverError::VariableNotDeclared { + name: ident_name.to_owned(), + span: call_expr_span, + }); + } + } + HirLiteral::FmtStr(str, fmt_str_idents) + } } /// Gives an error if a user tries to create a mutable reference @@ -1572,6 +1621,39 @@ mod test { assert!(errors.is_empty()); } + #[test] + fn resolve_fmt_strings() { + let src = r#" + fn main() { + let string = f"this is i: {i}"; + println(string); + + println(f"I want to print {0}"); + + let new_val = 10; + println(f"randomstring{new_val}{new_val}"); + } + fn println(x : T) -> T { + x + } + "#; + + let errors = resolve_src_code(src, vec!["main", "println"]); + assert!(errors.len() == 2, "Expected 2 errors, got: {:?}", errors); + + for err in errors { + match &err { + ResolverError::VariableNotDeclared { name, .. } => { + assert_eq!(name, "i"); + } + ResolverError::NumericConstantInFormatString { name, .. } => { + assert_eq!(name, "0"); + } + _ => unimplemented!(), + }; + } + } + fn path_unresolved_error(err: ResolverError, expected_unresolved_path: &str) { match err { ResolverError::PathResolutionError(PathResolutionError::Unresolved(name)) => { diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index b19833fb311..12c11bf20e1 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -111,6 +111,11 @@ impl<'interner> TypeChecker<'interner> { let len = Type::Constant(string.len() as u64); Type::String(Box::new(len)) } + HirLiteral::FmtStr(string, idents) => { + let len = Type::Constant(string.len() as u64); + let types = vecmap(&idents, |elem| self.check_expression(elem)); + Type::FmtString(Box::new(len), Box::new(Type::Tuple(types))) + } HirLiteral::Unit => Type::Unit, } } diff --git a/crates/noirc_frontend/src/hir_def/expr.rs b/crates/noirc_frontend/src/hir_def/expr.rs index 63b7e421dc3..5db9751591a 100644 --- a/crates/noirc_frontend/src/hir_def/expr.rs +++ b/crates/noirc_frontend/src/hir_def/expr.rs @@ -80,6 +80,7 @@ pub enum HirLiteral { Bool(bool), Integer(FieldElement), Str(String), + FmtStr(String, Vec), Unit, } diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs index 6e1113345a8..4b4318f79d6 100644 --- a/crates/noirc_frontend/src/hir_def/types.rs +++ b/crates/noirc_frontend/src/hir_def/types.rs @@ -39,6 +39,10 @@ pub enum Type { /// is either a type variable of some kind or a Type::Constant. String(Box), + /// FmtString(N, Vec) is an array of characters of length N that contains + /// a list of fields specified inside the string by the following regular expression r"\{([\S]+)\}" + FmtString(Box, Box), + /// The unit type `()`. Unit, @@ -608,7 +612,6 @@ impl Type { Type::FieldElement(_) | Type::Integer(_, _, _) | Type::Bool(_) - | Type::String(_) | Type::Unit | Type::Error | Type::TypeVariable(_, _) @@ -638,6 +641,11 @@ impl Type { }) } Type::MutableReference(element) => element.contains_numeric_typevar(target_id), + Type::String(length) => named_generic_id_matches_target(length), + Type::FmtString(length, elements) => { + elements.contains_numeric_typevar(target_id) + || named_generic_id_matches_target(length) + } } } @@ -704,6 +712,9 @@ impl std::fmt::Display for Type { } Type::Bool(comp_time) => write!(f, "{comp_time}bool"), Type::String(len) => write!(f, "str<{len}>"), + Type::FmtString(len, elements) => { + write!(f, "fmtstr<{len}, {elements}>") + } Type::Unit => write!(f, "()"), Type::Error => write!(f, "error"), Type::NamedGeneric(binding, name) => match &*binding.borrow() { @@ -1057,6 +1068,13 @@ impl Type { elem_a.try_unify(elem_b, span) } + (String(len_a), String(len_b)) => len_a.try_unify(len_b, span), + + (FmtString(len_a, elements_a), FmtString(len_b, elements_b)) => { + len_a.try_unify(len_b, span)?; + elements_a.try_unify(elements_b, span) + } + (Tuple(elements_a), Tuple(elements_b)) => { if elements_a.len() != elements_b.len() { Err(SpanKind::None) @@ -1258,6 +1276,13 @@ impl Type { elem_a.is_subtype_of(elem_b, span) } + (String(len_a), String(len_b)) => len_a.is_subtype_of(len_b, span), + + (FmtString(len_a, elements_a), FmtString(len_b, elements_b)) => { + len_a.is_subtype_of(len_b, span)?; + elements_a.is_subtype_of(elements_b, span) + } + (Tuple(elements_a), Tuple(elements_b)) => { if elements_a.len() != elements_b.len() { Err(SpanKind::None) @@ -1396,6 +1421,7 @@ impl Type { .expect("Cannot have variable sized strings as a parameter to main"); AbiType::String { length: size } } + Type::FmtString(_, _) => unreachable!("format strings cannot be used in the abi"), Type::Error => unreachable!(), Type::Unit => unreachable!(), Type::Constant(_) => unreachable!(), @@ -1497,6 +1523,11 @@ impl Type { let size = Box::new(size.substitute(type_bindings)); Type::String(size) } + Type::FmtString(size, fields) => { + let size = Box::new(size.substitute(type_bindings)); + let fields = Box::new(fields.substitute(type_bindings)); + Type::FmtString(size, fields) + } Type::NamedGeneric(binding, _) | Type::TypeVariable(binding, _) => { substitute_binding(binding) } @@ -1543,6 +1574,11 @@ impl Type { match self { Type::Array(len, elem) => len.occurs(target_id) || elem.occurs(target_id), Type::String(len) => len.occurs(target_id), + Type::FmtString(len, fields) => { + let len_occurs = len.occurs(target_id); + let field_occurs = fields.occurs(target_id); + len_occurs || field_occurs + } Type::Struct(_, generic_args) => generic_args.iter().any(|arg| arg.occurs(target_id)), Type::Tuple(fields) => fields.iter().any(|field| field.occurs(target_id)), Type::NamedGeneric(binding, _) | Type::TypeVariable(binding, _) => { @@ -1582,6 +1618,11 @@ impl Type { Array(Box::new(size.follow_bindings()), Box::new(elem.follow_bindings())) } String(size) => String(Box::new(size.follow_bindings())), + FmtString(size, args) => { + let size = Box::new(size.follow_bindings()); + let args = Box::new(args.follow_bindings()); + FmtString(size, args) + } Struct(def, args) => { let args = vecmap(args, |arg| arg.follow_bindings()); Struct(def.clone(), args) diff --git a/crates/noirc_frontend/src/lexer/lexer.rs b/crates/noirc_frontend/src/lexer/lexer.rs index e376d85ddf0..8a98d5bfa3c 100644 --- a/crates/noirc_frontend/src/lexer/lexer.rs +++ b/crates/noirc_frontend/src/lexer/lexer.rs @@ -102,7 +102,8 @@ impl<'a> Lexer<'a> { Some('}') => self.single_char_token(Token::RightBrace), Some('[') => self.single_char_token(Token::LeftBracket), Some(']') => self.single_char_token(Token::RightBracket), - Some('"') => Ok(self.eat_string_literal()), + Some('"') => Ok(self.eat_string_literal(false)), + Some('f') => self.eat_format_string_or_alpha_numeric(), Some('#') => self.eat_attribute(), Some(ch) if ch.is_ascii_alphanumeric() || ch == '_' => self.eat_alpha_numeric(ch), Some(ch) => { @@ -307,13 +308,23 @@ impl<'a> Lexer<'a> { Ok(integer_token.into_span(start, end)) } - fn eat_string_literal(&mut self) -> SpannedToken { + fn eat_string_literal(&mut self, is_format_string: bool) -> SpannedToken { let (str_literal, start_span, end_span) = self.eat_while(None, |ch| ch != '"'); - let str_literal_token = Token::Str(str_literal); + let str_literal_token = + if is_format_string { Token::FmtStr(str_literal) } else { Token::Str(str_literal) }; self.next_char(); // Advance past the closing quote str_literal_token.into_span(start_span, end_span) } + fn eat_format_string_or_alpha_numeric(&mut self) -> SpannedTokenResult { + if self.peek_char_is('"') { + self.next_char(); + Ok(self.eat_string_literal(true)) + } else { + self.eat_alpha_numeric('f') + } + } + fn parse_comment(&mut self) -> SpannedTokenResult { let _ = self.eat_while(None, |ch| ch != '\n'); self.next_token() diff --git a/crates/noirc_frontend/src/lexer/token.rs b/crates/noirc_frontend/src/lexer/token.rs index b39d1640c57..3ef1d2a5dde 100644 --- a/crates/noirc_frontend/src/lexer/token.rs +++ b/crates/noirc_frontend/src/lexer/token.rs @@ -15,6 +15,7 @@ pub enum Token { Int(FieldElement), Bool(bool), Str(String), + FmtStr(String), Keyword(Keyword), IntType(IntType), Attribute(Attribute), @@ -145,6 +146,7 @@ impl fmt::Display for Token { Token::Int(n) => write!(f, "{}", n.to_u128()), Token::Bool(b) => write!(f, "{b}"), Token::Str(ref b) => write!(f, "{b}"), + Token::FmtStr(ref b) => write!(f, "f{b}"), Token::Keyword(k) => write!(f, "{k}"), Token::Attribute(ref a) => write!(f, "{a}"), Token::IntType(ref i) => write!(f, "{i}"), @@ -212,7 +214,7 @@ impl Token { pub fn kind(&self) -> TokenKind { match *self { Token::Ident(_) => TokenKind::Ident, - Token::Int(_) | Token::Bool(_) | Token::Str(_) => TokenKind::Literal, + Token::Int(_) | Token::Bool(_) | Token::Str(_) | Token::FmtStr(_) => TokenKind::Literal, Token::Keyword(_) => TokenKind::Keyword, Token::Attribute(_) => TokenKind::Attribute, ref tok => TokenKind::Token(tok.clone()), @@ -451,6 +453,7 @@ pub enum Keyword { Field, Fn, For, + FormatString, Global, If, Impl, @@ -489,6 +492,7 @@ impl fmt::Display for Keyword { Keyword::Field => write!(f, "Field"), Keyword::Fn => write!(f, "fn"), Keyword::For => write!(f, "for"), + Keyword::FormatString => write!(f, "fmtstr"), Keyword::Global => write!(f, "global"), Keyword::If => write!(f, "if"), Keyword::Impl => write!(f, "impl"), @@ -530,6 +534,7 @@ impl Keyword { "Field" => Keyword::Field, "fn" => Keyword::Fn, "for" => Keyword::For, + "fmtstr" => Keyword::FormatString, "global" => Keyword::Global, "if" => Keyword::If, "impl" => Keyword::Impl, diff --git a/crates/noirc_frontend/src/monomorphization/ast.rs b/crates/noirc_frontend/src/monomorphization/ast.rs index 488d05c6509..7ad05f09231 100644 --- a/crates/noirc_frontend/src/monomorphization/ast.rs +++ b/crates/noirc_frontend/src/monomorphization/ast.rs @@ -83,6 +83,7 @@ pub enum Literal { Integer(FieldElement, Type), Bool(bool), Str(String), + FmtStr(String, u64, Box), } #[derive(Debug, Clone)] @@ -207,6 +208,7 @@ pub enum Type { Integer(Signedness, /*bits:*/ u32), // u32 = Integer(unsigned, 32) Bool, String(/*len:*/ u64), // String(4) = str[4] + FmtString(/*len:*/ u64, Box), Unit, Tuple(Vec), Slice(Box), @@ -313,7 +315,10 @@ impl std::fmt::Display for Type { Signedness::Signed => write!(f, "i{bits}"), }, Type::Bool => write!(f, "bool"), - Type::String(len) => write!(f, "str[{len}]"), + Type::String(len) => write!(f, "str<{len}>"), + Type::FmtString(len, elements) => { + write!(f, "fmtstr<{len}, {elements}>") + } Type::Unit => write!(f, "()"), Type::Tuple(elements) => { let elements = vecmap(elements, ToString::to_string); diff --git a/crates/noirc_frontend/src/monomorphization/mod.rs b/crates/noirc_frontend/src/monomorphization/mod.rs index bb0228091da..963d16a311c 100644 --- a/crates/noirc_frontend/src/monomorphization/mod.rs +++ b/crates/noirc_frontend/src/monomorphization/mod.rs @@ -22,7 +22,7 @@ use crate::{ }, node_interner::{self, DefinitionKind, NodeInterner, StmtId}, token::Attribute, - ContractFunctionType, FunctionKind, TypeBinding, TypeBindings, TypeVariableKind, + ContractFunctionType, FunctionKind, Type, TypeBinding, TypeBindings, TypeVariableKind, }; use self::ast::{Definition, FuncId, Function, LocalId, Program}; @@ -261,6 +261,14 @@ impl<'interner> Monomorphizer<'interner> { match self.interner.expression(&expr) { HirExpression::Ident(ident) => self.ident(ident, expr), HirExpression::Literal(HirLiteral::Str(contents)) => Literal(Str(contents)), + HirExpression::Literal(HirLiteral::FmtStr(contents, idents)) => { + let fields = vecmap(idents, |ident| self.expr(ident)); + Literal(FmtStr( + contents, + fields.len() as u64, + Box::new(ast::Expression::Tuple(fields)), + )) + } HirExpression::Literal(HirLiteral::Bool(value)) => Literal(Bool(value)), HirExpression::Literal(HirLiteral::Integer(value)) => { let typ = Self::convert_type(&self.interner.id_type(expr)); @@ -587,6 +595,11 @@ impl<'interner> Monomorphizer<'interner> { HirType::Integer(_, sign, bits) => ast::Type::Integer(*sign, *bits), HirType::Bool(_) => ast::Type::Bool, HirType::String(size) => ast::Type::String(size.evaluate_to_u64().unwrap_or(0)), + HirType::FmtString(size, fields) => { + let size = size.evaluate_to_u64().unwrap_or(0); + let fields = Box::new(Self::convert_type(fields.as_ref())); + ast::Type::FmtString(size, fields) + } HirType::Unit => ast::Type::Unit, HirType::Array(length, element) => { @@ -704,18 +717,50 @@ impl<'interner> Monomorphizer<'interner> { /// of field elements to/from JSON. The type metadata attached in this method /// is the serialized `AbiType` for the argument passed to the function. /// The caller that is running a Noir program should then deserialize the `AbiType`, - /// and accurately decode the list of field elements passed to the foreign call. - fn append_abi_arg(&self, hir_argument: &HirExpression, arguments: &mut Vec) { + /// and accurately decode the list of field elements passed to the foreign call. + fn append_abi_arg( + &mut self, + hir_argument: &HirExpression, + arguments: &mut Vec, + ) { match hir_argument { HirExpression::Ident(ident) => { let typ = self.interner.id_type(ident.id); - let typ = typ.follow_bindings(); - - let abi_type = typ.as_abi_type(); - let abi_as_string = - serde_json::to_string(&abi_type).expect("ICE: expected Abi type to serialize"); + let typ: Type = typ.follow_bindings(); + match &typ { + // A format string has many different possible types that need to be handled. + // Loop over each element in the format string to fetch each type's relevant metadata + Type::FmtString(_, elements) => { + match elements.as_ref() { + Type::Tuple(element_types) => { + for typ in element_types { + let abi_type = typ.as_abi_type(); + let abi_as_string = serde_json::to_string(&abi_type) + .expect("ICE: expected Abi type to serialize"); + + arguments.push(ast::Expression::Literal(ast::Literal::Str( + abi_as_string, + ))); + } + } + _ => unreachable!( + "ICE: format string type should be a tuple but got a {elements}" + ), + } - arguments.push(ast::Expression::Literal(ast::Literal::Str(abi_as_string))); + // The caller needs information as to whether it is handling a format string or a single type + arguments.push(ast::Expression::Literal(ast::Literal::Bool(true))); + } + _ => { + let abi_type = typ.as_abi_type(); + let abi_as_string = serde_json::to_string(&abi_type) + .expect("ICE: expected Abi type to serialize"); + + arguments.push(ast::Expression::Literal(ast::Literal::Str(abi_as_string))); + // The caller needs information as to whether it is handling a format string or a single type + arguments.push(ast::Expression::Literal(ast::Literal::Bool(false))); + } + } } _ => unreachable!("logging expr {:?} is not supported", arguments[0]), } @@ -922,6 +967,18 @@ impl<'interner> Monomorphizer<'interner> { ast::Type::String(length) => { ast::Expression::Literal(ast::Literal::Str("\0".repeat(*length as usize))) } + ast::Type::FmtString(length, fields) => { + let zeroed_tuple = self.zeroed_value_of_type(fields); + let fields_len = match &zeroed_tuple { + ast::Expression::Tuple(fields) => fields.len() as u64, + _ => unreachable!("ICE: format string fields should be structured in a tuple, but got a {zeroed_tuple}"), + }; + ast::Expression::Literal(ast::Literal::FmtStr( + "\0".repeat(*length as usize), + fields_len, + Box::new(zeroed_tuple), + )) + } ast::Type::Tuple(fields) => { ast::Expression::Tuple(vecmap(fields, |field| self.zeroed_value_of_type(field))) } diff --git a/crates/noirc_frontend/src/monomorphization/printer.rs b/crates/noirc_frontend/src/monomorphization/printer.rs index 929a14e07da..ff2b7d0d256 100644 --- a/crates/noirc_frontend/src/monomorphization/printer.rs +++ b/crates/noirc_frontend/src/monomorphization/printer.rs @@ -96,6 +96,11 @@ impl AstPrinter { super::ast::Literal::Integer(x, _) => x.fmt(f), super::ast::Literal::Bool(x) => x.fmt(f), super::ast::Literal::Str(s) => s.fmt(f), + super::ast::Literal::FmtStr(s, _, _) => { + write!(f, "f\"")?; + s.fmt(f)?; + write!(f, "\"") + } } } diff --git a/crates/noirc_frontend/src/node_interner.rs b/crates/noirc_frontend/src/node_interner.rs index f01c5f22a50..062e9daf2d6 100644 --- a/crates/noirc_frontend/src/node_interner.rs +++ b/crates/noirc_frontend/src/node_interner.rs @@ -213,11 +213,11 @@ impl DefinitionKind { matches!(self, DefinitionKind::Global(..)) } - pub fn get_rhs(self) -> Option { + pub fn get_rhs(&self) -> Option { match self { DefinitionKind::Function(_) => None, - DefinitionKind::Global(id) => Some(id), - DefinitionKind::Local(id) => id, + DefinitionKind::Global(id) => Some(*id), + DefinitionKind::Local(id) => *id, DefinitionKind::GenericType(_) => None, } } @@ -637,6 +637,7 @@ fn get_type_method_key(typ: &Type) -> Option { | Type::Constant(_) | Type::Error | Type::NotConstant - | Type::Struct(_, _) => None, + | Type::Struct(_, _) + | Type::FmtString(_, _) => None, } } diff --git a/crates/noirc_frontend/src/parser/parser.rs b/crates/noirc_frontend/src/parser/parser.rs index c6d84416975..65446e5d6c6 100644 --- a/crates/noirc_frontend/src/parser/parser.rs +++ b/crates/noirc_frontend/src/parser/parser.rs @@ -795,6 +795,7 @@ fn parse_type_inner( int_type(), bool_type(), string_type(), + format_string_type(recursive_type_parser.clone()), named_type(recursive_type_parser.clone()), array_type(recursive_type_parser.clone()), recursive_type_parser.clone().delimited_by(just(Token::LeftParen), just(Token::RightParen)), @@ -841,6 +842,19 @@ fn string_type() -> impl NoirParser { .map(UnresolvedType::String) } +fn format_string_type( + type_parser: impl NoirParser, +) -> impl NoirParser { + keyword(Keyword::FormatString) + .ignore_then( + type_expression() + .then_ignore(just(Token::Comma)) + .then(type_parser) + .delimited_by(just(Token::Less), just(Token::Greater)), + ) + .map(|(size, fields)| UnresolvedType::FormatString(size, Box::new(fields))) +} + fn int_type() -> impl NoirParser { maybe_comp_time() .then(filter_map(|span, token: Token| match token { @@ -1366,6 +1380,7 @@ fn literal() -> impl NoirParser { Token::Int(x) => ExpressionKind::integer(x), Token::Bool(b) => ExpressionKind::boolean(b), Token::Str(s) => ExpressionKind::string(s), + Token::FmtStr(s) => ExpressionKind::format_string(s), unexpected => unreachable!("Non-literal {} parsed as a literal", unexpected), }) } From 920a900818b31285c9bf2f5dd5b84c2799610a7c Mon Sep 17 00:00:00 2001 From: jfecher Date: Tue, 1 Aug 2023 14:55:21 -0500 Subject: [PATCH 18/50] feat: Add `Option` to noir stdlib (#1781) * Add Option * Fix path * Add option test * Move test * Add docs and filter, flatten methods * Fix stdlib --- .../tests/test_data/option/Nargo.toml | 6 + .../tests/test_data/option/src/main.nr | 53 ++++++ .../src/ssa_refactor/acir_gen/mod.rs | 2 +- noir_stdlib/src/lib.nr | 1 + noir_stdlib/src/option.nr | 157 ++++++++++++++++++ 5 files changed, 218 insertions(+), 1 deletion(-) create mode 100644 crates/nargo_cli/tests/test_data/option/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/option/src/main.nr create mode 100644 noir_stdlib/src/option.nr diff --git a/crates/nargo_cli/tests/test_data/option/Nargo.toml b/crates/nargo_cli/tests/test_data/option/Nargo.toml new file mode 100644 index 00000000000..2248e9c06dd --- /dev/null +++ b/crates/nargo_cli/tests/test_data/option/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "option" +authors = [""] +compiler_version = "0.7.0" + +[dependencies] diff --git a/crates/nargo_cli/tests/test_data/option/src/main.nr b/crates/nargo_cli/tests/test_data/option/src/main.nr new file mode 100644 index 00000000000..0a41b9a629c --- /dev/null +++ b/crates/nargo_cli/tests/test_data/option/src/main.nr @@ -0,0 +1,53 @@ +use dep::std::option::Option; + +fn main() { + let none = Option::none(); + let some = Option::some(3); + + assert(none.is_none()); + assert(some.is_some()); + + assert(some.unwrap() == 3); + + assert(none.unwrap_or(2) == 2); + assert(some.unwrap_or(2) == 3); + + assert(none.unwrap_or_else(|| 5) == 5); + assert(some.unwrap_or_else(|| 5) == 3); + + assert(none.map(|x| x * 2).is_none()); + assert(some.map(|x| x * 2).unwrap() == 6); + + assert(none.map_or(0, |x| x * 2) == 0); + assert(some.map_or(0, |x| x * 2) == 6); + + assert(none.map_or_else(|| 0, |x| x * 2) == 0); + assert(some.map_or_else(|| 0, |x| x * 2) == 6); + + assert(none.and(none).is_none()); + assert(none.and(some).is_none()); + assert(some.and(none).is_none()); + assert(some.and(some).is_some()); + + let add1_u64 = |value: Field| Option::some(value as u64 + 1); + + assert(none.and_then(|_value| Option::none()).is_none()); + assert(none.and_then(add1_u64).is_none()); + assert(some.and_then(|_value| Option::none()).is_none()); + assert(some.and_then(add1_u64).unwrap() == 4); + + assert(none.or(none).is_none()); + assert(none.or(some).is_some()); + assert(some.or(none).is_some()); + assert(some.or(some).is_some()); + + assert(none.or_else(|| Option::none()).is_none()); + assert(none.or_else(|| Option::some(5)).is_some()); + assert(some.or_else(|| Option::none()).is_some()); + assert(some.or_else(|| Option::some(5)).is_some()); + + assert(none.xor(none).is_none()); + assert(none.xor(some).is_some()); + assert(some.xor(none).is_some()); + assert(some.xor(some).is_none()); +} diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index 5253cb71875..4a7d2e46775 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -1002,7 +1002,7 @@ impl Context { } Intrinsic::ArrayLen => { let len = match self.convert_value(arguments[0], dfg) { - AcirValue::Var(_, _) => unreachable!("Non-array passed to array.len() method"), + AcirValue::Var(_, _) => unreachable!("Non-array passed to array.len() method"), AcirValue::Array(values) => (values.len() as u128).into(), AcirValue::DynamicArray(array) => (array.len as u128).into(), }; diff --git a/noir_stdlib/src/lib.nr b/noir_stdlib/src/lib.nr index e654a20b1d8..9c0dcc6b269 100644 --- a/noir_stdlib/src/lib.nr +++ b/noir_stdlib/src/lib.nr @@ -14,6 +14,7 @@ mod ec; mod unsafe; mod collections; mod compat; +mod option; // Oracle calls are required to be wrapped in an unconstrained function // Thus, the only argument to the `println` oracle is expected to always be an ident diff --git a/noir_stdlib/src/option.nr b/noir_stdlib/src/option.nr new file mode 100644 index 00000000000..5cc4dfae887 --- /dev/null +++ b/noir_stdlib/src/option.nr @@ -0,0 +1,157 @@ +struct Option { + _is_some: bool, + value: T, +} + +impl Option { + /// Constructs a None value + fn none() -> Self { + Self { _is_some: false, value: crate::unsafe::zeroed() } + } + + /// Constructs a Some wrapper around the given value + fn some(value: T) -> Self { + Self { _is_some: true, value } + } + + /// True if this Option is None + fn is_none(self) -> bool { + !self._is_some + } + + /// True if this Option is Some + fn is_some(self) -> bool { + self._is_some + } + + /// Asserts `self.is_some()` and returns the wrapped value. + fn unwrap(self) -> T { + assert(self._is_some); + self.value + } + + /// Returns the wrapped value if `self.is_some()`. Otherwise, returns the given default value. + fn unwrap_or(self, default: T) -> T { + if self._is_some { + self.value + } else { + default + } + } + + /// Returns the wrapped value if `self.is_some()`. Otherwise, calls the given function to return + /// a default value. + fn unwrap_or_else(self, default: fn() -> T) -> T { + if self._is_some { + self.value + } else { + default() + } + } + + /// If self is `Some(x)`, this returns `Some(f(x))`. Otherwise, this returns `None`. + fn map(self, f: fn(T) -> U) -> Option { + if self._is_some { + Option::some(f(self.value)) + } else { + Option::none() + } + } + + /// If self is `Some(x)`, this returns `f(x)`. Otherwise, this returns the given default value. + fn map_or(self, default: U, f: fn(T) -> U) -> U { + if self._is_some { + f(self.value) + } else { + default + } + } + + /// If self is `Some(x)`, this returns `f(x)`. Otherwise, this returns `default()`. + fn map_or_else(self, default: fn() -> U, f: fn(T) -> U) -> U { + if self._is_some { + f(self.value) + } else { + default() + } + } + + /// Returns None if self is None. Otherwise, this returns `other`. + fn and(self, other: Self) -> Self { + if self.is_none() { + Option::none() + } else { + other + } + } + + /// If self is None, this returns None. Otherwise, this calls the given function + /// with the Some value contained within self, and returns the result of that call. + /// + /// In some languages this function is called `flat_map` or `bind`. + fn and_then(self, f: fn(T) -> Option) -> Option { + if self._is_some { + f(self.value) + } else { + Option::none() + } + } + + /// If self is Some, return self. Otherwise, return `other`. + fn or(self, other: Self) -> Self { + if self._is_some { + self + } else { + other + } + } + + /// If self is Some, return self. Otherwise, return `default()`. + fn or_else(self, default: fn() -> Self) -> Self { + if self._is_some { + self + } else { + default() + } + } + + // If only one of the two Options is Some, return that option. + // Otherwise, if both options are Some or both are None, None is returned. + fn xor(self, other: Self) -> Self { + if self._is_some { + if other._is_some { + Option::none() + } else { + self + } + } else if other._is_some { + other + } else { + Option::none() + } + } + + /// Returns `Some(x)` if self is `Some(x)` and `predicate(x)` is true. + /// Otherwise, this returns `None` + fn filter(self, predicate: fn(T) -> bool) -> Self { + if self._is_some { + if predicate(self.value) { + self + } else { + Option::none() + } + } else { + Option::none() + } + } + + /// Flattens an Option> into a Option. + /// This returns None if the outer Option is None. Otherwise, this returns the inner Option. + fn flatten(option: Option>) -> Option { + if option._is_some { + option.value + } else { + Option::none() + } + } +} From ce94cb4f9f9fccf504de9d0b12b8760fc8fab75c Mon Sep 17 00:00:00 2001 From: jfecher Date: Tue, 1 Aug 2023 15:12:03 -0500 Subject: [PATCH 19/50] feat: Implement type aliases (#2112) * . * . * . * . * stash * . * . * . * remove tyalias as an hir type * namings * . * clippy * move to collector * working? * working? * move test to new_ssa * resolve type alias name in module * . * comments * review * move test to test_data folder * type aliases cannot be used in type namespace * more efficient? * remove comment * use interner for id * . * Rework def_interner storage of aliases * Update crates/noirc_frontend/src/ast/type_alias.rs Co-authored-by: Maxim Vezenov * Update crates/noirc_frontend/src/ast/type_alias.rs Co-authored-by: Maxim Vezenov * Update crates/noirc_frontend/src/ast/type_alias.rs Co-authored-by: Maxim Vezenov * Update crates/noirc_frontend/src/hir/def_collector/dc_mod.rs Co-authored-by: Maxim Vezenov * Update crates/noirc_frontend/src/hir/resolution/resolver.rs Co-authored-by: Maxim Vezenov * typ -> type --------- Co-authored-by: ethan-000 Co-authored-by: Ethan-000 Co-authored-by: Maxim Vezenov --- .../tests/test_data/type_aliases/Nargo.toml | 6 ++ .../tests/test_data/type_aliases/Prover.toml | 1 + .../tests/test_data/type_aliases/src/main.nr | 31 ++++++++ crates/noirc_frontend/src/ast/mod.rs | 2 + crates/noirc_frontend/src/ast/type_alias.rs | 31 ++++++++ .../src/hir/def_collector/dc_crate.rs | 38 +++++++++- .../src/hir/def_collector/dc_mod.rs | 40 ++++++++++- .../src/hir/def_map/item_scope.rs | 1 + .../src/hir/def_map/module_data.rs | 10 ++- .../src/hir/def_map/module_def.rs | 31 +++++++- .../src/hir/resolution/import.rs | 1 + .../src/hir/resolution/resolver.rs | 70 +++++++++++++++---- crates/noirc_frontend/src/hir_def/types.rs | 68 +++++++++++++++++- crates/noirc_frontend/src/node_interner.rs | 49 ++++++++++++- crates/noirc_frontend/src/parser/mod.rs | 15 +++- crates/noirc_frontend/src/parser/parser.rs | 28 +++++++- 16 files changed, 393 insertions(+), 29 deletions(-) create mode 100644 crates/nargo_cli/tests/test_data/type_aliases/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/type_aliases/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/type_aliases/src/main.nr create mode 100644 crates/noirc_frontend/src/ast/type_alias.rs diff --git a/crates/nargo_cli/tests/test_data/type_aliases/Nargo.toml b/crates/nargo_cli/tests/test_data/type_aliases/Nargo.toml new file mode 100644 index 00000000000..a797cb0bbe2 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/type_aliases/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "type_aliases" +authors = [""] +compiler_version = "0.1" + +[dependencies] diff --git a/crates/nargo_cli/tests/test_data/type_aliases/Prover.toml b/crates/nargo_cli/tests/test_data/type_aliases/Prover.toml new file mode 100644 index 00000000000..771df41899d --- /dev/null +++ b/crates/nargo_cli/tests/test_data/type_aliases/Prover.toml @@ -0,0 +1 @@ +x = [2, 3] diff --git a/crates/nargo_cli/tests/test_data/type_aliases/src/main.nr b/crates/nargo_cli/tests/test_data/type_aliases/src/main.nr new file mode 100644 index 00000000000..6cfafc91b7d --- /dev/null +++ b/crates/nargo_cli/tests/test_data/type_aliases/src/main.nr @@ -0,0 +1,31 @@ +use dep::std; + +type Foo = [T; 2]; + +type Bar = Field; + +type Three = Two; +type Two = One; +type One = (A, B); + +struct MyStruct { + foo: Bar, +} + +fn main(x : [Field; 2]) { + let a: Foo = [1, 2]; + assert(a[0] != x[0]); + + let b: Bar = 2; + assert(x[0] == b); + + let c: u8 = 1; + let d: u32 = 2; + let e: Three = (c, d); + assert(e.0 == 1); + + let s = MyStruct { + foo: 10 + }; + assert(s.foo == 10); +} diff --git a/crates/noirc_frontend/src/ast/mod.rs b/crates/noirc_frontend/src/ast/mod.rs index b52c3e685d3..6aa373c66a9 100644 --- a/crates/noirc_frontend/src/ast/mod.rs +++ b/crates/noirc_frontend/src/ast/mod.rs @@ -9,6 +9,7 @@ mod function; mod statement; mod structure; mod traits; +mod type_alias; pub use expression::*; pub use function::*; @@ -17,6 +18,7 @@ use noirc_errors::Span; pub use statement::*; pub use structure::*; pub use traits::*; +pub use type_alias::*; use crate::{ parser::{ParserError, ParserErrorReason}, diff --git a/crates/noirc_frontend/src/ast/type_alias.rs b/crates/noirc_frontend/src/ast/type_alias.rs new file mode 100644 index 00000000000..76a1e5a7e30 --- /dev/null +++ b/crates/noirc_frontend/src/ast/type_alias.rs @@ -0,0 +1,31 @@ +use crate::{Ident, UnresolvedGenerics, UnresolvedType}; +use iter_extended::vecmap; +use noirc_errors::Span; +use std::fmt::Display; + +/// Ast node for type aliases +#[derive(Clone, Debug)] +pub struct NoirTypeAlias { + pub name: Ident, + pub generics: UnresolvedGenerics, + pub typ: UnresolvedType, + pub span: Span, +} + +impl NoirTypeAlias { + pub fn new( + name: Ident, + generics: UnresolvedGenerics, + typ: UnresolvedType, + span: Span, + ) -> NoirTypeAlias { + NoirTypeAlias { name, generics, typ, span } + } +} + +impl Display for NoirTypeAlias { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + let generics = vecmap(&self.generics, |generic| generic.to_string()); + write!(f, "type {}<{}> = {}", self.name, generics.join(", "), self.typ) + } +} diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs index 3f30a4990e4..e974961a405 100644 --- a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs +++ b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs @@ -10,10 +10,10 @@ use crate::hir::resolution::{ }; use crate::hir::type_check::{type_check_func, TypeChecker}; use crate::hir::Context; -use crate::node_interner::{FuncId, NodeInterner, StmtId, StructId}; +use crate::node_interner::{FuncId, NodeInterner, StmtId, StructId, TypeAliasId}; use crate::{ - ExpressionKind, Generics, Ident, LetStatement, NoirFunction, NoirStruct, ParsedModule, Shared, - Type, TypeBinding, UnresolvedGenerics, UnresolvedType, + ExpressionKind, Generics, Ident, LetStatement, NoirFunction, NoirStruct, NoirTypeAlias, + ParsedModule, Shared, Type, TypeBinding, UnresolvedGenerics, UnresolvedType, }; use fm::FileId; use iter_extended::vecmap; @@ -40,6 +40,13 @@ pub struct UnresolvedStruct { pub struct_def: NoirStruct, } +#[derive(Clone)] +pub struct UnresolvedTypeAlias { + pub file_id: FileId, + pub module_id: LocalModuleId, + pub type_alias_def: NoirTypeAlias, +} + #[derive(Clone)] pub struct UnresolvedGlobal { pub file_id: FileId, @@ -54,6 +61,7 @@ pub struct DefCollector { pub(crate) collected_imports: Vec, pub(crate) collected_functions: Vec, pub(crate) collected_types: HashMap, + pub(crate) collected_type_aliases: HashMap, pub(crate) collected_globals: Vec, pub(crate) collected_impls: ImplMap, } @@ -71,6 +79,7 @@ impl DefCollector { collected_imports: vec![], collected_functions: vec![], collected_types: HashMap::new(), + collected_type_aliases: HashMap::new(), collected_impls: HashMap::new(), collected_globals: vec![], } @@ -157,6 +166,8 @@ impl DefCollector { let mut file_global_ids = resolve_globals(context, integer_globals, crate_id, errors); + resolve_type_aliases(context, def_collector.collected_type_aliases, crate_id, errors); + // Must resolve structs before we resolve globals. resolve_structs(context, def_collector.collected_types, crate_id, errors); @@ -358,6 +369,27 @@ fn resolve_struct_fields( (generics, fields) } +fn resolve_type_aliases( + context: &mut Context, + type_aliases: HashMap, + crate_id: CrateId, + all_errors: &mut Vec, +) { + for (type_id, unresolved_typ) in type_aliases { + let path_resolver = StandardPathResolver::new(ModuleId { + local_id: unresolved_typ.module_id, + krate: crate_id, + }); + let file = unresolved_typ.file_id; + let (typ, generics, errors) = + Resolver::new(&mut context.def_interner, &path_resolver, &context.def_maps, file) + .resolve_type_aliases(unresolved_typ.type_alias_def); + extend_errors(all_errors, file, errors); + + context.def_interner.set_type_alias(type_id, typ, generics); + } +} + fn resolve_impls( interner: &mut NodeInterner, crate_id: CrateId, diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs b/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs index 2e478b6c040..37c017ecb96 100644 --- a/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs +++ b/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs @@ -3,11 +3,12 @@ use noirc_errors::FileDiagnostic; use crate::{ graph::CrateId, hir::def_collector::dc_crate::UnresolvedStruct, node_interner::StructId, - parser::SubModule, Ident, LetStatement, NoirFunction, NoirStruct, ParsedModule, TypeImpl, + parser::SubModule, Ident, LetStatement, NoirFunction, NoirStruct, NoirTypeAlias, ParsedModule, + TypeImpl, }; use super::{ - dc_crate::{DefCollector, UnresolvedFunctions, UnresolvedGlobal}, + dc_crate::{DefCollector, UnresolvedFunctions, UnresolvedGlobal, UnresolvedTypeAlias}, errors::DefCollectorErrorKind, }; use crate::hir::def_map::{parse_file, LocalModuleId, ModuleData, ModuleId, ModuleOrigin}; @@ -55,6 +56,8 @@ pub fn collect_defs( collector.collect_structs(ast.types, crate_id, errors); + collector.collect_type_aliases(context, ast.type_aliases, errors); + collector.collect_functions(context, ast.functions, errors); collector.collect_impls(context, ast.impls); @@ -183,6 +186,39 @@ impl<'a> ModCollector<'a> { } } + /// Collect any type aliases definitions declared within the ast. + /// Returns a vector of errors if any type aliases were already defined. + fn collect_type_aliases( + &mut self, + context: &mut Context, + type_aliases: Vec, + errors: &mut Vec, + ) { + for type_alias in type_aliases { + let name = type_alias.name.clone(); + + // And store the TypeId -> TypeAlias mapping somewhere it is reachable + let unresolved = UnresolvedTypeAlias { + file_id: self.file_id, + module_id: self.module_id, + type_alias_def: type_alias, + }; + + let type_alias_id = context.def_interner.push_type_alias(&unresolved); + + // Add the type alias to scope so its path can be looked up later + let result = self.def_collector.def_map.modules[self.module_id.0] + .declare_type_alias(name, type_alias_id); + + if let Err((first_def, second_def)) = result { + let err = DefCollectorErrorKind::DuplicateFunction { first_def, second_def }; + errors.push(err.into_file_diagnostic(self.file_id)); + } + + self.def_collector.collected_type_aliases.insert(type_alias_id, unresolved); + } + } + fn collect_submodules( &mut self, context: &mut Context, diff --git a/crates/noirc_frontend/src/hir/def_map/item_scope.rs b/crates/noirc_frontend/src/hir/def_map/item_scope.rs index 52201f7ade3..760088a3b7e 100644 --- a/crates/noirc_frontend/src/hir/def_map/item_scope.rs +++ b/crates/noirc_frontend/src/hir/def_map/item_scope.rs @@ -48,6 +48,7 @@ impl ItemScope { ModuleDefId::ModuleId(_) => add_item(&mut self.types), ModuleDefId::FunctionId(_) => add_item(&mut self.values), ModuleDefId::TypeId(_) => add_item(&mut self.types), + ModuleDefId::TypeAliasId(_) => add_item(&mut self.types), ModuleDefId::GlobalId(_) => add_item(&mut self.values), } } diff --git a/crates/noirc_frontend/src/hir/def_map/module_data.rs b/crates/noirc_frontend/src/hir/def_map/module_data.rs index 20906885ad9..5b93d04fea7 100644 --- a/crates/noirc_frontend/src/hir/def_map/module_data.rs +++ b/crates/noirc_frontend/src/hir/def_map/module_data.rs @@ -3,7 +3,7 @@ use std::collections::HashMap; use fm::FileId; use crate::{ - node_interner::{FuncId, StmtId, StructId}, + node_interner::{FuncId, StmtId, StructId, TypeAliasId}, Ident, }; @@ -65,6 +65,14 @@ impl ModuleData { self.declare(name, ModuleDefId::TypeId(id)) } + pub fn declare_type_alias( + &mut self, + name: Ident, + id: TypeAliasId, + ) -> Result<(), (Ident, Ident)> { + self.declare(name, id.into()) + } + pub fn declare_child_module( &mut self, name: Ident, diff --git a/crates/noirc_frontend/src/hir/def_map/module_def.rs b/crates/noirc_frontend/src/hir/def_map/module_def.rs index 399ee15700c..b64ced78772 100644 --- a/crates/noirc_frontend/src/hir/def_map/module_def.rs +++ b/crates/noirc_frontend/src/hir/def_map/module_def.rs @@ -1,4 +1,4 @@ -use crate::node_interner::{FuncId, StmtId, StructId}; +use crate::node_interner::{FuncId, StmtId, StructId, TypeAliasId}; use super::ModuleId; @@ -8,6 +8,7 @@ pub enum ModuleDefId { ModuleId(ModuleId), FunctionId(FuncId), TypeId(StructId), + TypeAliasId(TypeAliasId), GlobalId(StmtId), } @@ -26,6 +27,13 @@ impl ModuleDefId { } } + pub fn as_type_alias(&self) -> Option { + match self { + ModuleDefId::TypeAliasId(type_alias_id) => Some(*type_alias_id), + _ => None, + } + } + pub fn as_global(&self) -> Option { match self { ModuleDefId::GlobalId(stmt_id) => Some(*stmt_id), @@ -39,6 +47,7 @@ impl ModuleDefId { match self { ModuleDefId::FunctionId(_) => "function", ModuleDefId::TypeId(_) => "type", + ModuleDefId::TypeAliasId(_) => "type alias", ModuleDefId::ModuleId(_) => "module", ModuleDefId::GlobalId(_) => "global", } @@ -57,6 +66,12 @@ impl From for ModuleDefId { } } +impl From for ModuleDefId { + fn from(fid: TypeAliasId) -> Self { + ModuleDefId::TypeAliasId(fid) + } +} + impl From for ModuleDefId { fn from(stmt_id: StmtId) -> Self { ModuleDefId::GlobalId(stmt_id) @@ -97,6 +112,20 @@ impl TryFromModuleDefId for StructId { } } +impl TryFromModuleDefId for TypeAliasId { + fn try_from(id: ModuleDefId) -> Option { + id.as_type_alias() + } + + fn dummy_id() -> Self { + TypeAliasId::dummy_id() + } + + fn description() -> String { + "type alias".to_string() + } +} + impl TryFromModuleDefId for StmtId { fn try_from(id: ModuleDefId) -> Option { id.as_global() diff --git a/crates/noirc_frontend/src/hir/resolution/import.rs b/crates/noirc_frontend/src/hir/resolution/import.rs index 0bc7e065adb..9a6ef9b1b8b 100644 --- a/crates/noirc_frontend/src/hir/resolution/import.rs +++ b/crates/noirc_frontend/src/hir/resolution/import.rs @@ -152,6 +152,7 @@ fn resolve_name_in_module( ModuleDefId::FunctionId(_) => panic!("functions cannot be in the type namespace"), // TODO: If impls are ever implemented, types can be used in a path ModuleDefId::TypeId(id) => id.0, + ModuleDefId::TypeAliasId(_) => panic!("type aliases cannot be used in type namespace"), ModuleDefId::GlobalId(_) => panic!("globals cannot be in the type namespace"), }; diff --git a/crates/noirc_frontend/src/hir/resolution/resolver.rs b/crates/noirc_frontend/src/hir/resolution/resolver.rs index fe19cb633e4..8b4f97dbd8e 100644 --- a/crates/noirc_frontend/src/hir/resolution/resolver.rs +++ b/crates/noirc_frontend/src/hir/resolution/resolver.rs @@ -34,9 +34,9 @@ use crate::{ Statement, }; use crate::{ - ArrayLiteral, ContractFunctionType, Generics, LValue, NoirStruct, Path, Pattern, Shared, - StructType, Type, TypeBinding, TypeVariable, UnaryOp, UnresolvedGenerics, UnresolvedType, - UnresolvedTypeExpression, ERROR_IDENT, + ArrayLiteral, ContractFunctionType, Generics, LValue, NoirStruct, NoirTypeAlias, Path, Pattern, + Shared, StructType, Type, TypeAliasType, TypeBinding, TypeVariable, UnaryOp, + UnresolvedGenerics, UnresolvedType, UnresolvedTypeExpression, ERROR_IDENT, }; use fm::FileId; use iter_extended::vecmap; @@ -403,22 +403,27 @@ impl<'a> Resolver<'a> { } let span = path.span(); + let mut args = vecmap(args, |arg| self.resolve_type_inner(arg, new_variables)); + + if let Some(type_alias_type) = self.lookup_type_alias(path.clone()) { + let expected_generic_count = type_alias_type.generics.len(); + let type_alias_string = type_alias_type.to_string(); + let id = type_alias_type.id; + + self.verify_generics_count(expected_generic_count, &mut args, span, || { + type_alias_string + }); + + return self.interner.get_type_alias(id).get_type(&args); + } + match self.lookup_struct_or_error(path) { Some(struct_type) => { - let mut args = vecmap(args, |arg| self.resolve_type_inner(arg, new_variables)); let expected_generic_count = struct_type.borrow().generics.len(); - if args.len() != expected_generic_count { - self.push_err(ResolverError::IncorrectGenericCount { - span, - struct_type: struct_type.borrow().to_string(), - actual: args.len(), - expected: expected_generic_count, - }); - - // Fix the generic count so we can continue typechecking - args.resize_with(expected_generic_count, || Type::Error); - } + self.verify_generics_count(expected_generic_count, &mut args, span, || { + struct_type.borrow().to_string() + }); Type::Struct(struct_type, args) } @@ -426,6 +431,26 @@ impl<'a> Resolver<'a> { } } + fn verify_generics_count( + &mut self, + expected_count: usize, + args: &mut Vec, + span: Span, + type_name: impl FnOnce() -> String, + ) { + if args.len() != expected_count { + self.errors.push(ResolverError::IncorrectGenericCount { + span, + struct_type: type_name(), + actual: args.len(), + expected: expected_count, + }); + + // Fix the generic count so we can continue typechecking + args.resize_with(expected_count, || Type::Error); + } + } + fn lookup_generic_or_global_type(&mut self, path: &Path) -> Option { if path.segments.len() == 1 { let name = &path.last_segment().0.contents; @@ -517,6 +542,17 @@ impl<'a> Resolver<'a> { self.resolve_type_inner(typ, &mut vec![]) } + pub fn resolve_type_aliases( + mut self, + unresolved: NoirTypeAlias, + ) -> (Type, Generics, Vec) { + let generics = self.add_generics(&unresolved.generics); + self.resolve_local_globals(); + let typ = self.resolve_type(unresolved.typ); + + (typ, generics, self.errors) + } + pub fn take_errors(self) -> Vec { self.errors } @@ -1253,6 +1289,10 @@ impl<'a> Resolver<'a> { } } + fn lookup_type_alias(&mut self, path: Path) -> Option<&TypeAliasType> { + self.lookup(path).ok().map(|id| self.interner.get_type_alias(id)) + } + fn resolve_path(&mut self, path: Path) -> Result { self.path_resolver.resolve(self.def_maps, path).map_err(ResolverError::PathResolutionError) } diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs index 4b4318f79d6..df4c2f6c229 100644 --- a/crates/noirc_frontend/src/hir_def/types.rs +++ b/crates/noirc_frontend/src/hir_def/types.rs @@ -7,7 +7,7 @@ use std::{ use crate::{ hir::type_check::TypeCheckError, - node_interner::{ExprId, NodeInterner}, + node_interner::{ExprId, NodeInterner, TypeAliasId}, }; use iter_extended::vecmap; use noirc_abi::AbiType; @@ -226,6 +226,72 @@ impl std::fmt::Display for StructType { } } +/// Wrap around an unsolved type +#[derive(Debug, Clone, Eq)] +pub struct TypeAliasType { + pub name: Ident, + pub id: TypeAliasId, + pub typ: Type, + pub generics: Generics, + pub span: Span, +} + +impl std::hash::Hash for TypeAliasType { + fn hash(&self, state: &mut H) { + self.id.hash(state); + } +} + +impl PartialEq for TypeAliasType { + fn eq(&self, other: &Self) -> bool { + self.id == other.id + } +} + +impl std::fmt::Display for TypeAliasType { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + write!(f, "{}", self.name)?; + + if !self.generics.is_empty() { + let generics = vecmap(&self.generics, |(_, binding)| binding.borrow().to_string()); + write!(f, "{}", generics.join(", "))?; + } + + Ok(()) + } +} + +impl TypeAliasType { + pub fn new( + id: TypeAliasId, + name: Ident, + span: Span, + typ: Type, + generics: Generics, + ) -> TypeAliasType { + TypeAliasType { id, typ, name, span, generics } + } + + pub fn set_type_and_generics(&mut self, new_typ: Type, new_generics: Generics) { + assert_eq!(self.typ, Type::Error); + self.typ = new_typ; + self.generics = new_generics; + } + + pub fn get_type(&self, generic_args: &[Type]) -> Type { + assert_eq!(self.generics.len(), generic_args.len()); + + let substitutions = self + .generics + .iter() + .zip(generic_args) + .map(|((old_id, old_var), new)| (*old_id, (old_var.clone(), new.clone()))) + .collect(); + + self.typ.substitute(&substitutions) + } +} + /// A shared, mutable reference to some T. /// Wrapper is required for Hash impl of RefCell. #[derive(Debug, Eq, PartialOrd, Ord)] diff --git a/crates/noirc_frontend/src/node_interner.rs b/crates/noirc_frontend/src/node_interner.rs index 062e9daf2d6..f5fea5c1ea7 100644 --- a/crates/noirc_frontend/src/node_interner.rs +++ b/crates/noirc_frontend/src/node_interner.rs @@ -7,7 +7,7 @@ use noirc_errors::{Location, Span, Spanned}; use crate::ast::Ident; use crate::graph::CrateId; -use crate::hir::def_collector::dc_crate::UnresolvedStruct; +use crate::hir::def_collector::dc_crate::{UnresolvedStruct, UnresolvedTypeAlias}; use crate::hir::def_map::{LocalModuleId, ModuleId}; use crate::hir::StorageSlot; use crate::hir_def::stmt::HirLetStatement; @@ -17,7 +17,10 @@ use crate::hir_def::{ function::{FuncMeta, HirFunction}, stmt::HirStatement, }; -use crate::{Shared, TypeBinding, TypeBindings, TypeVariable, TypeVariableId, TypeVariableKind}; +use crate::{ + Generics, Shared, TypeAliasType, TypeBinding, TypeBindings, TypeVariable, TypeVariableId, + TypeVariableKind, +}; /// The node interner is the central storage location of all nodes in Noir's Hir (the /// various node types can be found in hir_def). The interner is also used to collect @@ -52,6 +55,12 @@ pub struct NodeInterner { // methods from impls to the type. structs: HashMap>, + // Type Aliases map. + // + // Map type aliases to the actual type. + // When resolving types, check against this map to see if a type alias is defined. + type_aliases: Vec, + /// Map from ExprId (referring to a Function/Method call) to its corresponding TypeBindings, /// filled out during type checking from instantiated variables. Used during monomorphization /// to map call site types back onto function parameter types, and undo this binding as needed. @@ -132,6 +141,15 @@ impl StructId { } } +#[derive(Debug, Eq, PartialEq, Hash, Copy, Clone)] +pub struct TypeAliasId(pub usize); + +impl TypeAliasId { + pub fn dummy_id() -> TypeAliasId { + TypeAliasId(std::usize::MAX) + } +} + macro_rules! into_index { ($id_type:ty) => { impl From<$id_type> for Index { @@ -243,6 +261,7 @@ impl Default for NodeInterner { definitions: vec![], id_to_type: HashMap::new(), structs: HashMap::new(), + type_aliases: Vec::new(), instantiation_bindings: HashMap::new(), field_indices: HashMap::new(), next_type_variable_id: 0, @@ -305,11 +324,33 @@ impl NodeInterner { ); } + pub fn push_type_alias(&mut self, typ: &UnresolvedTypeAlias) -> TypeAliasId { + let type_id = TypeAliasId(self.type_aliases.len()); + + self.type_aliases.push(TypeAliasType::new( + type_id, + typ.type_alias_def.name.clone(), + typ.type_alias_def.span, + Type::Error, + vecmap(&typ.type_alias_def.generics, |_| { + let id = TypeVariableId(0); + (id, Shared::new(TypeBinding::Unbound(id))) + }), + )); + + type_id + } + pub fn update_struct(&mut self, type_id: StructId, f: impl FnOnce(&mut StructType)) { let mut value = self.structs.get_mut(&type_id).unwrap().borrow_mut(); f(&mut value); } + pub fn set_type_alias(&mut self, type_id: TypeAliasId, typ: Type, generics: Generics) { + let type_alias_type = &mut self.type_aliases[type_id.0]; + type_alias_type.set_type_and_generics(typ, generics); + } + /// Returns the interned statement corresponding to `stmt_id` pub fn update_statement(&mut self, stmt_id: &StmtId, f: impl FnOnce(&mut HirStatement)) { let def = @@ -506,6 +547,10 @@ impl NodeInterner { self.structs[&id].clone() } + pub fn get_type_alias(&self, id: TypeAliasId) -> &TypeAliasType { + &self.type_aliases[id.0] + } + pub fn get_global(&self, stmt_id: &StmtId) -> Option { self.globals.get(stmt_id).cloned() } diff --git a/crates/noirc_frontend/src/parser/mod.rs b/crates/noirc_frontend/src/parser/mod.rs index 9cf9f1e9869..ad519836b39 100644 --- a/crates/noirc_frontend/src/parser/mod.rs +++ b/crates/noirc_frontend/src/parser/mod.rs @@ -17,8 +17,8 @@ use crate::token::{Keyword, Token}; use crate::{ast::ImportStatement, Expression, NoirStruct}; use crate::{ BlockExpression, ExpressionKind, ForExpression, Ident, IndexExpression, LetStatement, - MethodCallExpression, NoirFunction, NoirTrait, Path, PathKind, Pattern, Recoverable, Statement, - TraitImpl, TypeImpl, UnresolvedType, UseTree, + MethodCallExpression, NoirFunction, NoirTrait, NoirTypeAlias, Path, PathKind, Pattern, + Recoverable, Statement, TraitImpl, TypeImpl, UnresolvedType, UseTree, }; use acvm::FieldElement; @@ -43,6 +43,7 @@ pub(crate) enum TopLevelStatement { Trait(NoirTrait), TraitImpl(TraitImpl), Impl(TypeImpl), + TypeAlias(NoirTypeAlias), SubModule(SubModule), Global(LetStatement), Error, @@ -225,6 +226,7 @@ pub struct ParsedModule { pub traits: Vec, pub trait_impls: Vec, pub impls: Vec, + pub type_aliases: Vec, pub globals: Vec, /// Module declarations like `mod foo;` @@ -264,6 +266,10 @@ impl ParsedModule { self.impls.push(r#impl); } + fn push_type_alias(&mut self, type_alias: NoirTypeAlias) { + self.type_aliases.push(type_alias); + } + fn push_import(&mut self, import_stmt: UseTree) { self.imports.extend(import_stmt.desugar(None)); } @@ -463,6 +469,7 @@ impl std::fmt::Display for TopLevelStatement { TopLevelStatement::TraitImpl(i) => i.fmt(f), TopLevelStatement::Struct(s) => s.fmt(f), TopLevelStatement::Impl(i) => i.fmt(f), + TopLevelStatement::TypeAlias(t) => t.fmt(f), TopLevelStatement::SubModule(s) => s.fmt(f), TopLevelStatement::Global(c) => c.fmt(f), TopLevelStatement::Error => write!(f, "error"), @@ -496,6 +503,10 @@ impl std::fmt::Display for ParsedModule { write!(f, "{impl_}")?; } + for type_alias in &self.type_aliases { + write!(f, "{type_alias}")?; + } + for submodule in &self.submodules { write!(f, "{submodule}")?; } diff --git a/crates/noirc_frontend/src/parser/parser.rs b/crates/noirc_frontend/src/parser/parser.rs index 65446e5d6c6..6445205eae6 100644 --- a/crates/noirc_frontend/src/parser/parser.rs +++ b/crates/noirc_frontend/src/parser/parser.rs @@ -36,8 +36,8 @@ use crate::token::{Attribute, Keyword, Token, TokenKind}; use crate::{ BinaryOp, BinaryOpKind, BlockExpression, CompTime, ConstrainStatement, FunctionDefinition, Ident, IfExpression, InfixExpression, LValue, Lambda, Literal, NoirFunction, NoirStruct, - NoirTrait, Path, PathKind, Pattern, Recoverable, TraitConstraint, TraitImpl, TraitImplItem, - TraitItem, TypeImpl, UnaryOp, UnresolvedTypeExpression, UseTree, UseTreeKind, + NoirTrait, NoirTypeAlias, Path, PathKind, Pattern, Recoverable, TraitConstraint, TraitImpl, + TraitImplItem, TraitItem, TypeImpl, UnaryOp, UnresolvedTypeExpression, UseTree, UseTreeKind, }; use chumsky::prelude::*; @@ -82,6 +82,7 @@ fn module() -> impl NoirParser { TopLevelStatement::Trait(t) => program.push_trait(t), TopLevelStatement::TraitImpl(t) => program.push_trait_impl(t), TopLevelStatement::Impl(i) => program.push_impl(i), + TopLevelStatement::TypeAlias(t) => program.push_type_alias(t), TopLevelStatement::SubModule(s) => program.push_submodule(s), TopLevelStatement::Global(c) => program.push_global(c), TopLevelStatement::Error => (), @@ -108,6 +109,7 @@ fn top_level_statement( trait_definition(), trait_implementation(), implementation(), + type_alias_definition().then_ignore(force(just(Token::Semicolon))), submodule(module_parser.clone()), contract(module_parser), module_declaration().then_ignore(force(just(Token::Semicolon))), @@ -236,6 +238,19 @@ fn struct_definition() -> impl NoirParser { ) } +fn type_alias_definition() -> impl NoirParser { + use self::Keyword::Type; + + let p = ignore_then_commit(keyword(Type), ident()); + let p = then_commit(p, generics()); + let p = then_commit_ignore(p, just(Token::Assign)); + let p = then_commit(p, parse_type()); + + p.map_with_span(|((name, generics), typ), span| { + TopLevelStatement::TypeAlias(NoirTypeAlias { name, generics, typ, span }) + }) +} + fn lambda_return_type() -> impl NoirParser { just(Token::Arrow) .ignore_then(parse_type()) @@ -1917,6 +1932,15 @@ mod test { parse_all_failing(struct_definition(), failing); } + #[test] + fn parse_type_aliases() { + let cases = vec!["type foo = u8", "type bar = String", "type baz = Vec"]; + parse_all(type_alias_definition(), cases); + + let failing = vec!["type = u8", "type foo", "type foo = 1"]; + parse_all_failing(type_alias_definition(), failing); + } + #[test] fn parse_member_access() { let cases = vec!["a.b", "a + b.c", "foo.bar as i32"]; From 3a423686ee657db9cc3cbc6376fe0f7b4316ccc4 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Tue, 1 Aug 2023 21:36:39 +0100 Subject: [PATCH 20/50] chore: Make a more clear error for slices passed to std::println (#2113) * chore: make a more clear error for slices passed to std::println * fix up err message --- .../src/monomorphization/mod.rs | 42 ++++++++++--------- 1 file changed, 22 insertions(+), 20 deletions(-) diff --git a/crates/noirc_frontend/src/monomorphization/mod.rs b/crates/noirc_frontend/src/monomorphization/mod.rs index 963d16a311c..dbe2ee080bf 100644 --- a/crates/noirc_frontend/src/monomorphization/mod.rs +++ b/crates/noirc_frontend/src/monomorphization/mod.rs @@ -727,45 +727,47 @@ impl<'interner> Monomorphizer<'interner> { HirExpression::Ident(ident) => { let typ = self.interner.id_type(ident.id); let typ: Type = typ.follow_bindings(); - match &typ { + let is_fmt_str = match typ { // A format string has many different possible types that need to be handled. // Loop over each element in the format string to fetch each type's relevant metadata Type::FmtString(_, elements) => { - match elements.as_ref() { + match *elements { Type::Tuple(element_types) => { for typ in element_types { - let abi_type = typ.as_abi_type(); - let abi_as_string = serde_json::to_string(&abi_type) - .expect("ICE: expected Abi type to serialize"); - - arguments.push(ast::Expression::Literal(ast::Literal::Str( - abi_as_string, - ))); + Self::append_abi_arg_inner(&typ, arguments); } } _ => unreachable!( "ICE: format string type should be a tuple but got a {elements}" ), } - - // The caller needs information as to whether it is handling a format string or a single type - arguments.push(ast::Expression::Literal(ast::Literal::Bool(true))); + true } _ => { - let abi_type = typ.as_abi_type(); - let abi_as_string = serde_json::to_string(&abi_type) - .expect("ICE: expected Abi type to serialize"); - - arguments.push(ast::Expression::Literal(ast::Literal::Str(abi_as_string))); - // The caller needs information as to whether it is handling a format string or a single type - arguments.push(ast::Expression::Literal(ast::Literal::Bool(false))); + Self::append_abi_arg_inner(&typ, arguments); + false } - } + }; + // The caller needs information as to whether it is handling a format string or a single type + arguments.push(ast::Expression::Literal(ast::Literal::Bool(is_fmt_str))); } _ => unreachable!("logging expr {:?} is not supported", arguments[0]), } } + fn append_abi_arg_inner(typ: &Type, arguments: &mut Vec) { + if let HirType::Array(size, _) = typ { + if let HirType::NotConstant = **size { + unreachable!("println does not support slices. Convert the slice to an array before passing it to println"); + } + } + let abi_type = typ.as_abi_type(); + let abi_as_string = + serde_json::to_string(&abi_type).expect("ICE: expected Abi type to serialize"); + + arguments.push(ast::Expression::Literal(ast::Literal::Str(abi_as_string))); + } + /// Try to evaluate certain builtin functions (currently only 'array_len' and field modulus methods) /// at their call site. /// NOTE: Evaluating at the call site means we cannot track aliased functions. From 940b189d4fd47dad8cc9f2650162da9e99c5024c Mon Sep 17 00:00:00 2001 From: Blaine Bublitz Date: Tue, 1 Aug 2023 14:51:22 -0700 Subject: [PATCH 21/50] feat!: Support workspaces and package selection on every nargo command (#1992) * feat!: Support workspaces and package selection on every nargo command * add package name to contract directory * print package name at the beginning of any stdout messages * Remove circuit_name from compile command and use package name * remove resolve_workspace_in_directory * avoid resolving dependencies as a Workspace struct by always requiring it to be a Package * chore: ensure workspace packages are distinct * Update crates/nargo_cli/src/git.rs * remove proof name argument and use package name, remove stdout printing of proof * fix tests * rename functions to be more descriptive * add issue number to todo --------- Co-authored-by: Tom French Co-authored-by: Tom French <15848336+TomAFrench@users.noreply.github.com> --- Cargo.lock | 2 +- crates/nargo/Cargo.toml | 2 +- crates/{nargo_cli => nargo}/src/constants.rs | 18 +- crates/nargo/src/lib.rs | 4 +- crates/nargo/src/manifest/errors.rs | 26 -- crates/nargo/src/manifest/mod.rs | 147 --------- crates/nargo/src/package.rs | 33 ++ crates/nargo/src/workspace.rs | 74 +++++ crates/nargo_cli/build.rs | 4 +- crates/nargo_cli/src/cli/check_cmd.rs | 86 +++--- .../nargo_cli/src/cli/codegen_verifier_cmd.rs | 97 +++--- crates/nargo_cli/src/cli/compile_cmd.rs | 141 +++++---- crates/nargo_cli/src/cli/execute_cmd.rs | 53 ++-- crates/nargo_cli/src/cli/fs/inputs.rs | 2 +- crates/nargo_cli/src/cli/fs/program.rs | 6 +- crates/nargo_cli/src/cli/fs/proof.rs | 4 +- crates/nargo_cli/src/cli/fs/witness.rs | 3 +- crates/nargo_cli/src/cli/info_cmd.rs | 38 ++- crates/nargo_cli/src/cli/init_cmd.rs | 6 +- crates/nargo_cli/src/cli/prove_cmd.rs | 149 ++++----- crates/nargo_cli/src/cli/test_cmd.rs | 58 ++-- crates/nargo_cli/src/cli/verify_cmd.rs | 106 ++++--- crates/nargo_cli/src/errors.rs | 56 +++- crates/nargo_cli/src/git.rs | 11 +- crates/nargo_cli/src/lib.rs | 60 +++- crates/nargo_cli/src/manifest.rs | 289 +++++++++++++++++- crates/nargo_cli/src/resolver.rs | 265 ---------------- crates/nargo_cli/tests/codegen-verifier.rs | 6 +- crates/nargo_cli/tests/hello_world.rs | 9 +- crates/nargo_cli/tests/test_data/config.toml | 2 +- .../test_data/workspace/crates/a/Prover.toml | 2 + .../test_data/workspace/crates/a/src/main.nr | 10 +- .../test_data/workspace/crates/b/Prover.toml | 2 + .../test_data/workspace/crates/b/src/main.nr | 8 - .../workspace_default_member/a/Prover.toml | 2 + .../workspace_default_member/a/src/main.nr | 10 +- .../workspace_default_member/b/Nargo.toml | 6 + .../workspace_default_member/b/Prover.toml | 3 + .../workspace_default_member/b/src/main.nr | 3 + .../tests/test_data/workspace_fail/Nargo.toml | 2 + .../workspace_fail/crates/a/Nargo.toml | 6 + .../workspace_fail/crates/a/Prover.toml | 3 + .../workspace_fail/crates/a/src/main.nr | 3 + .../workspace_fail/crates/b/Nargo.toml | 6 + .../workspace_fail/crates/b/Prover.toml | 2 + .../workspace_fail/crates/b/src/main.nr | 3 + .../workspace_missing_toml/Nargo.toml | 2 + .../crates/a/Prover.toml | 2 + .../crates/a/src/main.nr | 3 + .../crates/b/Nargo.toml | 6 + .../crates/b/Prover.toml | 2 + .../crates/b/src/main.nr | 3 + crates/noirc_driver/src/lib.rs | 20 +- crates/noirc_frontend/src/graph/mod.rs | 16 +- crates/noirc_frontend/src/hir/mod.rs | 18 +- 55 files changed, 1004 insertions(+), 896 deletions(-) rename crates/{nargo_cli => nargo}/src/constants.rs (55%) delete mode 100644 crates/nargo/src/manifest/errors.rs delete mode 100644 crates/nargo/src/manifest/mod.rs create mode 100644 crates/nargo/src/package.rs delete mode 100644 crates/nargo_cli/src/resolver.rs create mode 100644 crates/nargo_cli/tests/test_data/workspace/crates/a/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace/crates/b/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_default_member/a/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_default_member/b/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_default_member/b/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_default_member/b/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/a/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_fail/crates/b/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/src/main.nr diff --git a/Cargo.lock b/Cargo.lock index 1b7a70b2063..f513136caf3 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1982,12 +1982,12 @@ dependencies = [ "noirc_abi", "noirc_driver", "noirc_errors", + "noirc_frontend", "regex", "rustc_version", "serde", "serde_json", "thiserror", - "toml", ] [[package]] diff --git a/crates/nargo/Cargo.toml b/crates/nargo/Cargo.toml index afbafdff931..3039268281c 100644 --- a/crates/nargo/Cargo.toml +++ b/crates/nargo/Cargo.toml @@ -14,8 +14,8 @@ rustc_version = "0.4.0" acvm.workspace = true noirc_abi.workspace = true noirc_driver.workspace = true +noirc_frontend.workspace = true iter-extended.workspace = true -toml.workspace = true serde.workspace = true serde_json.workspace = true thiserror.workspace = true diff --git a/crates/nargo_cli/src/constants.rs b/crates/nargo/src/constants.rs similarity index 55% rename from crates/nargo_cli/src/constants.rs rename to crates/nargo/src/constants.rs index d3e6b7f28e1..5e448277694 100644 --- a/crates/nargo_cli/src/constants.rs +++ b/crates/nargo/src/constants.rs @@ -1,23 +1,23 @@ // Directories /// The directory for the `nargo contract` command output -pub(crate) const CONTRACT_DIR: &str = "contract"; +pub const CONTRACT_DIR: &str = "contract"; /// The directory to store serialized circuit proofs. -pub(crate) const PROOFS_DIR: &str = "proofs"; +pub const PROOFS_DIR: &str = "proofs"; /// The directory to store Noir source files -pub(crate) const SRC_DIR: &str = "src"; +pub const SRC_DIR: &str = "src"; /// The directory to store circuits' serialized ACIR representations. -pub(crate) const TARGET_DIR: &str = "target"; +pub const TARGET_DIR: &str = "target"; // Files /// The file from which Nargo pulls prover inputs -pub(crate) const PROVER_INPUT_FILE: &str = "Prover"; +pub const PROVER_INPUT_FILE: &str = "Prover"; /// The file from which Nargo pulls verifier inputs -pub(crate) const VERIFIER_INPUT_FILE: &str = "Verifier"; +pub const VERIFIER_INPUT_FILE: &str = "Verifier"; /// The package definition file for a Noir project. -pub(crate) const PKG_FILE: &str = "Nargo.toml"; +pub const PKG_FILE: &str = "Nargo.toml"; // Extensions /// The extension for files containing circuit proofs. -pub(crate) const PROOF_EXT: &str = "proof"; +pub const PROOF_EXT: &str = "proof"; /// The extension for files containing proof witnesses. -pub(crate) const WITNESS_EXT: &str = "tr"; +pub const WITNESS_EXT: &str = "tr"; diff --git a/crates/nargo/src/lib.rs b/crates/nargo/src/lib.rs index 24605de7849..fda02cf98c2 100644 --- a/crates/nargo/src/lib.rs +++ b/crates/nargo/src/lib.rs @@ -8,8 +8,10 @@ //! Noir Package Manager abbreviated is npm, which is already taken. pub mod artifacts; +pub mod constants; mod errors; -pub mod manifest; pub mod ops; +pub mod package; +pub mod workspace; pub use self::errors::NargoError; diff --git a/crates/nargo/src/manifest/errors.rs b/crates/nargo/src/manifest/errors.rs deleted file mode 100644 index 250211de6fb..00000000000 --- a/crates/nargo/src/manifest/errors.rs +++ /dev/null @@ -1,26 +0,0 @@ -use std::path::PathBuf; -use thiserror::Error; - -/// Errors covering situations where a package is either missing or malformed. -#[derive(Debug, Error)] -pub enum InvalidPackageError { - /// Package doesn't have a manifest file - #[error("cannot find a Nargo.toml in {}", .0.display())] - MissingManifestFile(PathBuf), - - /// Package manifest is unreadable. - #[error("Nargo.toml is badly formed, could not parse.\n\n {0}")] - MalformedManifestFile(#[from] toml::de::Error), - - /// Package does not contain Noir source files. - #[error("cannot find src directory in path {}", .0.display())] - NoSourceDir(PathBuf), - - /// Package has neither of `main.nr` and `lib.nr`. - #[error("package must contain either a `lib.nr`(Library) or a `main.nr`(Binary).")] - ContainsZeroCrates, - - /// Package has both a `main.nr` (for binaries) and `lib.nr` (for libraries) - #[error("package cannot contain both a `lib.nr` and a `main.nr`")] - ContainsMultipleCrates, -} diff --git a/crates/nargo/src/manifest/mod.rs b/crates/nargo/src/manifest/mod.rs deleted file mode 100644 index f5a247cf72a..00000000000 --- a/crates/nargo/src/manifest/mod.rs +++ /dev/null @@ -1,147 +0,0 @@ -use serde::Deserialize; -use std::{collections::BTreeMap, path::PathBuf}; - -mod errors; -pub use self::errors::InvalidPackageError; - -#[derive(Debug, Deserialize, Clone)] -pub struct PackageManifest { - pub package: PackageMetadata, - pub dependencies: BTreeMap, -} - -/// Contains all the information about a package, as loaded from a `Nargo.toml`. -/// Represents a manifest, which can be either a package manifest or a workspace manifest. -#[derive(Debug, Deserialize, Clone)] -#[serde(untagged)] -pub enum Manifest { - /// Represents a package manifest. - Package(PackageManifest), - /// Represents a workspace manifest. - Workspace(Workspace), -} - -impl Manifest { - pub fn from_toml_str(toml_as_string: &str) -> Result { - let manifest = toml::from_str(toml_as_string)?; - Ok(manifest) - } - - pub fn to_package(self) -> Option { - match self { - Self::Package(v) => Some(v), - _ => None, - } - } -} - -impl PackageManifest { - /// Returns whether the package has a local dependency. - // Local paths are usually relative and are discouraged when sharing libraries - // It is better to separate these into different packages. - pub fn has_local_dependency(&self) -> bool { - self.dependencies.values().any(|dep| matches!(dep, Dependency::Path { .. })) - } -} - -/// Configuration of a workspace in a manifest. -/// Indicates that `[workspace]` was present and the members were specified as well. -#[derive(Debug, Deserialize, Clone)] -pub struct Workspace { - #[serde(rename = "workspace")] - pub config: WorkspaceConfig, -} - -#[derive(Default, Debug, Deserialize, Clone)] -#[serde(rename_all = "kebab-case")] -pub struct WorkspaceConfig { - /// List of members in this workspace. - pub members: Vec, - /// Specifies the default crate to interact with in the context (similarly to how we have nargo as the default crate in this repository). - pub default_member: Option, -} - -#[allow(dead_code)] -#[derive(Default, Debug, Deserialize, Clone)] -pub struct PackageMetadata { - #[serde(default = "panic_missing_name")] - pub name: String, - description: Option, - authors: Vec, - // If not compiler version is supplied, the latest is used - // For now, we state that all packages must be compiled under the same - // compiler version. - // We also state that ACIR and the compiler will upgrade in lockstep. - // so you will not need to supply an ACIR and compiler version - compiler_version: Option, - backend: Option, - license: Option, -} - -// TODO: Remove this after a couple of breaking releases (added in 0.10.0) -fn panic_missing_name() -> String { - panic!( - r#" - -Failed to parse `Nargo.toml`. - -`Nargo.toml` now requires a "name" field for Noir packages. - -```toml -[package] -name = "package_name" -``` - -Modify your `Nargo.toml` similarly to above and rerun the command. - -"# - ) -} - -#[derive(Debug, Deserialize, Clone)] -#[serde(untagged)] -/// Enum representing the different types of ways to -/// supply a source for the dependency -pub enum Dependency { - Github { git: String, tag: String }, - Path { path: String }, -} - -#[test] -fn parse_standard_toml() { - let src = r#" - - [package] - name = "test" - authors = ["kev", "foo"] - compiler_version = "0.1" - - [dependencies] - rand = { tag = "next", git = "https://github.com/rust-lang-nursery/rand"} - cool = { tag = "next", git = "https://github.com/rust-lang-nursery/rand"} - hello = {path = "./noir_driver"} - "#; - - assert!(Manifest::from_toml_str(src).is_ok()); -} - -#[test] -fn parse_workspace_toml() { - let src = r#" - [workspace] - members = ["a", "b"] - "#; - - assert!(Manifest::from_toml_str(src).is_ok()); -} - -#[test] -fn parse_workspace_default_member_toml() { - let src = r#" - [workspace] - members = ["a", "b"] - default-member = "a" - "#; - - assert!(Manifest::from_toml_str(src).is_ok()); -} diff --git a/crates/nargo/src/package.rs b/crates/nargo/src/package.rs new file mode 100644 index 00000000000..20c662b69f4 --- /dev/null +++ b/crates/nargo/src/package.rs @@ -0,0 +1,33 @@ +use std::{collections::BTreeMap, path::PathBuf}; + +use noirc_frontend::graph::{CrateName, CrateType}; + +use crate::constants::{PROVER_INPUT_FILE, VERIFIER_INPUT_FILE}; + +#[derive(Clone)] +pub enum Dependency { + Local { package: Package }, + Remote { package: Package }, +} + +#[derive(Clone)] +pub struct Package { + pub root_dir: PathBuf, + pub crate_type: CrateType, + pub entry_path: PathBuf, + pub name: CrateName, + pub dependencies: BTreeMap, +} + +impl Package { + pub fn prover_input_path(&self) -> PathBuf { + // TODO: This should be configurable, such as if we are looking for .json or .toml or custom paths + // For now it is hard-coded to be toml. + self.root_dir.join(format!("{PROVER_INPUT_FILE}.toml")) + } + pub fn verifier_input_path(&self) -> PathBuf { + // TODO: This should be configurable, such as if we are looking for .json or .toml or custom paths + // For now it is hard-coded to be toml. + self.root_dir.join(format!("{VERIFIER_INPUT_FILE}.toml")) + } +} diff --git a/crates/nargo/src/workspace.rs b/crates/nargo/src/workspace.rs index 0954b4eb143..5df13350683 100644 --- a/crates/nargo/src/workspace.rs +++ b/crates/nargo/src/workspace.rs @@ -2,3 +2,77 @@ // Then we use workspace to allow more than one. In the future, do not allow there to be // both a binary and a library. // - library will be default + +use std::{ + iter::{once, Once}, + path::PathBuf, + slice, +}; + +use crate::{ + constants::{CONTRACT_DIR, PROOFS_DIR, TARGET_DIR}, + package::Package, +}; + +#[derive(Clone)] +pub struct Workspace { + pub root_dir: PathBuf, + pub members: Vec, + // If `Some()`, the `selected_package_index` is used to select the only `Package` when iterating a Workspace + pub selected_package_index: Option, +} + +impl Workspace { + pub fn package_build_path(&self, package: &Package) -> PathBuf { + let name: String = package.name.clone().into(); + self.target_directory_path().join(name) + } + + pub fn contracts_directory_path(&self, package: &Package) -> PathBuf { + let name: String = package.name.clone().into(); + self.root_dir.join(CONTRACT_DIR).join(name) + } + + pub fn proofs_directory_path(&self) -> PathBuf { + self.root_dir.join(PROOFS_DIR) + } + + pub fn target_directory_path(&self) -> PathBuf { + self.root_dir.join(TARGET_DIR) + } +} + +pub enum IntoIter<'a, T> { + Only(Once<&'a T>), + All(slice::Iter<'a, T>), +} + +impl<'a> IntoIterator for &'a Workspace { + type Item = &'a Package; + type IntoIter = IntoIter<'a, Package>; + + fn into_iter(self) -> Self::IntoIter { + if let Some(index) = self.selected_package_index { + // Precondition: The selected_package_index was verified to be in-bounds before constructing workspace + let member = self + .members + .get(index) + .expect("Workspace constructed with invalid selected_package_index"); + + IntoIter::Only(once(member)) + } else { + IntoIter::All(self.members.iter()) + } + } +} + +impl<'a> Iterator for IntoIter<'a, Package> { + type Item = &'a Package; + + fn next(&mut self) -> Option { + match self { + Self::Only(iter) => iter.next(), + Self::All(iter) => iter.next(), + } + } +} diff --git a/crates/nargo_cli/build.rs b/crates/nargo_cli/build.rs index d889ba6856c..f3493148a7f 100644 --- a/crates/nargo_cli/build.rs +++ b/crates/nargo_cli/build.rs @@ -84,7 +84,6 @@ fn generate_tests(test_file: &mut File) { if config_data["exclude"].contains(&test_name) { "#[ignore]" } else { "" }; let should_fail = config_data["fail"].contains(&test_name); - let is_workspace = test_dir.to_str().map_or(false, |s| s.contains("workspace")); write!( test_file, @@ -96,8 +95,7 @@ fn execute_{test_sub_dir}_{test_name}() {{ let mut cmd = Command::cargo_bin("nargo").unwrap(); cmd.arg("--program-dir").arg(test_program_dir); - cmd.arg(if {is_workspace} {{ "test" }} else {{ "execute" }}); - + cmd.arg("execute"); if {should_fail} {{ cmd.assert().failure(); diff --git a/crates/nargo_cli/src/cli/check_cmd.rs b/crates/nargo_cli/src/cli/check_cmd.rs index 9a0a2f77e7c..8f2e23ed750 100644 --- a/crates/nargo_cli/src/cli/check_cmd.rs +++ b/crates/nargo_cli/src/cli/check_cmd.rs @@ -1,53 +1,58 @@ -use crate::{errors::CliError, resolver::resolve_root_manifest}; +use crate::{ + errors::CliError, find_package_manifest, manifest::resolve_workspace_from_toml, prepare_package, +}; use acvm::Backend; use clap::Args; use iter_extended::btree_map; +use nargo::package::Package; use noirc_abi::{AbiParameter, AbiType, MAIN_RETURN_NAME}; use noirc_driver::{check_crate, compute_function_signature, CompileOptions}; use noirc_errors::reporter::ReportedErrors; -use noirc_frontend::{graph::CrateId, hir::Context}; -use std::path::{Path, PathBuf}; +use noirc_frontend::{ + graph::{CrateId, CrateName}, + hir::Context, +}; use super::fs::write_to_file; use super::NargoConfig; -use crate::constants::{PROVER_INPUT_FILE, VERIFIER_INPUT_FILE}; /// Checks the constraint system for errors #[derive(Debug, Clone, Args)] pub(crate) struct CheckCommand { + /// The name of the package to check + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } pub(crate) fn run( - backend: &B, + _backend: &B, args: CheckCommand, config: NargoConfig, ) -> Result<(), CliError> { - check_from_path(backend, &config.program_dir, &args.compile_options)?; - println!("Constraint system successfully built!"); + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + + for package in &workspace { + check_package(package, &args.compile_options)?; + println!("[{}] Constraint system successfully built!", package.name); + } Ok(()) } -fn check_from_path( - // Backend isn't used but keeping it in the signature allows for better type inference - // TODO: This function doesn't need to exist but requires a little more refactoring - _backend: &B, - program_dir: &Path, +fn check_package( + package: &Package, compile_options: &CompileOptions, -) -> Result<(), CliError> { - let (mut context, crate_id) = resolve_root_manifest(program_dir, None)?; +) -> Result<(), ReportedErrors> { + let (mut context, crate_id) = prepare_package(package); check_crate_and_report_errors(&mut context, crate_id, compile_options.deny_warnings)?; // XXX: We can have a --overwrite flag to determine if you want to overwrite the Prover/Verifier.toml files if let Some((parameters, return_type)) = compute_function_signature(&context, &crate_id) { - // XXX: The root config should return an enum to determine if we are looking for .json or .toml - // For now it is hard-coded to be toml. - // - // Check for input.toml and verifier.toml - let path_to_root = PathBuf::from(program_dir); - let path_to_prover_input = path_to_root.join(format!("{PROVER_INPUT_FILE}.toml")); - let path_to_verifier_input = path_to_root.join(format!("{VERIFIER_INPUT_FILE}.toml")); + let path_to_prover_input = package.prover_input_path(); + let path_to_verifier_input = package.verifier_input_path(); // If they are not available, then create them and populate them based on the ABI if !path_to_prover_input.exists() { @@ -108,6 +113,8 @@ mod tests { use noirc_abi::{AbiParameter, AbiType, AbiVisibility, Sign}; use noirc_driver::CompileOptions; + use crate::{find_package_manifest, manifest::resolve_workspace_from_toml}; + use super::create_input_toml_template; const TEST_DATA_DIR: &str = "tests/target_tests_data"; @@ -157,16 +164,15 @@ d2 = ["", "", ""] let pass_dir = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join(format!("{TEST_DATA_DIR}/pass")); - let backend = crate::backends::ConcreteBackend::default(); let config = CompileOptions::default(); let paths = std::fs::read_dir(pass_dir).unwrap(); for path in paths.flatten() { let path = path.path(); - assert!( - super::check_from_path(&backend, &path, &config).is_ok(), - "path: {}", - path.display() - ); + let toml_path = find_package_manifest(&path).unwrap(); + let workspace = resolve_workspace_from_toml(&toml_path, None).unwrap(); + for package in &workspace { + assert!(super::check_package(package, &config).is_ok(), "path: {}", path.display()); + } } } @@ -176,16 +182,19 @@ d2 = ["", "", ""] let fail_dir = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join(format!("{TEST_DATA_DIR}/fail")); - let backend = crate::backends::ConcreteBackend::default(); let config = CompileOptions::default(); let paths = std::fs::read_dir(fail_dir).unwrap(); for path in paths.flatten() { let path = path.path(); - assert!( - super::check_from_path(&backend, &path, &config).is_err(), - "path: {}", - path.display() - ); + let toml_path = find_package_manifest(&path).unwrap(); + let workspace = resolve_workspace_from_toml(&toml_path, None).unwrap(); + for package in &workspace { + assert!( + super::check_package(package, &config).is_err(), + "path: {}", + path.display() + ); + } } } @@ -194,17 +203,16 @@ d2 = ["", "", ""] let pass_dir = PathBuf::from(env!("CARGO_MANIFEST_DIR")) .join(format!("{TEST_DATA_DIR}/pass_dev_mode")); - let backend = crate::backends::ConcreteBackend::default(); let config = CompileOptions { deny_warnings: false, ..Default::default() }; let paths = std::fs::read_dir(pass_dir).unwrap(); for path in paths.flatten() { let path = path.path(); - assert!( - super::check_from_path(&backend, &path, &config).is_ok(), - "path: {}", - path.display() - ); + let toml_path = find_package_manifest(&path).unwrap(); + let workspace = resolve_workspace_from_toml(&toml_path, None).unwrap(); + for package in &workspace { + assert!(super::check_package(package, &config).is_ok(), "path: {}", path.display()); + } } } } diff --git a/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs b/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs index cedf558bcb8..0c01f8d5dc8 100644 --- a/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs +++ b/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs @@ -1,3 +1,5 @@ +use std::path::PathBuf; + use super::fs::{ common_reference_string::{ read_cached_common_reference_string, update_common_reference_string, @@ -8,20 +10,23 @@ use super::fs::{ write_to_file, }; use super::NargoConfig; -use crate::{ - cli::compile_cmd::compile_circuit, constants::CONTRACT_DIR, constants::TARGET_DIR, - errors::CliError, -}; +use crate::{cli::compile_cmd::compile_circuit, errors::CliError}; +use crate::{find_package_manifest, manifest::resolve_workspace_from_toml, prepare_package}; use acvm::Backend; use clap::Args; -use nargo::ops::{codegen_verifier, preprocess_program}; +use nargo::{ + ops::{codegen_verifier, preprocess_program}, + package::Package, +}; use noirc_driver::CompileOptions; +use noirc_frontend::graph::CrateName; /// Generates a Solidity verifier smart contract for the program #[derive(Debug, Clone, Args)] pub(crate) struct CodegenVerifierCommand { - /// The name of the circuit build files (ACIR, proving and verification keys) - circuit_name: Option, + /// The name of the package to codegen + #[clap(long)] + package: Option, #[clap(flatten)] compile_options: CompileOptions, @@ -32,34 +37,52 @@ pub(crate) fn run( args: CodegenVerifierCommand, config: NargoConfig, ) -> Result<(), CliError> { - // TODO(#1201): Should this be a utility function? - let circuit_build_path = args - .circuit_name - .map(|circuit_name| config.program_dir.join(TARGET_DIR).join(circuit_name)); + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; - let common_reference_string = read_cached_common_reference_string(); + for package in &workspace { + let circuit_build_path = workspace.package_build_path(package); + + let smart_contract_string = smart_contract_for_package( + backend, + package, + circuit_build_path, + &args.compile_options, + )?; + + let contract_dir = workspace.contracts_directory_path(package); + create_named_dir(&contract_dir, "contract"); + let contract_path = contract_dir.join("plonk_vk").with_extension("sol"); + + let path = write_to_file(smart_contract_string.as_bytes(), &contract_path); + println!("[{}] Contract successfully created and located at {path}", package.name); + } - let (common_reference_string, preprocessed_program) = match circuit_build_path { - Some(circuit_build_path) => { - let program = read_program_from_file(circuit_build_path)?; - let common_reference_string = update_common_reference_string( - backend, - &common_reference_string, - &program.bytecode, - ) - .map_err(CliError::CommonReferenceStringError)?; - (common_reference_string, program) - } - None => { - let (program, _) = - compile_circuit(backend, None, config.program_dir.as_ref(), &args.compile_options)?; - let common_reference_string = - update_common_reference_string(backend, &common_reference_string, &program.circuit) - .map_err(CliError::CommonReferenceStringError)?; - let (program, _) = preprocess_program(backend, true, &common_reference_string, program) - .map_err(CliError::ProofSystemCompilerError)?; - (common_reference_string, program) - } + Ok(()) +} + +fn smart_contract_for_package( + backend: &B, + package: &Package, + circuit_build_path: PathBuf, + compile_options: &CompileOptions, +) -> Result> { + let common_reference_string = read_cached_common_reference_string(); + let (common_reference_string, preprocessed_program) = if circuit_build_path.exists() { + let program = read_program_from_file(circuit_build_path)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.bytecode) + .map_err(CliError::CommonReferenceStringError)?; + (common_reference_string, program) + } else { + let (mut context, crate_id) = prepare_package(package); + let program = compile_circuit(backend, &mut context, crate_id, compile_options)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.circuit) + .map_err(CliError::CommonReferenceStringError)?; + let (program, _) = preprocess_program(backend, true, &common_reference_string, program) + .map_err(CliError::ProofSystemCompilerError)?; + (common_reference_string, program) }; let verification_key = preprocessed_program @@ -75,11 +98,5 @@ pub(crate) fn run( write_cached_common_reference_string(&common_reference_string); - let contract_dir = config.program_dir.join(CONTRACT_DIR); - create_named_dir(&contract_dir, "contract"); - let contract_path = contract_dir.join("plonk_vk").with_extension("sol"); - - let path = write_to_file(smart_contract_string.as_bytes(), &contract_path); - println!("Contract successfully created and located at {path}"); - Ok(()) + Ok(smart_contract_string) } diff --git a/crates/nargo_cli/src/cli/compile_cmd.rs b/crates/nargo_cli/src/cli/compile_cmd.rs index fbaecb606a1..2d59667e7ff 100644 --- a/crates/nargo_cli/src/cli/compile_cmd.rs +++ b/crates/nargo_cli/src/cli/compile_cmd.rs @@ -7,14 +7,16 @@ use noirc_driver::{ compile_contracts, compile_main, CompileOptions, CompiledProgram, ErrorsAndWarnings, Warnings, }; use noirc_errors::reporter::ReportedErrors; +use noirc_frontend::graph::{CrateId, CrateName}; use noirc_frontend::hir::Context; -use std::path::Path; use clap::Args; use nargo::ops::{preprocess_contract_function, preprocess_program}; -use crate::{constants::TARGET_DIR, errors::CliError, resolver::resolve_root_manifest}; +use crate::errors::CliError; +use crate::manifest::resolve_workspace_from_toml; +use crate::{find_package_manifest, prepare_package}; use super::fs::{ common_reference_string::{ @@ -31,9 +33,6 @@ const BACKEND_IDENTIFIER: &str = "acvm-backend-barretenberg"; /// Compile the program and its secret execution trace into ACIR format #[derive(Debug, Clone, Args)] pub(crate) struct CompileCommand { - /// The name of the ACIR file - circuit_name: String, - /// Include Proving and Verification keys in the build artifacts. #[arg(long)] include_keys: bool, @@ -42,6 +41,10 @@ pub(crate) struct CompileCommand { #[arg(short, long)] contracts: bool, + /// The name of the package to compile + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } @@ -51,66 +54,72 @@ pub(crate) fn run( args: CompileCommand, config: NargoConfig, ) -> Result<(), CliError> { - let circuit_dir = config.program_dir.join(TARGET_DIR); + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + let circuit_dir = workspace.target_directory_path(); let mut common_reference_string = read_cached_common_reference_string(); // If contracts is set we're compiling every function in a 'contract' rather than just 'main'. if args.contracts { - let (mut context, crate_id) = resolve_root_manifest(&config.program_dir, None)?; - - let result = compile_contracts(&mut context, crate_id, &args.compile_options); - let contracts = report_errors(result, &context, args.compile_options.deny_warnings)?; - - // TODO(#1389): I wonder if it is incorrect for nargo-core to know anything about contracts. - // As can be seen here, It seems like a leaky abstraction where ContractFunctions (essentially CompiledPrograms) - // are compiled via nargo-core and then the PreprocessedContract is constructed here. - // This is due to EACH function needing it's own CRS, PKey, and VKey from the backend. - let preprocessed_contracts: Result, CliError> = - try_vecmap(contracts, |contract| { - let preprocessed_contract_functions = - try_vecmap(contract.functions, |mut func| { - func.bytecode = optimize_circuit(backend, func.bytecode)?.0; - common_reference_string = update_common_reference_string( - backend, - &common_reference_string, - &func.bytecode, - ) - .map_err(CliError::CommonReferenceStringError)?; - - preprocess_contract_function( - backend, - args.include_keys, - &common_reference_string, - func, - ) - .map_err(CliError::ProofSystemCompilerError) - })?; - - Ok(PreprocessedContract { - name: contract.name, - backend: String::from(BACKEND_IDENTIFIER), - functions: preprocessed_contract_functions, - }) - }); - for contract in preprocessed_contracts? { - save_contract_to_file( - &contract, - &format!("{}-{}", &args.circuit_name, contract.name), - &circuit_dir, - ); + for package in &workspace { + let (mut context, crate_id) = prepare_package(package); + let result = compile_contracts(&mut context, crate_id, &args.compile_options); + let contracts = report_errors(result, &context, args.compile_options.deny_warnings)?; + + // TODO(#1389): I wonder if it is incorrect for nargo-core to know anything about contracts. + // As can be seen here, It seems like a leaky abstraction where ContractFunctions (essentially CompiledPrograms) + // are compiled via nargo-core and then the PreprocessedContract is constructed here. + // This is due to EACH function needing it's own CRS, PKey, and VKey from the backend. + let preprocessed_contracts: Result, CliError> = + try_vecmap(contracts, |contract| { + let preprocessed_contract_functions = + try_vecmap(contract.functions, |mut func| { + func.bytecode = optimize_circuit(backend, func.bytecode)?.0; + common_reference_string = update_common_reference_string( + backend, + &common_reference_string, + &func.bytecode, + ) + .map_err(CliError::CommonReferenceStringError)?; + + preprocess_contract_function( + backend, + args.include_keys, + &common_reference_string, + func, + ) + .map_err(CliError::ProofSystemCompilerError) + })?; + + Ok(PreprocessedContract { + name: contract.name, + backend: String::from(BACKEND_IDENTIFIER), + functions: preprocessed_contract_functions, + }) + }); + for contract in preprocessed_contracts? { + save_contract_to_file( + &contract, + &format!("{}-{}", package.name, contract.name), + &circuit_dir, + ); + } } } else { - let (program, _) = - compile_circuit(backend, None, &config.program_dir, &args.compile_options)?; - common_reference_string = - update_common_reference_string(backend, &common_reference_string, &program.circuit) - .map_err(CliError::CommonReferenceStringError)?; - - let (preprocessed_program, _) = - preprocess_program(backend, args.include_keys, &common_reference_string, program) - .map_err(CliError::ProofSystemCompilerError)?; - save_program_to_file(&preprocessed_program, &args.circuit_name, circuit_dir); + for package in &workspace { + let (mut context, crate_id) = prepare_package(package); + let program = compile_circuit(backend, &mut context, crate_id, &args.compile_options)?; + + common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.circuit) + .map_err(CliError::CommonReferenceStringError)?; + + let (preprocessed_program, _) = + preprocess_program(backend, args.include_keys, &common_reference_string, program) + .map_err(CliError::ProofSystemCompilerError)?; + save_program_to_file(&preprocessed_program, &package.name, &circuit_dir); + } } write_cached_common_reference_string(&common_reference_string); @@ -120,18 +129,18 @@ pub(crate) fn run( pub(crate) fn compile_circuit( backend: &B, - package: Option, - program_dir: &Path, + context: &mut Context, + crate_id: CrateId, compile_options: &CompileOptions, -) -> Result<(CompiledProgram, Context), CliError> { - let (mut context, crate_id) = resolve_root_manifest(program_dir, package)?; - let result = compile_main(&mut context, crate_id, compile_options); - let mut program = report_errors(result, &context, compile_options.deny_warnings)?; - +) -> Result { + let result = compile_main(context, crate_id, compile_options); + let mut program = report_errors(result, context, compile_options.deny_warnings)?; // Apply backend specific optimizations. let (optimized_circuit, opcode_labels) = optimize_circuit(backend, program.circuit) .expect("Backend does not support an opcode that is in the IR"); + // TODO(#2110): Why does this set `program.circuit` to `optimized_circuit` instead of the function taking ownership + // and requiring we use `optimized_circuit` everywhere after program.circuit = optimized_circuit; let opcode_ids = vecmap(opcode_labels, |label| match label { OpcodeLabel::Unresolved => { @@ -141,7 +150,7 @@ pub(crate) fn compile_circuit( }); program.debug.update_acir(opcode_ids); - Ok((program, context)) + Ok(program) } pub(super) fn optimize_circuit( diff --git a/crates/nargo_cli/src/cli/execute_cmd.rs b/crates/nargo_cli/src/cli/execute_cmd.rs index eaaea6d4ab3..ca5c18585ab 100644 --- a/crates/nargo_cli/src/cli/execute_cmd.rs +++ b/crates/nargo_cli/src/cli/execute_cmd.rs @@ -1,23 +1,23 @@ -use std::path::Path; - use acvm::acir::circuit::OpcodeLabel; use acvm::acir::{circuit::Circuit, native_types::WitnessMap}; use acvm::Backend; use clap::Args; +use nargo::constants::PROVER_INPUT_FILE; +use nargo::package::Package; use nargo::NargoError; use noirc_abi::input_parser::{Format, InputValue}; use noirc_abi::{Abi, InputMap}; use noirc_driver::{CompileOptions, CompiledProgram}; use noirc_errors::{debug_info::DebugInfo, CustomDiagnostic}; +use noirc_frontend::graph::CrateName; use noirc_frontend::hir::Context; +use super::compile_cmd::compile_circuit; use super::fs::{inputs::read_inputs_from_file, witness::save_witness_to_dir}; use super::NargoConfig; -use crate::{ - cli::compile_cmd::compile_circuit, - constants::{PROVER_INPUT_FILE, TARGET_DIR}, - errors::CliError, -}; +use crate::errors::CliError; +use crate::manifest::resolve_workspace_from_toml; +use crate::{find_package_manifest, prepare_package}; /// Executes a circuit to calculate its return value #[derive(Debug, Clone, Args)] @@ -29,6 +29,10 @@ pub(crate) struct ExecuteCommand { #[clap(long, short, default_value = PROVER_INPUT_FILE)] prover_name: String, + /// The name of the package to execute + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } @@ -38,35 +42,40 @@ pub(crate) fn run( args: ExecuteCommand, config: NargoConfig, ) -> Result<(), CliError> { - let (return_value, solved_witness) = - execute_with_path(backend, &config.program_dir, args.prover_name, &args.compile_options)?; + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + let witness_dir = &workspace.target_directory_path(); - println!("Circuit witness successfully solved"); - if let Some(return_value) = return_value { - println!("Circuit output: {return_value:?}"); - } - if let Some(witness_name) = args.witness_name { - let witness_dir = config.program_dir.join(TARGET_DIR); + for package in &workspace { + let (return_value, solved_witness) = + execute_package(backend, package, &args.prover_name, &args.compile_options)?; - let witness_path = save_witness_to_dir(solved_witness, &witness_name, witness_dir)?; + println!("[{}] Circuit witness successfully solved", package.name); + if let Some(return_value) = return_value { + println!("[{}] Circuit output: {return_value:?}", package.name); + } + if let Some(witness_name) = &args.witness_name { + let witness_path = save_witness_to_dir(solved_witness, witness_name, witness_dir)?; - println!("Witness saved to {}", witness_path.display()); + println!("[{}] Witness saved to {}", package.name, witness_path.display()); + } } Ok(()) } -fn execute_with_path( +fn execute_package( backend: &B, - program_dir: &Path, - prover_name: String, + package: &Package, + prover_name: &str, compile_options: &CompileOptions, ) -> Result<(Option, WitnessMap), CliError> { - let (compiled_program, context) = compile_circuit(backend, None, program_dir, compile_options)?; + let (mut context, crate_id) = prepare_package(package); + let compiled_program = compile_circuit(backend, &mut context, crate_id, compile_options)?; let CompiledProgram { abi, circuit, debug } = compiled_program; // Parse the initial witness values from Prover.toml let (inputs_map, _) = - read_inputs_from_file(program_dir, prover_name.as_str(), Format::Toml, &abi)?; + read_inputs_from_file(&package.root_dir, prover_name, Format::Toml, &abi)?; let solved_witness = execute_program(backend, circuit, &abi, &inputs_map, Some((debug, context)))?; diff --git a/crates/nargo_cli/src/cli/fs/inputs.rs b/crates/nargo_cli/src/cli/fs/inputs.rs index bd55e4b0abd..fd2afdefa12 100644 --- a/crates/nargo_cli/src/cli/fs/inputs.rs +++ b/crates/nargo_cli/src/cli/fs/inputs.rs @@ -70,6 +70,7 @@ mod tests { use std::{collections::BTreeMap, vec}; use acvm::FieldElement; + use nargo::constants::VERIFIER_INPUT_FILE; use noirc_abi::{ input_parser::{Format, InputValue}, Abi, AbiParameter, AbiType, AbiVisibility, @@ -77,7 +78,6 @@ mod tests { use tempdir::TempDir; use super::{read_inputs_from_file, write_inputs_to_file}; - use crate::constants::VERIFIER_INPUT_FILE; #[test] fn write_and_read_recovers_inputs_and_return_value() { diff --git a/crates/nargo_cli/src/cli/fs/program.rs b/crates/nargo_cli/src/cli/fs/program.rs index 871a6023837..311923a6686 100644 --- a/crates/nargo_cli/src/cli/fs/program.rs +++ b/crates/nargo_cli/src/cli/fs/program.rs @@ -1,6 +1,7 @@ use std::path::{Path, PathBuf}; use nargo::artifacts::{contract::PreprocessedContract, program::PreprocessedProgram}; +use noirc_frontend::graph::CrateName; use crate::errors::FilesystemError; @@ -8,10 +9,11 @@ use super::{create_named_dir, write_to_file}; pub(crate) fn save_program_to_file>( compiled_program: &PreprocessedProgram, - circuit_name: &str, + crate_name: &CrateName, circuit_dir: P, ) -> PathBuf { - save_build_artifact_to_file(compiled_program, circuit_name, circuit_dir) + let circuit_name: String = crate_name.into(); + save_build_artifact_to_file(compiled_program, &circuit_name, circuit_dir) } pub(crate) fn save_contract_to_file>( compiled_contract: &PreprocessedContract, diff --git a/crates/nargo_cli/src/cli/fs/proof.rs b/crates/nargo_cli/src/cli/fs/proof.rs index 3a54aa908f8..d2b3050708b 100644 --- a/crates/nargo_cli/src/cli/fs/proof.rs +++ b/crates/nargo_cli/src/cli/fs/proof.rs @@ -1,6 +1,8 @@ use std::path::{Path, PathBuf}; -use crate::{constants::PROOF_EXT, errors::FilesystemError}; +use nargo::constants::PROOF_EXT; + +use crate::errors::FilesystemError; use super::{create_named_dir, write_to_file}; diff --git a/crates/nargo_cli/src/cli/fs/witness.rs b/crates/nargo_cli/src/cli/fs/witness.rs index 7ecafb1615b..edfb1aa63d6 100644 --- a/crates/nargo_cli/src/cli/fs/witness.rs +++ b/crates/nargo_cli/src/cli/fs/witness.rs @@ -1,9 +1,10 @@ use std::path::{Path, PathBuf}; use acvm::acir::native_types::WitnessMap; +use nargo::constants::WITNESS_EXT; use super::{create_named_dir, write_to_file}; -use crate::{constants::WITNESS_EXT, errors::FilesystemError}; +use crate::errors::FilesystemError; pub(crate) fn save_witness_to_dir>( witnesses: WitnessMap, diff --git a/crates/nargo_cli/src/cli/info_cmd.rs b/crates/nargo_cli/src/cli/info_cmd.rs index 7ad0a2caf8c..12a70f7b13e 100644 --- a/crates/nargo_cli/src/cli/info_cmd.rs +++ b/crates/nargo_cli/src/cli/info_cmd.rs @@ -1,19 +1,26 @@ use acvm::Backend; use clap::Args; +use nargo::package::Package; use noirc_driver::CompileOptions; -use std::path::Path; +use noirc_frontend::graph::CrateName; -use crate::cli::compile_cmd::compile_circuit; -use crate::errors::CliError; +use crate::{ + cli::compile_cmd::compile_circuit, errors::CliError, find_package_manifest, + manifest::resolve_workspace_from_toml, prepare_package, +}; use super::NargoConfig; -/// Provides detailed informaton on a circuit +/// Provides detailed information on a circuit /// Current information provided: /// 1. The number of ACIR opcodes /// 2. Counts the final number gates in the circuit used by a backend #[derive(Debug, Clone, Args)] pub(crate) struct InfoCommand { + /// The name of the package to detail + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } @@ -23,20 +30,29 @@ pub(crate) fn run( args: InfoCommand, config: NargoConfig, ) -> Result<(), CliError> { - count_opcodes_and_gates_with_path(backend, config.program_dir, &args.compile_options) + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + + for package in &workspace { + count_opcodes_and_gates_in_package(backend, package, &args.compile_options)?; + } + + Ok(()) } -fn count_opcodes_and_gates_with_path>( +fn count_opcodes_and_gates_in_package( backend: &B, - program_dir: P, + package: &Package, compile_options: &CompileOptions, ) -> Result<(), CliError> { - let (compiled_program, _) = - compile_circuit(backend, None, program_dir.as_ref(), compile_options)?; + let (mut context, crate_id) = prepare_package(package); + let compiled_program = compile_circuit(backend, &mut context, crate_id, compile_options)?; + let num_opcodes = compiled_program.circuit.opcodes.len(); println!( - "Total ACIR opcodes generated for language {:?}: {}", + "[{}] Total ACIR opcodes generated for language {:?}: {}", + package.name, backend.np_language(), num_opcodes ); @@ -44,7 +60,7 @@ fn count_opcodes_and_gates_with_path>( let exact_circuit_size = backend .get_exact_circuit_size(&compiled_program.circuit) .map_err(CliError::ProofSystemCompilerError)?; - println!("Backend circuit size: {exact_circuit_size}"); + println!("[{}] Backend circuit size: {exact_circuit_size}", package.name); Ok(()) } diff --git a/crates/nargo_cli/src/cli/init_cmd.rs b/crates/nargo_cli/src/cli/init_cmd.rs index 77613611343..576690b7fab 100644 --- a/crates/nargo_cli/src/cli/init_cmd.rs +++ b/crates/nargo_cli/src/cli/init_cmd.rs @@ -1,12 +1,10 @@ -use crate::{ - constants::{PKG_FILE, SRC_DIR}, - errors::CliError, -}; +use crate::errors::CliError; use super::fs::{create_named_dir, write_to_file}; use super::{NargoConfig, CARGO_PKG_VERSION}; use acvm::Backend; use clap::Args; +use nargo::constants::{PKG_FILE, SRC_DIR}; use std::path::PathBuf; /// Create a Noir project in the current directory. diff --git a/crates/nargo_cli/src/cli/prove_cmd.rs b/crates/nargo_cli/src/cli/prove_cmd.rs index 92e9599cd8b..cdf83f9759b 100644 --- a/crates/nargo_cli/src/cli/prove_cmd.rs +++ b/crates/nargo_cli/src/cli/prove_cmd.rs @@ -3,38 +3,31 @@ use std::path::{Path, PathBuf}; use acvm::Backend; use clap::Args; use nargo::artifacts::program::PreprocessedProgram; +use nargo::constants::{PROVER_INPUT_FILE, VERIFIER_INPUT_FILE}; use nargo::ops::{preprocess_program, prove_execution, verify_proof}; +use nargo::package::Package; use noirc_abi::input_parser::Format; use noirc_driver::CompileOptions; +use noirc_frontend::graph::CrateName; -use super::NargoConfig; -use super::{ - compile_cmd::compile_circuit, - fs::{ - common_reference_string::{ - read_cached_common_reference_string, update_common_reference_string, - write_cached_common_reference_string, - }, - inputs::{read_inputs_from_file, write_inputs_to_file}, - program::read_program_from_file, - proof::save_proof_to_dir, +use super::compile_cmd::compile_circuit; +use super::fs::{ + common_reference_string::{ + read_cached_common_reference_string, update_common_reference_string, + write_cached_common_reference_string, }, + inputs::{read_inputs_from_file, write_inputs_to_file}, + program::read_program_from_file, + proof::save_proof_to_dir, }; -use crate::{ - cli::execute_cmd::execute_program, - constants::{PROOFS_DIR, PROVER_INPUT_FILE, TARGET_DIR, VERIFIER_INPUT_FILE}, - errors::CliError, -}; +use super::NargoConfig; +use crate::manifest::resolve_workspace_from_toml; +use crate::{cli::execute_cmd::execute_program, errors::CliError}; +use crate::{find_package_manifest, prepare_package}; /// Create proof for this program. The proof is returned as a hex encoded string. #[derive(Debug, Clone, Args)] pub(crate) struct ProveCommand { - /// The name of the proof - proof_name: Option, - - /// The name of the circuit build files (ACIR, proving and verification keys) - circuit_name: Option, - /// The name of the toml file which contains the inputs for the prover #[clap(long, short, default_value = PROVER_INPUT_FILE)] prover_name: String, @@ -47,11 +40,12 @@ pub(crate) struct ProveCommand { #[arg(long)] verify: bool, + /// The name of the package to prove + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, - - #[clap(long)] - package: Option, } pub(crate) fn run( @@ -59,65 +53,57 @@ pub(crate) fn run( args: ProveCommand, config: NargoConfig, ) -> Result<(), CliError> { - let proof_dir = config.program_dir.join(PROOFS_DIR); - - let circuit_build_path = args - .circuit_name - .map(|circuit_name| config.program_dir.join(TARGET_DIR).join(circuit_name)); - - prove_with_path( - backend, - args.proof_name, - args.prover_name, - args.verifier_name, - args.package, - config.program_dir, - proof_dir, - circuit_build_path, - args.verify, - &args.compile_options, - )?; + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + let proof_dir = workspace.proofs_directory_path(); + + for package in &workspace { + let circuit_build_path = workspace.package_build_path(package); + + prove_package( + backend, + package, + &args.prover_name, + &args.verifier_name, + &proof_dir, + circuit_build_path, + args.verify, + &args.compile_options, + )?; + } Ok(()) } #[allow(clippy::too_many_arguments)] -pub(crate) fn prove_with_path>( +pub(crate) fn prove_package( backend: &B, - proof_name: Option, - prover_name: String, - verifier_name: String, - package: Option, - program_dir: P, - proof_dir: P, - circuit_build_path: Option, + package: &Package, + prover_name: &str, + verifier_name: &str, + proof_dir: &Path, + circuit_build_path: PathBuf, check_proof: bool, compile_options: &CompileOptions, -) -> Result, CliError> { +) -> Result<(), CliError> { let common_reference_string = read_cached_common_reference_string(); - let (common_reference_string, preprocessed_program, debug_data) = match circuit_build_path { - Some(circuit_build_path) => { - let program = read_program_from_file(circuit_build_path)?; - let common_reference_string = update_common_reference_string( - backend, - &common_reference_string, - &program.bytecode, - ) - .map_err(CliError::CommonReferenceStringError)?; - (common_reference_string, program, None) - } - None => { - let (program, context) = - compile_circuit(backend, package, program_dir.as_ref(), compile_options)?; - let common_reference_string = - update_common_reference_string(backend, &common_reference_string, &program.circuit) - .map_err(CliError::CommonReferenceStringError)?; - let (program, debug) = - preprocess_program(backend, true, &common_reference_string, program) - .map_err(CliError::ProofSystemCompilerError)?; - (common_reference_string, program, Some((debug, context))) - } + let (common_reference_string, preprocessed_program, debug_data) = if circuit_build_path.exists() + { + let program = read_program_from_file(circuit_build_path)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.bytecode) + .map_err(CliError::CommonReferenceStringError)?; + (common_reference_string, program, None) + } else { + let (mut context, crate_id) = prepare_package(package); + let program = compile_circuit(backend, &mut context, crate_id, compile_options)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.circuit) + .map_err(CliError::CommonReferenceStringError)?; + let (program, debug) = preprocess_program(backend, true, &common_reference_string, program) + .map_err(CliError::ProofSystemCompilerError)?; + (common_reference_string, program, Some((debug, context))) }; write_cached_common_reference_string(&common_reference_string); @@ -127,7 +113,7 @@ pub(crate) fn prove_with_path>( // Parse the initial witness values from Prover.toml let (inputs_map, _) = - read_inputs_from_file(&program_dir, prover_name.as_str(), Format::Toml, &abi)?; + read_inputs_from_file(&package.root_dir, prover_name, Format::Toml, &abi)?; let solved_witness = execute_program(backend, bytecode.clone(), &abi, &inputs_map, debug_data)?; @@ -139,8 +125,8 @@ pub(crate) fn prove_with_path>( &public_inputs, &return_value, &public_abi, - &program_dir, - verifier_name.as_str(), + &package.root_dir, + verifier_name, Format::Toml, )?; @@ -170,12 +156,7 @@ pub(crate) fn prove_with_path>( } } - let proof_path = if let Some(proof_name) = proof_name { - Some(save_proof_to_dir(&proof, &proof_name, proof_dir)?) - } else { - println!("{}", hex::encode(&proof)); - None - }; + save_proof_to_dir(&proof, &String::from(&package.name), proof_dir)?; - Ok(proof_path) + Ok(()) } diff --git a/crates/nargo_cli/src/cli/test_cmd.rs b/crates/nargo_cli/src/cli/test_cmd.rs index c1aa359e724..7eb1c9bff74 100644 --- a/crates/nargo_cli/src/cli/test_cmd.rs +++ b/crates/nargo_cli/src/cli/test_cmd.rs @@ -1,15 +1,15 @@ -use std::{io::Write, path::Path}; +use std::io::Write; use acvm::{acir::native_types::WitnessMap, Backend}; use clap::Args; -use nargo::ops::execute_circuit; +use nargo::{ops::execute_circuit, package::Package}; use noirc_driver::{compile_no_check, CompileOptions}; -use noirc_frontend::{hir::Context, node_interner::FuncId}; +use noirc_frontend::{graph::CrateName, hir::Context, node_interner::FuncId}; use termcolor::{Color, ColorChoice, ColorSpec, StandardStream, WriteColor}; use crate::{ - cli::check_cmd::check_crate_and_report_errors, errors::CliError, - resolver::resolve_root_manifest, + cli::check_cmd::check_crate_and_report_errors, errors::CliError, find_package_manifest, + manifest::resolve_workspace_from_toml, prepare_package, }; use super::{compile_cmd::optimize_circuit, NargoConfig}; @@ -24,6 +24,10 @@ pub(crate) struct TestCommand { #[arg(long)] show_output: bool, + /// The name of the package to test + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } @@ -35,56 +39,62 @@ pub(crate) fn run( ) -> Result<(), CliError> { let test_name: String = args.test_name.unwrap_or_else(|| "".to_owned()); - run_tests(backend, &config.program_dir, &test_name, args.show_output, &args.compile_options) + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + + for package in &workspace { + run_tests(backend, package, &test_name, args.show_output, &args.compile_options)?; + } + + Ok(()) } fn run_tests( backend: &B, - program_dir: &Path, + package: &Package, test_name: &str, show_output: bool, compile_options: &CompileOptions, ) -> Result<(), CliError> { - let (mut context, crate_id) = resolve_root_manifest(program_dir, None)?; + let (mut context, crate_id) = prepare_package(package); check_crate_and_report_errors(&mut context, crate_id, compile_options.deny_warnings)?; - let test_functions = match context.crate_graph.crate_type(crate_id) { - noirc_frontend::graph::CrateType::Workspace => { - context.get_all_test_functions_in_workspace_matching(test_name) - } - _ => context.get_all_test_functions_in_crate_matching(&crate_id, test_name), - }; + let test_functions = context.get_all_test_functions_in_crate_matching(&crate_id, test_name); - println!("Running {} test functions...", test_functions.len()); + println!("[{}] Running {} test functions", package.name, test_functions.len()); let mut failing = 0; let writer = StandardStream::stderr(ColorChoice::Always); let mut writer = writer.lock(); for (test_name, test_function) in test_functions { - writeln!(writer, "Testing {test_name}...").expect("Failed to write to stdout"); - writer.flush().ok(); + write!(writer, "[{}] Testing {test_name}... ", package.name) + .expect("Failed to write to stdout"); + writer.flush().expect("Failed to flush writer"); match run_test(backend, &test_name, test_function, &context, show_output, compile_options) { Ok(_) => { - writer.set_color(ColorSpec::new().set_fg(Some(Color::Green))).ok(); - writeln!(writer, "ok").ok(); + writer + .set_color(ColorSpec::new().set_fg(Some(Color::Green))) + .expect("Failed to set color"); + writeln!(writer, "ok").expect("Failed to write to stdout"); } // Assume an error was already printed to stdout Err(_) => failing += 1, } - writer.reset().ok(); + writer.reset().expect("Failed to reset writer"); } if failing == 0 { - writer.set_color(ColorSpec::new().set_fg(Some(Color::Green))).unwrap(); - writeln!(writer, "All tests passed").ok(); + write!(writer, "[{}] ", package.name).expect("Failed to write to stdout"); + writer.set_color(ColorSpec::new().set_fg(Some(Color::Green))).expect("Failed to set color"); + writeln!(writer, "All tests passed").expect("Failed to write to stdout"); } else { let plural = if failing == 1 { "" } else { "s" }; - return Err(CliError::Generic(format!("{failing} test{plural} failed"))); + return Err(CliError::Generic(format!("[{}] {failing} test{plural} failed", package.name))); } - writer.reset().ok(); + writer.reset().expect("Failed to reset writer"); Ok(()) } diff --git a/crates/nargo_cli/src/cli/verify_cmd.rs b/crates/nargo_cli/src/cli/verify_cmd.rs index f9068c66c9c..78b23a0612d 100644 --- a/crates/nargo_cli/src/cli/verify_cmd.rs +++ b/crates/nargo_cli/src/cli/verify_cmd.rs @@ -9,32 +9,31 @@ use super::fs::{ program::read_program_from_file, }; use super::NargoConfig; -use crate::{ - constants::{PROOFS_DIR, PROOF_EXT, TARGET_DIR, VERIFIER_INPUT_FILE}, - errors::CliError, -}; +use crate::errors::CliError; +use crate::manifest::resolve_workspace_from_toml; +use crate::{find_package_manifest, prepare_package}; use acvm::Backend; use clap::Args; -use nargo::artifacts::program::PreprocessedProgram; +use nargo::constants::{PROOF_EXT, VERIFIER_INPUT_FILE}; use nargo::ops::{preprocess_program, verify_proof}; +use nargo::{artifacts::program::PreprocessedProgram, package::Package}; use noirc_abi::input_parser::Format; use noirc_driver::CompileOptions; +use noirc_frontend::graph::CrateName; use std::path::{Path, PathBuf}; /// Given a proof and a program, verify whether the proof is valid #[derive(Debug, Clone, Args)] pub(crate) struct VerifyCommand { - /// The proof to verify - proof: String, - - /// The name of the circuit build files (ACIR, proving and verification keys) - circuit_name: Option, - /// The name of the toml file which contains the inputs for the verifier #[clap(long, short, default_value = VERIFIER_INPUT_FILE)] verifier_name: String, + /// The name of the package verify + #[clap(long)] + package: Option, + #[clap(flatten)] compile_options: CompileOptions, } @@ -44,54 +43,53 @@ pub(crate) fn run( args: VerifyCommand, config: NargoConfig, ) -> Result<(), CliError> { - let proof_path = - config.program_dir.join(PROOFS_DIR).join(&args.proof).with_extension(PROOF_EXT); - - let circuit_build_path = args - .circuit_name - .map(|circuit_name| config.program_dir.join(TARGET_DIR).join(circuit_name)); + let toml_path = find_package_manifest(&config.program_dir)?; + let workspace = resolve_workspace_from_toml(&toml_path, args.package)?; + let proofs_dir = workspace.proofs_directory_path(); + + for package in &workspace { + let circuit_build_path = workspace.package_build_path(package); + + let proof_path = proofs_dir.join(String::from(&package.name)).with_extension(PROOF_EXT); + + verify_package( + backend, + package, + &proof_path, + circuit_build_path, + &args.verifier_name, + &args.compile_options, + )?; + } - verify_with_path( - backend, - &config.program_dir, - proof_path, - circuit_build_path.as_ref(), - args.verifier_name, - &args.compile_options, - ) + Ok(()) } -fn verify_with_path>( +fn verify_package( backend: &B, - program_dir: P, - proof_path: PathBuf, - circuit_build_path: Option

, - verifier_name: String, + package: &Package, + proof_path: &Path, + circuit_build_path: PathBuf, + verifier_name: &str, compile_options: &CompileOptions, ) -> Result<(), CliError> { let common_reference_string = read_cached_common_reference_string(); - let (common_reference_string, preprocessed_program) = match circuit_build_path { - Some(circuit_build_path) => { - let program = read_program_from_file(circuit_build_path)?; - let common_reference_string = update_common_reference_string( - backend, - &common_reference_string, - &program.bytecode, - ) - .map_err(CliError::CommonReferenceStringError)?; - (common_reference_string, program) - } - None => { - let (program, _) = - compile_circuit(backend, None, program_dir.as_ref(), compile_options)?; - let common_reference_string = - update_common_reference_string(backend, &common_reference_string, &program.circuit) - .map_err(CliError::CommonReferenceStringError)?; - let (program, _) = preprocess_program(backend, true, &common_reference_string, program) - .map_err(CliError::ProofSystemCompilerError)?; - (common_reference_string, program) - } + let (common_reference_string, preprocessed_program) = if circuit_build_path.exists() { + let program = read_program_from_file(circuit_build_path)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.bytecode) + .map_err(CliError::CommonReferenceStringError)?; + (common_reference_string, program) + } else { + let (mut context, crate_id) = prepare_package(package); + let program = compile_circuit(backend, &mut context, crate_id, compile_options)?; + let common_reference_string = + update_common_reference_string(backend, &common_reference_string, &program.circuit) + .map_err(CliError::CommonReferenceStringError)?; + let (program, _) = preprocess_program(backend, true, &common_reference_string, program) + .map_err(CliError::ProofSystemCompilerError)?; + (common_reference_string, program) }; write_cached_common_reference_string(&common_reference_string); @@ -101,10 +99,10 @@ fn verify_with_path>( // Load public inputs (if any) from `verifier_name`. let public_abi = abi.public_abi(); let (public_inputs_map, return_value) = - read_inputs_from_file(program_dir, verifier_name.as_str(), Format::Toml, &public_abi)?; + read_inputs_from_file(&package.root_dir, verifier_name, Format::Toml, &public_abi)?; let public_inputs = public_abi.encode(&public_inputs_map, return_value)?; - let proof = load_hex_data(&proof_path)?; + let proof = load_hex_data(proof_path)?; let verification_key = verification_key .expect("Verification key should exist as `true` is passed to `preprocess_program`"); @@ -121,6 +119,6 @@ fn verify_with_path>( if valid_proof { Ok(()) } else { - Err(CliError::InvalidProof(proof_path)) + Err(CliError::InvalidProof(proof_path.to_path_buf())) } } diff --git a/crates/nargo_cli/src/errors.rs b/crates/nargo_cli/src/errors.rs index f9220d55b1c..00a84ff2964 100644 --- a/crates/nargo_cli/src/errors.rs +++ b/crates/nargo_cli/src/errors.rs @@ -9,8 +9,6 @@ use noirc_errors::reporter::ReportedErrors; use std::path::PathBuf; use thiserror::Error; -use crate::resolver::DependencyResolutionError; - #[derive(Debug, Error)] pub(crate) enum FilesystemError { #[error("Error: {} is not a valid path\nRun either `nargo compile` to generate missing build artifacts or `nargo prove` to construct a proof", .0.display())] @@ -41,9 +39,6 @@ pub(crate) enum CliError { #[error("Failed to verify proof {}", .0.display())] InvalidProof(PathBuf), - #[error(transparent)] - ResolutionError(#[from] DependencyResolutionError), - /// Errors encountered while compiling the noir program. /// These errors are already written to stderr. #[error("Aborting due to {} previous error{}", .0.error_count, if .0.error_count == 1 { "" } else { "s" })] @@ -64,6 +59,10 @@ pub(crate) enum CliError { #[error(transparent)] NargoError(#[from] NargoError), + /// Error from Manifest + #[error(transparent)] + ManifestError(#[from] ManifestError), + /// Backend error caused by a function on the SmartContract trait #[error(transparent)] SmartContractError(::Error), // Unfortunately, Rust won't let us `impl From` over an Associated Type on a generic @@ -82,3 +81,50 @@ impl From for CliError { Self::ReportedErrors(errors) } } + +/// Errors covering situations where a package is either missing or malformed. +#[derive(Debug, Error)] +pub(crate) enum ManifestError { + /// Package doesn't have a manifest file + #[error("cannot find a Nargo.toml in {}", .0.display())] + MissingFile(PathBuf), + + #[error("Cannot read file {0}. Does it exist?")] + ReadFailed(PathBuf), + + #[error("Nargo.toml is missing a parent directory")] + MissingParent, + + /// Package manifest is unreadable. + #[error("Nargo.toml is badly formed, could not parse.\n\n {0}")] + MalformedFile(#[from] toml::de::Error), + + #[error("Unxpected workspace definition found in {0}")] + UnexpectedWorkspace(PathBuf), + + /// Package does not contain Noir source files. + #[error("cannot find src directory in path {0}")] + NoSourceDir(PathBuf), + + /// Package has neither of `main.nr` and `lib.nr`. + #[error("package must contain either a `lib.nr`(Library) or a `main.nr`(Binary).")] + ContainsZeroCrates, + + /// Package has both a `main.nr` (for binaries) and `lib.nr` (for libraries) + #[error("package cannot contain both a `lib.nr` and a `main.nr`")] + ContainsMultipleCrates, + + /// Invalid character `-` in package name + #[error("invalid character `-` in package name")] + InvalidPackageName, + + /// Encountered error while downloading git repository. + #[error("{0}")] + GitError(String), + + #[error("Selected package ({0}) was not found")] + MissingSelectedPackage(String), + + #[error("Default package was not found. Does {0} exist in your workspace?")] + MissingDefaultPackage(PathBuf), +} diff --git a/crates/nargo_cli/src/git.rs b/crates/nargo_cli/src/git.rs index 7f103e21b38..850657a8af1 100644 --- a/crates/nargo_cli/src/git.rs +++ b/crates/nargo_cli/src/git.rs @@ -1,7 +1,16 @@ use std::path::PathBuf; +/// Creates a unique folder name for a GitHub repo +/// by using its URL and tag +fn resolve_folder_name(base: &url::Url, tag: &str) -> String { + let mut folder_name = base.domain().unwrap().to_owned(); + folder_name.push_str(base.path()); + folder_name.push_str(tag); + folder_name +} + pub(crate) fn git_dep_location(base: &url::Url, tag: &str) -> PathBuf { - let folder_name = super::resolver::resolve_folder_name(base, tag); + let folder_name = resolve_folder_name(base, tag); super::nargo_crates().join(folder_name) } diff --git a/crates/nargo_cli/src/lib.rs b/crates/nargo_cli/src/lib.rs index 9426decf194..b456d31c0ca 100644 --- a/crates/nargo_cli/src/lib.rs +++ b/crates/nargo_cli/src/lib.rs @@ -7,21 +7,26 @@ //! This name was used because it sounds like `cargo` and //! Noir Package Manager abbreviated is npm, which is already taken. -use noirc_frontend::graph::CrateType; +use fm::FileManager; +use nargo::package::{Dependency, Package}; +use noirc_driver::{add_dep, create_local_crate, create_non_local_crate}; +use noirc_frontend::{ + graph::{CrateGraph, CrateId, CrateName, CrateType}, + hir::Context, +}; use std::{ + collections::BTreeMap, fs::ReadDir, path::{Path, PathBuf}, }; +use errors::ManifestError; + mod backends; pub mod cli; -mod constants; mod errors; mod git; mod manifest; -mod resolver; - -use nargo::manifest::InvalidPackageError; fn nargo_crates() -> PathBuf { dirs::home_dir().unwrap().join("nargo") @@ -30,7 +35,7 @@ fn nargo_crates() -> PathBuf { /// Returns the path of the root directory of the package containing `current_path`. /// /// Returns a `CliError` if no parent directories of `current_path` contain a manifest file. -fn find_package_root(current_path: &Path) -> Result { +fn find_package_root(current_path: &Path) -> Result { let manifest_path = find_package_manifest(current_path)?; let package_root = @@ -42,27 +47,27 @@ fn find_package_root(current_path: &Path) -> Result Result { +fn find_package_manifest(current_path: &Path) -> Result { current_path .ancestors() .find_map(|dir| find_file(dir, "Nargo", "toml")) - .ok_or_else(|| InvalidPackageError::MissingManifestFile(current_path.to_path_buf())) + .ok_or_else(|| ManifestError::MissingFile(current_path.to_path_buf())) } -fn lib_or_bin(current_path: impl AsRef) -> Result<(PathBuf, CrateType), InvalidPackageError> { - let current_path = current_path.as_ref(); +fn lib_or_bin(root_dir: impl AsRef) -> Result<(PathBuf, CrateType), ManifestError> { + let current_path = root_dir.as_ref(); // A library has a lib.nr and a binary has a main.nr // You cannot have both. let src_path = find_dir(current_path, "src") - .ok_or_else(|| InvalidPackageError::NoSourceDir(current_path.to_path_buf()))?; + .ok_or_else(|| ManifestError::NoSourceDir(current_path.to_path_buf()))?; let lib_nr_path = find_file(&src_path, "lib", "nr"); let bin_nr_path = find_file(&src_path, "main", "nr"); match (lib_nr_path, bin_nr_path) { - (Some(_), Some(_)) => Err(InvalidPackageError::ContainsMultipleCrates), + (Some(_), Some(_)) => Err(ManifestError::ContainsMultipleCrates), (None, Some(path)) => Ok((path, CrateType::Binary)), (Some(path), None) => Ok((path, CrateType::Library)), - (None, None) => Err(InvalidPackageError::ContainsZeroCrates), + (None, None) => Err(ManifestError::ContainsZeroCrates), } } @@ -93,3 +98,32 @@ fn find_artifact(entries: ReadDir, artifact_name: &str) -> Option { fn list_files_and_folders_in>(path: P) -> Option { std::fs::read_dir(path).ok() } + +fn prepare_dependencies( + context: &mut Context, + parent_crate: CrateId, + dependencies: BTreeMap, +) { + for (dep_name, dep) in dependencies.into_iter() { + match dep { + Dependency::Remote { package } | Dependency::Local { package } => { + let crate_id = + create_non_local_crate(context, &package.entry_path, package.crate_type); + add_dep(context, parent_crate, crate_id, dep_name); + prepare_dependencies(context, crate_id, package.dependencies.to_owned()); + } + } + } +} + +fn prepare_package(package: &Package) -> (Context, CrateId) { + let fm = FileManager::new(&package.root_dir); + let graph = CrateGraph::default(); + let mut context = Context::new(fm, graph); + + let crate_id = create_local_crate(&mut context, &package.entry_path, package.crate_type); + + prepare_dependencies(&mut context, crate_id, package.dependencies.to_owned()); + + (context, crate_id) +} diff --git a/crates/nargo_cli/src/manifest.rs b/crates/nargo_cli/src/manifest.rs index 2660fd8c1cb..e1da57c0c2b 100644 --- a/crates/nargo_cli/src/manifest.rs +++ b/crates/nargo_cli/src/manifest.rs @@ -1,13 +1,284 @@ -use std::path::Path; +use std::{ + collections::BTreeMap, + path::{Path, PathBuf}, +}; -use nargo::manifest::{InvalidPackageError, Manifest}; +use nargo::{ + package::{Dependency, Package}, + workspace::Workspace, +}; +use noirc_frontend::graph::CrateName; +use serde::Deserialize; -/// Parses a Nargo.toml file from it's path -/// The path to the toml file must be present. -/// Calling this function without this guarantee is an ICE. -pub(crate) fn parse>(path_to_toml: P) -> Result { - let toml_as_string = - std::fs::read_to_string(&path_to_toml).expect("ice: path given for toml file is invalid"); +use crate::{errors::ManifestError, git::clone_git_repo}; - Manifest::from_toml_str(&toml_as_string) +#[derive(Debug, Deserialize, Clone)] +struct PackageConfig { + package: PackageMetadata, + dependencies: BTreeMap, +} + +impl PackageConfig { + fn resolve_to_package(&self, root_dir: &Path) -> Result { + let name = self.package.name.parse().map_err(|_| ManifestError::InvalidPackageName)?; + + let mut dependencies: BTreeMap = BTreeMap::new(); + for (name, dep_config) in self.dependencies.iter() { + let name = name.parse().map_err(|_| ManifestError::InvalidPackageName)?; + let resolved_dep = dep_config.resolve_to_dependency(root_dir)?; + + dependencies.insert(name, resolved_dep); + } + + let (entry_path, crate_type) = crate::lib_or_bin(root_dir)?; + + Ok(Package { root_dir: root_dir.to_path_buf(), entry_path, crate_type, name, dependencies }) + } +} + +/// Contains all the information about a package, as loaded from a `Nargo.toml`. +#[derive(Debug, Deserialize, Clone)] +#[serde(untagged)] +enum Config { + /// Represents a `Nargo.toml` with package fields. + Package { + #[serde(flatten)] + package_config: PackageConfig, + }, + /// Represents a `Nargo.toml` with workspace fields. + Workspace { + #[serde(alias = "workspace")] + workspace_config: WorkspaceConfig, + }, +} + +impl TryFrom for Config { + type Error = toml::de::Error; + + fn try_from(toml: String) -> Result { + toml::from_str(&toml) + } +} + +impl TryFrom<&str> for Config { + type Error = toml::de::Error; + + fn try_from(toml: &str) -> Result { + toml::from_str(toml) + } +} + +/// Tracks the root_dir of a `Nargo.toml` and the contents inside the file. +struct NargoToml { + root_dir: PathBuf, + config: Config, +} + +#[derive(Default, Debug, Deserialize, Clone)] +#[serde(rename_all = "kebab-case")] +struct WorkspaceConfig { + /// List of members in this workspace. + members: Vec, + /// Specifies the default crate to interact with in the context (similarly to how we have nargo as the default crate in this repository). + default_member: Option, +} + +#[allow(dead_code)] +#[derive(Default, Debug, Deserialize, Clone)] +struct PackageMetadata { + #[serde(default = "panic_missing_name")] + name: String, + description: Option, + authors: Option>, + // If not compiler version is supplied, the latest is used + // For now, we state that all packages must be compiled under the same + // compiler version. + // We also state that ACIR and the compiler will upgrade in lockstep. + // so you will not need to supply an ACIR and compiler version + compiler_version: Option, + backend: Option, + license: Option, +} + +// TODO: Remove this after a couple of breaking releases (added in 0.10.0) +fn panic_missing_name() -> String { + panic!( + r#" + +Failed to parse `Nargo.toml`. + +`Nargo.toml` now requires a "name" field for Noir packages. + +```toml +[package] +name = "package_name" +``` + +Modify your `Nargo.toml` similarly to above and rerun the command. + +"# + ) +} + +#[derive(Debug, Deserialize, Clone)] +#[serde(untagged)] +/// Enum representing the different types of ways to +/// supply a source for the dependency +enum DependencyConfig { + Github { git: String, tag: String }, + Path { path: String }, +} + +impl DependencyConfig { + fn resolve_to_dependency(&self, pkg_root: &Path) -> Result { + match self { + Self::Github { git, tag } => { + let dir_path = clone_git_repo(git, tag).map_err(ManifestError::GitError)?; + let toml_path = dir_path.join("Nargo.toml"); + let package = resolve_package_from_toml(&toml_path)?; + Ok(Dependency::Remote { package }) + } + Self::Path { path } => { + let dir_path = pkg_root.join(path); + let toml_path = dir_path.join("Nargo.toml"); + let package = resolve_package_from_toml(&toml_path)?; + Ok(Dependency::Local { package }) + } + } + } +} + +fn toml_to_workspace( + nargo_toml: NargoToml, + selected_package: Option, +) -> Result { + let workspace = match nargo_toml.config { + Config::Package { package_config } => { + let member = package_config.resolve_to_package(&nargo_toml.root_dir)?; + if selected_package.is_none() || Some(&member.name) == selected_package.as_ref() { + Workspace { + root_dir: nargo_toml.root_dir, + selected_package_index: Some(0), + members: vec![member], + } + } else { + return Err(ManifestError::MissingSelectedPackage(member.name.into())); + } + } + Config::Workspace { workspace_config } => { + let mut members = Vec::new(); + let mut selected_package_index = None; + for (index, member_path) in workspace_config.members.into_iter().enumerate() { + let package_root_dir = nargo_toml.root_dir.join(&member_path); + let package_toml_path = package_root_dir.join("Nargo.toml"); + let member = resolve_package_from_toml(&package_toml_path)?; + + match selected_package.as_ref() { + Some(selected_name) => { + if &member.name == selected_name { + selected_package_index = Some(index); + } + } + None => { + if Some(&member_path) == workspace_config.default_member.as_ref() { + selected_package_index = Some(index); + } + } + } + + members.push(member); + } + + // If the selected_package_index is still `None` but we have see a default_member or selected package, + // we want to present an error to users + if selected_package_index.is_none() { + if let Some(selected_name) = selected_package { + return Err(ManifestError::MissingSelectedPackage(selected_name.into())); + } + if let Some(default_path) = workspace_config.default_member { + return Err(ManifestError::MissingDefaultPackage(default_path)); + } + } + + Workspace { root_dir: nargo_toml.root_dir, members, selected_package_index } + } + }; + + Ok(workspace) +} + +fn read_toml(toml_path: &Path) -> Result { + let toml_as_string = std::fs::read_to_string(toml_path) + .map_err(|_| ManifestError::ReadFailed(toml_path.to_path_buf()))?; + let root_dir = toml_path.parent().ok_or(ManifestError::MissingParent)?; + let nargo_toml = + NargoToml { root_dir: root_dir.to_path_buf(), config: toml_as_string.try_into()? }; + + Ok(nargo_toml) +} + +/// Resolves a Nargo.toml file into a `Package` struct as defined by our `nargo` core. +fn resolve_package_from_toml(toml_path: &Path) -> Result { + let nargo_toml = read_toml(toml_path)?; + + match nargo_toml.config { + Config::Package { package_config } => { + package_config.resolve_to_package(&nargo_toml.root_dir) + } + Config::Workspace { .. } => { + Err(ManifestError::UnexpectedWorkspace(toml_path.to_path_buf())) + } + } +} + +/// Resolves a Nargo.toml file into a `Workspace` struct as defined by our `nargo` core. +pub(crate) fn resolve_workspace_from_toml( + toml_path: &Path, + selected_package: Option, +) -> Result { + let nargo_toml = read_toml(toml_path)?; + + toml_to_workspace(nargo_toml, selected_package) +} + +#[test] +fn parse_standard_toml() { + let src = r#" + + [package] + name = "test" + authors = ["kev", "foo"] + compiler_version = "0.1" + + [dependencies] + rand = { tag = "next", git = "https://github.com/rust-lang-nursery/rand"} + cool = { tag = "next", git = "https://github.com/rust-lang-nursery/rand"} + hello = {path = "./noir_driver"} + "#; + + assert!(Config::try_from(String::from(src)).is_ok()); + assert!(Config::try_from(src).is_ok()); +} + +#[test] +fn parse_workspace_toml() { + let src = r#" + [workspace] + members = ["a", "b"] + "#; + + assert!(Config::try_from(String::from(src)).is_ok()); + assert!(Config::try_from(src).is_ok()); +} + +#[test] +fn parse_workspace_default_member_toml() { + let src = r#" + [workspace] + members = ["a", "b"] + default-member = "a" + "#; + + assert!(Config::try_from(String::from(src)).is_ok()); + assert!(Config::try_from(src).is_ok()); } diff --git a/crates/nargo_cli/src/resolver.rs b/crates/nargo_cli/src/resolver.rs deleted file mode 100644 index 5c4e8225ee4..00000000000 --- a/crates/nargo_cli/src/resolver.rs +++ /dev/null @@ -1,265 +0,0 @@ -use std::{ - collections::HashMap, - path::{Path, PathBuf}, -}; - -use fm::FileManager; -use nargo::manifest::{Dependency, Manifest, PackageManifest, WorkspaceConfig}; -use noirc_driver::{add_dep, create_local_crate, create_non_local_crate}; -use noirc_frontend::{ - graph::{CrateGraph, CrateId, CrateName, CrateType}, - hir::Context, -}; -use thiserror::Error; - -use crate::{git::clone_git_repo, InvalidPackageError}; - -/// Creates a unique folder name for a GitHub repo -/// by using it's URL and tag -pub(crate) fn resolve_folder_name(base: &url::Url, tag: &str) -> String { - let mut folder_name = base.domain().unwrap().to_owned(); - folder_name.push_str(base.path()); - folder_name.push_str(tag); - folder_name -} - -/// Errors covering situations where a crate's dependency tree cannot be resolved. -#[derive(Debug, Error)] -pub(crate) enum DependencyResolutionError { - /// Encountered error while downloading git repository. - #[error("{0}")] - GitError(String), - - /// Attempted to depend on a binary crate. - #[error("dependency {dep_pkg_name} is a binary package and so it cannot be depended upon.")] - BinaryDependency { dep_pkg_name: String }, - - /// Attempted to depend on remote crate which has a local dependency. - /// We have no guarantees that this local dependency will be available so must error. - #[error("remote(git) dependency has a local dependency.\ndependency located at {}", dependency_path.display())] - RemoteDepWithLocalDep { dependency_path: PathBuf }, - - /// Dependency is not a valid crate - #[error(transparent)] - MalformedDependency(#[from] InvalidPackageError), - - /// Workspace does not contain packages - #[error("manifest path `{}` contains no packages", path.display())] - EmptyWorkspace { path: PathBuf }, - - /// Use workspace as a dependency is not currently supported - #[error("use workspace as a dependency is not currently supported")] - WorkspaceDependency, - - /// Multiple workspace roots found in the same workspace - #[error("multiple workspace roots found in the same workspace:\n{}\n{}", root.display(), member.display())] - MultipleWorkspace { root: PathBuf, member: PathBuf }, - - /// Invalid character `-` in package name - #[error("invalid character `-` in package name")] - InvalidPackageName, - - #[error("package specification `{0}` did not match any packages")] - PackageNotFound(String), - - #[error("two packages named `{0}` in this workspace")] - PackageCollision(String), -} - -#[derive(Debug, Clone)] -struct CachedDep { - entry_path: PathBuf, - crate_type: CrateType, - manifest: PackageManifest, - // Whether the dependency came from - // a remote dependency - remote: bool, -} - -/// Resolves a toml file by either downloading the necessary git repo -/// or it uses the repo on the cache. -/// Downloading will be recursive, so if a package contains packages -/// We need to download those too - -/// Returns the Driver and the backend to use -/// Note that the backend is ignored in the dependencies. -/// Since Noir is backend agnostic, this is okay to do. -/// XXX: Need to handle when a local package changes! -pub(crate) fn resolve_root_manifest( - dir_path: &std::path::Path, - package: Option, -) -> Result<(Context, CrateId), DependencyResolutionError> { - let fm = FileManager::new(dir_path); - let graph = CrateGraph::default(); - let mut context = Context::new(fm, graph); - - let manifest_path = super::find_package_manifest(dir_path)?; - let manifest = super::manifest::parse(&manifest_path)?; - - let crate_id = match manifest { - Manifest::Package(package) => { - let (entry_path, crate_type) = super::lib_or_bin(dir_path)?; - - let crate_id = create_local_crate(&mut context, &entry_path, crate_type); - let pkg_root = manifest_path.parent().expect("Every manifest path has a parent."); - - resolve_package_manifest(&mut context, crate_id, package, pkg_root)?; - - crate_id - } - Manifest::Workspace(workspace) => resolve_workspace_manifest( - &mut context, - package, - manifest_path, - dir_path, - workspace.config, - )?, - }; - - Ok((context, crate_id)) -} - -// Resolves a config file by recursively resolving the dependencies in the config -// Need to solve the case of a project trying to use itself as a dep -// -// We do not need to add stdlib, as it's implicitly -// imported. However, it may be helpful to have the stdlib imported by the -// package manager. -fn resolve_package_manifest( - context: &mut Context, - parent_crate: CrateId, - manifest: PackageManifest, - pkg_root: &Path, -) -> Result<(), DependencyResolutionError> { - let mut cached_packages: HashMap = HashMap::new(); - - // First download and add these top level dependencies crates to the Driver - for (dep_pkg_name, pkg_src) in manifest.dependencies.iter() { - let (dir_path, dep_meta) = cache_dep(pkg_src, pkg_root)?; - - let (entry_path, crate_type) = (&dep_meta.entry_path, &dep_meta.crate_type); - - if crate_type == &CrateType::Binary { - return Err(DependencyResolutionError::BinaryDependency { - dep_pkg_name: dep_pkg_name.to_string(), - }); - } - - let crate_id = create_non_local_crate(context, entry_path, *crate_type); - add_dep(context, parent_crate, crate_id, dep_pkg_name); - - cached_packages.insert(dir_path, (crate_id, dep_meta)); - } - - // Resolve all transitive dependencies - for (dependency_path, (crate_id, dep_meta)) in cached_packages { - if dep_meta.remote && dep_meta.manifest.has_local_dependency() { - return Err(DependencyResolutionError::RemoteDepWithLocalDep { dependency_path }); - } - // TODO: Why did it create a new resolver? - resolve_package_manifest(context, crate_id, dep_meta.manifest, &dependency_path)?; - } - Ok(()) -} - -fn resolve_workspace_manifest( - context: &mut Context, - mut local_package: Option, - manifest_path: PathBuf, - dir_path: &Path, - workspace: WorkspaceConfig, -) -> Result { - let members = workspace.members; - let mut packages = HashMap::new(); - - if members.is_empty() { - return Err(DependencyResolutionError::EmptyWorkspace { path: manifest_path }); - } - - for member in &members { - let member_path: PathBuf = dir_path.join(member); - let member_member_path = super::find_package_manifest(&member_path)?; - let member_manifest = super::manifest::parse(&member_member_path)?; - - match member_manifest { - Manifest::Package(inner) => { - let name: CrateName = inner - .package - .name - .parse() - .map_err(|_name| DependencyResolutionError::InvalidPackageName)?; - - if packages.insert(name.clone(), member_path).is_some() { - return Err(DependencyResolutionError::PackageCollision(name.into())); - } - - if local_package.is_none() && workspace.default_member.as_ref() == Some(member) { - local_package = Some(name.into()); - } - } - Manifest::Workspace(_) => { - return Err(DependencyResolutionError::MultipleWorkspace { - root: manifest_path, - member: member_member_path, - }) - } - } - } - - let local_package = match local_package { - Some(local_package) => { - local_package.parse().map_err(|_| DependencyResolutionError::InvalidPackageName)? - } - None => packages.keys().last().expect("non-empty packages").clone(), - }; - - let local_crate = packages - .remove(&local_package) - .ok_or_else(|| DependencyResolutionError::PackageNotFound(local_package.into()))?; - - let (entry_path, _crate_type) = super::lib_or_bin(local_crate)?; - let crate_id = create_local_crate(context, &entry_path, CrateType::Workspace); - - for (_, package_path) in packages.drain() { - let (entry_path, crate_type) = super::lib_or_bin(package_path)?; - create_non_local_crate(context, &entry_path, crate_type); - } - - Ok(crate_id) -} - -/// If the dependency is remote, download the dependency -/// and return the directory path along with the metadata -/// Needed to fill the CachedDep struct -/// -/// If it's a local path, the same applies, however it will not -/// be downloaded -fn cache_dep( - dep: &Dependency, - pkg_root: &Path, -) -> Result<(PathBuf, CachedDep), DependencyResolutionError> { - fn retrieve_meta( - dir_path: &Path, - remote: bool, - ) -> Result { - let (entry_path, crate_type) = super::lib_or_bin(dir_path)?; - let manifest_path = super::find_package_manifest(dir_path)?; - let manifest = super::manifest::parse(manifest_path)? - .to_package() - .ok_or(DependencyResolutionError::WorkspaceDependency)?; - Ok(CachedDep { entry_path, crate_type, manifest, remote }) - } - - match dep { - Dependency::Github { git, tag } => { - let dir_path = clone_git_repo(git, tag).map_err(DependencyResolutionError::GitError)?; - let meta = retrieve_meta(&dir_path, true)?; - Ok((dir_path, meta)) - } - Dependency::Path { path } => { - let dir_path = pkg_root.join(path); - let meta = retrieve_meta(&dir_path, false)?; - Ok((dir_path, meta)) - } - } -} diff --git a/crates/nargo_cli/tests/codegen-verifier.rs b/crates/nargo_cli/tests/codegen-verifier.rs index 3e4dc1dc745..f991f72b108 100644 --- a/crates/nargo_cli/tests/codegen-verifier.rs +++ b/crates/nargo_cli/tests/codegen-verifier.rs @@ -29,5 +29,9 @@ fn simple_verifier_codegen() { .success() .stdout(predicate::str::contains("Contract successfully created and located at")); - project_dir.child("contract").child("plonk_vk.sol").assert(predicate::path::is_file()); + project_dir + .child("contract") + .child("hello_world") + .child("plonk_vk.sol") + .assert(predicate::path::is_file()); } diff --git a/crates/nargo_cli/tests/hello_world.rs b/crates/nargo_cli/tests/hello_world.rs index 121f09f0ece..bc7022d1567 100644 --- a/crates/nargo_cli/tests/hello_world.rs +++ b/crates/nargo_cli/tests/hello_world.rs @@ -36,21 +36,20 @@ fn hello_world_example() { project_dir.child("Prover.toml").assert(predicate::path::is_file()); project_dir.child("Verifier.toml").assert(predicate::path::is_file()); - // `nargo prove p` - let proof_name = "p"; + // `nargo prove` project_dir.child("Prover.toml").write_str("x = 1\ny = 2").unwrap(); let mut cmd = Command::cargo_bin("nargo").unwrap(); - cmd.arg("prove").arg(proof_name); + cmd.arg("prove"); cmd.assert().success(); project_dir .child("proofs") - .child(format!("{proof_name}.proof")) + .child(format!("{project_name}.proof")) .assert(predicate::path::is_file()); // `nargo verify p` let mut cmd = Command::cargo_bin("nargo").unwrap(); - cmd.arg("verify").arg(proof_name); + cmd.arg("verify"); cmd.assert().success(); } diff --git a/crates/nargo_cli/tests/test_data/config.toml b/crates/nargo_cli/tests/test_data/config.toml index 88776ed03d2..6fe6c7897e1 100644 --- a/crates/nargo_cli/tests/test_data/config.toml +++ b/crates/nargo_cli/tests/test_data/config.toml @@ -2,4 +2,4 @@ exclude = [] # List of tests (as their directory name) expecting to fail: if the test pass, we report an error. -fail = ["brillig_assert_fail", "dep_impl_primitive"] +fail = ["brillig_assert_fail", "dep_impl_primitive", "workspace_fail", "workspace_missing_toml"] diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/a/Prover.toml b/crates/nargo_cli/tests/test_data/workspace/crates/a/Prover.toml new file mode 100644 index 00000000000..465ef562de4 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace/crates/a/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "1" diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/a/src/main.nr b/crates/nargo_cli/tests/test_data/workspace/crates/a/src/main.nr index 81847a9031d..550e5034a7b 100644 --- a/crates/nargo_cli/tests/test_data/workspace/crates/a/src/main.nr +++ b/crates/nargo_cli/tests/test_data/workspace/crates/a/src/main.nr @@ -1,11 +1,3 @@ fn main(x : Field, y : pub Field) { - assert(x != y); -} - -#[test] -fn a() { - main(1, 2); - - // Uncomment to make test fail - // main(1, 1); + assert(x == y); } diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/b/Prover.toml b/crates/nargo_cli/tests/test_data/workspace/crates/b/Prover.toml new file mode 100644 index 00000000000..a0397e89477 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace/crates/b/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "0" diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/b/src/main.nr b/crates/nargo_cli/tests/test_data/workspace/crates/b/src/main.nr index 512f99feeca..6e170de75fc 100644 --- a/crates/nargo_cli/tests/test_data/workspace/crates/b/src/main.nr +++ b/crates/nargo_cli/tests/test_data/workspace/crates/b/src/main.nr @@ -1,11 +1,3 @@ fn main(x : Field, y : pub Field) { assert(x != y); } - -#[test] -fn b() { - main(1, 2); - - // Uncomment to make test fail - // main(1, 1); -} diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/a/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_default_member/a/Prover.toml new file mode 100644 index 00000000000..465ef562de4 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_default_member/a/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "1" diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/a/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_default_member/a/src/main.nr index 206dc46d57a..550e5034a7b 100644 --- a/crates/nargo_cli/tests/test_data/workspace_default_member/a/src/main.nr +++ b/crates/nargo_cli/tests/test_data/workspace_default_member/a/src/main.nr @@ -1,11 +1,3 @@ fn main(x : Field, y : pub Field) { - assert(x != y); -} - -#[test] -fn test_main() { - main(1, 2); - - // Uncomment to make test fail - // main(1, 1); + assert(x == y); } diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/b/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_default_member/b/Nargo.toml new file mode 100644 index 00000000000..85c6119c62c --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_default_member/b/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "b" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/b/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_default_member/b/Prover.toml new file mode 100644 index 00000000000..83fcd8678e7 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_default_member/b/Prover.toml @@ -0,0 +1,3 @@ +# Deliberately setting these to fail to prove this is NOT executed since a default is specified +x = "1" +y = "1" diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/b/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_default_member/b/src/main.nr new file mode 100644 index 00000000000..6e170de75fc --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_default_member/b/src/main.nr @@ -0,0 +1,3 @@ +fn main(x : Field, y : pub Field) { + assert(x != y); +} diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_fail/Nargo.toml new file mode 100644 index 00000000000..36db098686f --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/Nargo.toml @@ -0,0 +1,2 @@ +[workspace] +members = ["crates/a", "crates/b"] diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Nargo.toml new file mode 100644 index 00000000000..5ff1a743e3d --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "a" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Prover.toml new file mode 100644 index 00000000000..b76c88bf536 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/Prover.toml @@ -0,0 +1,3 @@ +# Deliberately setting these to fail to prove this is being executed +x = "1" +y = "2" diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/src/main.nr new file mode 100644 index 00000000000..550e5034a7b --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/a/src/main.nr @@ -0,0 +1,3 @@ +fn main(x : Field, y : pub Field) { + assert(x == y); +} diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Nargo.toml new file mode 100644 index 00000000000..8ae69a781eb --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "b" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Prover.toml new file mode 100644 index 00000000000..a0397e89477 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "0" diff --git a/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/src/main.nr new file mode 100644 index 00000000000..6e170de75fc --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_fail/crates/b/src/main.nr @@ -0,0 +1,3 @@ +fn main(x : Field, y : pub Field) { + assert(x != y); +} diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_missing_toml/Nargo.toml new file mode 100644 index 00000000000..36db098686f --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/Nargo.toml @@ -0,0 +1,2 @@ +[workspace] +members = ["crates/a", "crates/b"] diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/Prover.toml new file mode 100644 index 00000000000..465ef562de4 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "1" diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/src/main.nr new file mode 100644 index 00000000000..550e5034a7b --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/a/src/main.nr @@ -0,0 +1,3 @@ +fn main(x : Field, y : pub Field) { + assert(x == y); +} diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Nargo.toml new file mode 100644 index 00000000000..8ae69a781eb --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "b" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Prover.toml b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Prover.toml new file mode 100644 index 00000000000..a0397e89477 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/Prover.toml @@ -0,0 +1,2 @@ +x = "1" +y = "0" diff --git a/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/src/main.nr b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/src/main.nr new file mode 100644 index 00000000000..6e170de75fc --- /dev/null +++ b/crates/nargo_cli/tests/test_data/workspace_missing_toml/crates/b/src/main.nr @@ -0,0 +1,3 @@ +fn main(x : Field, y : pub Field) { + assert(x != y); +} diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs index f2537bb88fe..c0957313f69 100644 --- a/crates/noirc_driver/src/lib.rs +++ b/crates/noirc_driver/src/lib.rs @@ -87,10 +87,12 @@ pub fn create_non_local_crate( } /// Adds a edge in the crate graph for two crates -pub fn add_dep(context: &mut Context, this_crate: CrateId, depends_on: CrateId, crate_name: &str) { - let crate_name = - crate_name.parse().expect("crate name contains blacklisted characters, please remove"); - +pub fn add_dep( + context: &mut Context, + this_crate: CrateId, + depends_on: CrateId, + crate_name: CrateName, +) { // Cannot depend on a binary if context.crate_graph.crate_type(depends_on) == CrateType::Binary { panic!("crates cannot depend on binaries. {crate_name:?} is a binary crate") @@ -142,15 +144,7 @@ pub fn check_crate( propagate_dep(context, std_crate, &std_crate_name.parse().unwrap()); let mut errors = vec![]; - match context.crate_graph.crate_type(crate_id) { - CrateType::Workspace => { - let keys: Vec<_> = context.crate_graph.iter_keys().collect(); // avoid borrow checker - for crate_id in keys { - CrateDefMap::collect_defs(crate_id, context, &mut errors); - } - } - _ => CrateDefMap::collect_defs(crate_id, context, &mut errors), - } + CrateDefMap::collect_defs(crate_id, context, &mut errors); if has_errors(&errors, deny_warnings) { Err(errors) diff --git a/crates/noirc_frontend/src/graph/mod.rs b/crates/noirc_frontend/src/graph/mod.rs index 7ebfbae4817..af9216071e6 100644 --- a/crates/noirc_frontend/src/graph/mod.rs +++ b/crates/noirc_frontend/src/graph/mod.rs @@ -4,7 +4,7 @@ // This version is also simpler due to not having macro_defs or proc_macros // XXX: Edition may be reintroduced or some sort of versioning -use std::str::FromStr; +use std::{fmt::Display, str::FromStr}; use fm::FileId; use rustc_hash::{FxHashMap, FxHashSet}; @@ -26,14 +26,25 @@ impl CrateId { } } -#[derive(Debug, Clone, PartialEq, Eq, Hash)] +#[derive(Debug, Clone, PartialEq, Eq, Hash, Ord, PartialOrd)] pub struct CrateName(SmolStr); +impl Display for CrateName { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + self.0.fmt(f) + } +} + impl From for String { fn from(crate_name: CrateName) -> Self { crate_name.0.into() } } +impl From<&CrateName> for String { + fn from(crate_name: &CrateName) -> Self { + crate_name.0.clone().into() + } +} /// Creates a new CrateName rejecting any crate name that /// has a character on the blacklist. @@ -66,7 +77,6 @@ pub const CHARACTER_BLACK_LIST: [char; 1] = ['-']; pub enum CrateType { Library, Binary, - Workspace, } #[derive(Debug, Clone, PartialEq, Eq)] diff --git a/crates/noirc_frontend/src/hir/mod.rs b/crates/noirc_frontend/src/hir/mod.rs index 5937f57a8c7..d6f98e112af 100644 --- a/crates/noirc_frontend/src/hir/mod.rs +++ b/crates/noirc_frontend/src/hir/mod.rs @@ -69,10 +69,7 @@ impl Context { // Check the crate type // We don't panic here to allow users to `evaluate` libraries which will do nothing - if matches!( - self.crate_graph[*crate_id].crate_type, - CrateType::Binary | CrateType::Workspace - ) { + if matches!(self.crate_graph[*crate_id].crate_type, CrateType::Binary) { // All Binaries should have a main function local_crate.main_function() } else { @@ -112,19 +109,6 @@ impl Context { .collect() } - pub fn get_all_test_functions_in_workspace_matching( - &self, - pattern: &str, - ) -> Vec<(String, FuncId)> { - let mut tests = Vec::new(); - - for crate_id in self.crate_graph.iter_keys() { - tests.extend(self.get_all_test_functions_in_crate_matching(&crate_id, pattern)); - } - - tests - } - /// Return a Vec of all `contract` declarations in the source code and the functions they contain pub fn get_all_contracts(&self, crate_id: &CrateId) -> Vec { self.def_map(crate_id) From 39610af5b3cc8de7e3aa963a2cbff3083179cbf4 Mon Sep 17 00:00:00 2001 From: Blaine Bublitz Date: Wed, 2 Aug 2023 01:28:09 -0700 Subject: [PATCH 22/50] chore(noirc_driver): Unify crate preparation (#2119) --- crates/lsp/src/lib.rs | 6 +++--- crates/lsp/src/lib_hacky.rs | 7 +++---- crates/nargo_cli/src/cli/mod.rs | 4 ++-- crates/nargo_cli/src/lib.rs | 7 +++---- crates/noirc_driver/src/lib.rs | 29 +++-------------------------- crates/wasm/src/compile.rs | 8 ++++---- 6 files changed, 18 insertions(+), 43 deletions(-) diff --git a/crates/lsp/src/lib.rs b/crates/lsp/src/lib.rs index bd4112218e4..1c02c802808 100644 --- a/crates/lsp/src/lib.rs +++ b/crates/lsp/src/lib.rs @@ -22,7 +22,7 @@ use lsp_types::{ InitializeParams, InitializeResult, InitializedParams, Position, PublishDiagnosticsParams, Range, ServerCapabilities, TextDocumentSyncOptions, }; -use noirc_driver::{check_crate, create_local_crate}; +use noirc_driver::{check_crate, prepare_crate}; use noirc_errors::{DiagnosticKind, FileDiagnostic}; use noirc_frontend::{ graph::{CrateGraph, CrateType}, @@ -190,7 +190,7 @@ fn on_code_lens_request( } }; - let crate_id = create_local_crate(&mut context, file_path, CrateType::Binary); + let crate_id = prepare_crate(&mut context, file_path, CrateType::Binary); // We ignore the warnings and errors produced by compilation for producing codelenses // because we can still get the test functions even if compilation fails @@ -283,7 +283,7 @@ fn on_did_save_text_document( } }; - let crate_id = create_local_crate(&mut context, file_path, CrateType::Binary); + let crate_id = prepare_crate(&mut context, file_path, CrateType::Binary); let mut diagnostics = Vec::new(); diff --git a/crates/lsp/src/lib_hacky.rs b/crates/lsp/src/lib_hacky.rs index 72a2625fcac..13bb2b82847 100644 --- a/crates/lsp/src/lib_hacky.rs +++ b/crates/lsp/src/lib_hacky.rs @@ -19,7 +19,7 @@ use lsp_types::{ InitializedParams, Position, PublishDiagnosticsParams, Range, ServerCapabilities, TextDocumentSyncOptions, }; -use noirc_driver::{check_crate, create_local_crate, create_non_local_crate, propagate_dep}; +use noirc_driver::{check_crate, prepare_crate, propagate_dep}; use noirc_errors::{DiagnosticKind, FileDiagnostic}; use noirc_frontend::{ graph::{CrateGraph, CrateId, CrateType}, @@ -286,7 +286,7 @@ fn create_context_at_path( } let nargo_toml_path = find_nearest_parent_file(&file_path, &["Nargo.toml"]); - let current_crate_id = create_local_crate(&mut context, &file_path, CrateType::Binary); + let current_crate_id = prepare_crate(&mut context, &file_path, CrateType::Binary); // TODO(AD): undo hacky dependency resolution if let Some(nargo_toml_path) = nargo_toml_path { @@ -297,8 +297,7 @@ fn create_context_at_path( .parent() .unwrap() // TODO .join(PathBuf::from(&dependency_path).join("src").join("lib.nr")); - let library_crate = - create_non_local_crate(&mut context, &path_to_lib, CrateType::Library); + let library_crate = prepare_crate(&mut context, &path_to_lib, CrateType::Library); propagate_dep(&mut context, library_crate, &crate_name.parse().unwrap()); } } diff --git a/crates/nargo_cli/src/cli/mod.rs b/crates/nargo_cli/src/cli/mod.rs index 8ce66db1b7b..9d494b21e6a 100644 --- a/crates/nargo_cli/src/cli/mod.rs +++ b/crates/nargo_cli/src/cli/mod.rs @@ -92,7 +92,7 @@ pub fn start_cli() -> eyre::Result<()> { #[cfg(test)] mod tests { use fm::FileManager; - use noirc_driver::{check_crate, create_local_crate}; + use noirc_driver::{check_crate, prepare_crate}; use noirc_errors::reporter; use noirc_frontend::{ graph::{CrateGraph, CrateType}, @@ -110,7 +110,7 @@ mod tests { let fm = FileManager::new(root_dir); let graph = CrateGraph::default(); let mut context = Context::new(fm, graph); - let crate_id = create_local_crate(&mut context, root_file, CrateType::Binary); + let crate_id = prepare_crate(&mut context, root_file, CrateType::Binary); let result = check_crate(&mut context, crate_id, false); let success = result.is_ok(); diff --git a/crates/nargo_cli/src/lib.rs b/crates/nargo_cli/src/lib.rs index b456d31c0ca..05753f7f3d8 100644 --- a/crates/nargo_cli/src/lib.rs +++ b/crates/nargo_cli/src/lib.rs @@ -9,7 +9,7 @@ use fm::FileManager; use nargo::package::{Dependency, Package}; -use noirc_driver::{add_dep, create_local_crate, create_non_local_crate}; +use noirc_driver::{add_dep, prepare_crate}; use noirc_frontend::{ graph::{CrateGraph, CrateId, CrateName, CrateType}, hir::Context, @@ -107,8 +107,7 @@ fn prepare_dependencies( for (dep_name, dep) in dependencies.into_iter() { match dep { Dependency::Remote { package } | Dependency::Local { package } => { - let crate_id = - create_non_local_crate(context, &package.entry_path, package.crate_type); + let crate_id = prepare_crate(context, &package.entry_path, package.crate_type); add_dep(context, parent_crate, crate_id, dep_name); prepare_dependencies(context, crate_id, package.dependencies.to_owned()); } @@ -121,7 +120,7 @@ fn prepare_package(package: &Package) -> (Context, CrateId) { let graph = CrateGraph::default(); let mut context = Context::new(fm, graph); - let crate_id = create_local_crate(&mut context, &package.entry_path, package.crate_type); + let crate_id = prepare_crate(&mut context, &package.entry_path, package.crate_type); prepare_dependencies(&mut context, crate_id, package.dependencies.to_owned()); diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs index c0957313f69..4d1b7fe2675 100644 --- a/crates/noirc_driver/src/lib.rs +++ b/crates/noirc_driver/src/lib.rs @@ -52,40 +52,17 @@ pub fn compile_file( context: &mut Context, root_file: &Path, ) -> Result<(CompiledProgram, Warnings), ErrorsAndWarnings> { - let crate_id = create_local_crate(context, root_file, CrateType::Binary); + let crate_id = prepare_crate(context, root_file, CrateType::Binary); compile_main(context, crate_id, &CompileOptions::default()) } -/// Adds the File with the local crate root to the file system -/// and adds the local crate to the graph -/// XXX: This may pose a problem with workspaces, where you can change the local crate and where -/// we have multiple binaries in one workspace -/// A Fix would be for the driver instance to store the local crate id. -// Granted that this is the only place which relies on the local crate being first -pub fn create_local_crate( - context: &mut Context, - file_name: &Path, - crate_type: CrateType, -) -> CrateId { +/// Adds the file from the file system at `Path` to the crate graph +pub fn prepare_crate(context: &mut Context, file_name: &Path, crate_type: CrateType) -> CrateId { let root_file_id = context.file_manager.add_file(file_name).unwrap(); context.crate_graph.add_crate_root(crate_type, root_file_id) } -/// Creates a Non Local Crate. A Non Local Crate is any crate which is the not the crate that -/// the compiler is compiling. -pub fn create_non_local_crate( - context: &mut Context, - file_name: &Path, - crate_type: CrateType, -) -> CrateId { - let root_file_id = context.file_manager.add_file(file_name).unwrap(); - - // You can add any crate type to the crate graph - // but you cannot depend on Binaries - context.crate_graph.add_crate_root(crate_type, root_file_id) -} - /// Adds a edge in the crate graph for two crates pub fn add_dep( context: &mut Context, diff --git a/crates/wasm/src/compile.rs b/crates/wasm/src/compile.rs index c940f0ce246..15d8d5107ea 100644 --- a/crates/wasm/src/compile.rs +++ b/crates/wasm/src/compile.rs @@ -3,8 +3,8 @@ use fm::FileManager; use gloo_utils::format::JsValueSerdeExt; use log::debug; use noirc_driver::{ - check_crate, compile_contracts, compile_no_check, create_local_crate, create_non_local_crate, - propagate_dep, CompileOptions, CompiledContract, + check_crate, compile_contracts, compile_no_check, prepare_crate, propagate_dep, CompileOptions, + CompiledContract, }; use noirc_frontend::{ graph::{CrateGraph, CrateType}, @@ -63,7 +63,7 @@ impl Default for WASMCompileOptions { fn add_noir_lib(context: &mut Context, crate_name: &str) { let path_to_lib = Path::new(&crate_name).join("lib.nr"); - let library_crate = create_non_local_crate(context, &path_to_lib, CrateType::Library); + let library_crate = prepare_crate(context, &path_to_lib, CrateType::Library); propagate_dep(context, library_crate, &crate_name.parse().unwrap()); } @@ -87,7 +87,7 @@ pub fn compile(args: JsValue) -> JsValue { let mut context = Context::new(fm, graph); let path = Path::new(&options.entry_point); - let crate_id = create_local_crate(&mut context, path, CrateType::Binary); + let crate_id = prepare_crate(&mut context, path, CrateType::Binary); for dependency in options.optional_dependencies_set { add_noir_lib(&mut context, dependency.as_str()); From f7742ab026092f129bd4ec4f122bcd3249100529 Mon Sep 17 00:00:00 2001 From: jfecher Date: Wed, 2 Aug 2023 03:59:08 -0500 Subject: [PATCH 23/50] fix: flattening pass no longer overwrites previously mapped condition values (#2117) * Fix flattening pass overwriting previously mapped values * chore: add backticks to variable names in comment --------- Co-authored-by: Tom French <15848336+TomAFrench@users.noreply.github.com> --- .../test_data/regression_2099/Nargo.toml | 6 +++ .../test_data/regression_2099/src/main.nr | 37 +++++++++++++++++++ .../src/ssa_refactor/ir/function_inserter.rs | 1 - .../src/ssa_refactor/opt/flatten_cfg.rs | 5 ++- 4 files changed, 47 insertions(+), 2 deletions(-) create mode 100644 crates/nargo_cli/tests/test_data/regression_2099/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/regression_2099/src/main.nr diff --git a/crates/nargo_cli/tests/test_data/regression_2099/Nargo.toml b/crates/nargo_cli/tests/test_data/regression_2099/Nargo.toml new file mode 100644 index 00000000000..ca96e7164a5 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/regression_2099/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "regression_2099" +authors = [""] +compiler_version = "0.9.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/regression_2099/src/main.nr b/crates/nargo_cli/tests/test_data/regression_2099/src/main.nr new file mode 100644 index 00000000000..b96e664dedf --- /dev/null +++ b/crates/nargo_cli/tests/test_data/regression_2099/src/main.nr @@ -0,0 +1,37 @@ +use dep::std::ec::tecurve::affine::Curve as AffineCurve; +use dep::std::ec::tecurve::affine::Point as Gaffine; +use dep::std::ec::tecurve::curvegroup::Curve; +use dep::std::ec::tecurve::curvegroup::Point as G; + +use dep::std::ec::swcurve::affine::Point as SWGaffine; +use dep::std::ec::swcurve::curvegroup::Point as SWG; + +use dep::std::ec::montcurve::affine::Point as MGaffine; +use dep::std::ec::montcurve::curvegroup::Point as MG; + +fn main() { + // Define Baby Jubjub (ERC-2494) parameters in affine representation + let bjj_affine = AffineCurve::new(168700, 168696, Gaffine::new(995203441582195749578291179787384436505546430278305826713579947235728471134,5472060717959818805561601436314318772137091100104008585924551046643952123905)); + + // Test addition + let p1_affine = Gaffine::new(17777552123799933955779906779655732241715742912184938656739573121738514868268, 2626589144620713026669568689430873010625803728049924121243784502389097019475); + let p2_affine = Gaffine::new(16540640123574156134436876038791482806971768689494387082833631921987005038935, 20819045374670962167435360035096875258406992893633759881276124905556507972311); + let _p3_affine = bjj_affine.add(p1_affine, p2_affine); + + // Test SWCurve equivalents of the above + // First the affine representation + let bjj_swcurve_affine = bjj_affine.into_swcurve(); + + let p1_swcurve_affine = bjj_affine.map_into_swcurve(p1_affine); + let p2_swcurve_affine = bjj_affine.map_into_swcurve(p2_affine); + + let _p3_swcurve_affine_from_add = bjj_swcurve_affine.add( + p1_swcurve_affine, + p2_swcurve_affine + ); + + // Check that these points are on the curve + assert( + bjj_swcurve_affine.contains(p1_swcurve_affine) + ); +} diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs index 38dcfbbb168..15c755f40c2 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs @@ -124,7 +124,6 @@ impl<'f> FunctionInserter<'f> { let old_parameters = self.function.dfg.block_parameters(block); for (param, new_param) in old_parameters.iter().zip(new_values) { - // Don't overwrite any existing entries to avoid overwriting the induction variable self.values.entry(*param).or_insert(*new_param); } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs index 4ff857f942f..fdc4be085d7 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs @@ -274,7 +274,10 @@ impl<'f> Context<'f> { // end, in addition to resetting the value of old_condition since it is set to // known to be true/false within the then/else branch respectively. self.insert_current_side_effects_enabled(); - self.inserter.map_value(old_condition, old_condition); + + // We must map back to `then_condition` here. Mapping `old_condition` to itself would + // lose any previous mappings. + self.inserter.map_value(old_condition, then_condition); // While there is a condition on the stack we don't compile outside the condition // until it is popped. This ensures we inline the full then and else branches From 50b2816099a021e4b8cb44a9017fb849abf014e6 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Wed, 2 Aug 2023 14:20:28 +0100 Subject: [PATCH 24/50] feat: Add additional `BinaryOp` simplifications (#2124) feat: add additional `BinaryOp` simplifictions --- .../src/ssa_refactor/ir/instruction.rs | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs index b7a3ea02ae9..6d74a99e002 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs @@ -733,6 +733,9 @@ impl Binary { let zero = dfg.make_constant(FieldElement::zero(), operand_type); return SimplifyResult::SimplifiedTo(zero); } + if dfg.resolve(self.lhs) == dfg.resolve(self.rhs) { + return SimplifyResult::SimplifiedTo(self.lhs); + } } BinaryOp::Or => { if lhs_is_zero { @@ -741,8 +744,17 @@ impl Binary { if rhs_is_zero { return SimplifyResult::SimplifiedTo(self.lhs); } + if dfg.resolve(self.lhs) == dfg.resolve(self.rhs) { + return SimplifyResult::SimplifiedTo(self.lhs); + } } BinaryOp::Xor => { + if lhs_is_zero { + return SimplifyResult::SimplifiedTo(self.rhs); + } + if rhs_is_zero { + return SimplifyResult::SimplifiedTo(self.lhs); + } if dfg.resolve(self.lhs) == dfg.resolve(self.rhs) { let zero = dfg.make_constant(FieldElement::zero(), Type::bool()); return SimplifyResult::SimplifiedTo(zero); From b0fbc536dc432ba8d3ab6c12462758b11c2c21c4 Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Wed, 2 Aug 2023 15:52:35 +0200 Subject: [PATCH 25/50] feat: Add support for bitshifts by distances known at runtime (#2072) * remove shr and shl from ssa instruction * move bit_shift_runtime test to test_data * code review, fix typo * Forbid signed integers for bit shift and fix brillig failing test * Check for signeness also during the delayed checks * Add missing method * Code review * Code review --- .../test_data/bit_shifts_runtime/Nargo.toml | 6 ++ .../test_data/bit_shifts_runtime/Prover.toml | 2 + .../test_data/bit_shifts_runtime/src/main.nr | 9 +++ .../src/brillig/brillig_gen/brillig_block.rs | 24 +++--- .../src/brillig/brillig_gen/brillig_fn.rs | 7 -- .../noirc_evaluator/src/brillig/brillig_ir.rs | 12 +++ .../src/brillig/brillig_ir/debug_show.rs | 5 +- .../src/ssa_refactor/acir_gen/mod.rs | 7 -- .../src/ssa_refactor/ir/instruction.rs | 20 ----- .../src/ssa_refactor/ssa_gen/context.rs | 77 +++++++++++++++---- crates/noirc_frontend/src/ast/expression.rs | 4 + .../noirc_frontend/src/hir/type_check/expr.rs | 20 ++++- crates/noirc_frontend/src/hir_def/expr.rs | 4 + crates/noirc_frontend/src/hir_def/types.rs | 4 + 14 files changed, 132 insertions(+), 69 deletions(-) create mode 100644 crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml new file mode 100644 index 00000000000..661f4f937d5 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "bit_shifts_runtime" +authors = [""] +compiler_version = "0.1" + +[dependencies] diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml new file mode 100644 index 00000000000..98d8630792e --- /dev/null +++ b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml @@ -0,0 +1,2 @@ +x = 64 +y = 1 \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr new file mode 100644 index 00000000000..271a1ecb880 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr @@ -0,0 +1,9 @@ +fn main(x: u64, y: u64) { + // runtime shifts on comptime values + assert(64 << y == 128); + assert(64 >> y == 32); + + // runtime shifts on runtime values + assert(x << y == 128); + assert(x >> y == 32); +} \ No newline at end of file diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs index c7779533a8a..a9bbe189e57 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs @@ -336,10 +336,10 @@ impl<'block> BrilligBlock<'block> { dfg.instruction_results(instruction_id)[0], dfg, ); - + let heap_vec = self.brillig_context.extract_heap_vector(target_slice); self.brillig_context.radix_instruction( source, - self.function_context.extract_heap_vector(target_slice), + heap_vec, radix, limb_count, matches!(endianness, Endian::Big), @@ -355,10 +355,10 @@ impl<'block> BrilligBlock<'block> { ); let radix = self.brillig_context.make_constant(2_usize.into()); - + let heap_vec = self.brillig_context.extract_heap_vector(target_slice); self.brillig_context.radix_instruction( source, - self.function_context.extract_heap_vector(target_slice), + heap_vec, radix, limb_count, matches!(endianness, Endian::Big), @@ -589,7 +589,7 @@ impl<'block> BrilligBlock<'block> { dfg.instruction_results(instruction_id)[0], dfg, ); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); let item_value = self.convert_ssa_register_value(arguments[1], dfg); slice_push_back_operation( self.brillig_context, @@ -604,7 +604,7 @@ impl<'block> BrilligBlock<'block> { dfg.instruction_results(instruction_id)[0], dfg, ); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); let item_value = self.convert_ssa_register_value(arguments[1], dfg); slice_push_front_operation( self.brillig_context, @@ -618,7 +618,7 @@ impl<'block> BrilligBlock<'block> { let target_variable = self.function_context.create_variable(self.brillig_context, results[0], dfg); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); let pop_item = self.function_context.create_register_variable( self.brillig_context, @@ -643,7 +643,7 @@ impl<'block> BrilligBlock<'block> { ); let target_variable = self.function_context.create_variable(self.brillig_context, results[1], dfg); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); slice_pop_front_operation( self.brillig_context, @@ -659,7 +659,7 @@ impl<'block> BrilligBlock<'block> { let target_variable = self.function_context.create_variable(self.brillig_context, results[0], dfg); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); slice_insert_operation( self.brillig_context, target_vector, @@ -674,7 +674,7 @@ impl<'block> BrilligBlock<'block> { let target_variable = self.function_context.create_variable(self.brillig_context, results[0], dfg); - let target_vector = self.function_context.extract_heap_vector(target_variable); + let target_vector = self.brillig_context.extract_heap_vector(target_variable); let removed_item_register = self.function_context.create_register_variable( self.brillig_context, @@ -877,7 +877,7 @@ impl<'block> BrilligBlock<'block> { Type::Slice(_) => { let variable = self.function_context.create_variable(self.brillig_context, result, dfg); - let vector = self.function_context.extract_heap_vector(variable); + let vector = self.brillig_context.extract_heap_vector(variable); // Set the pointer to the current stack frame // The stack pointer will then be update by the caller of this method @@ -981,8 +981,6 @@ pub(crate) fn convert_ssa_binary_op_to_brillig_binary_op( BinaryOp::And => BinaryIntOp::And, BinaryOp::Or => BinaryIntOp::Or, BinaryOp::Xor => BinaryIntOp::Xor, - BinaryOp::Shl => BinaryIntOp::Shl, - BinaryOp::Shr => BinaryIntOp::Shr, }; BrilligBinaryOp::Integer { op: operation, bit_size } diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs index 1a751d28b23..210d6da7be6 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs @@ -115,13 +115,6 @@ impl FunctionContext { } } - pub(crate) fn extract_heap_vector(&self, variable: RegisterOrMemory) -> HeapVector { - match variable { - RegisterOrMemory::HeapVector(vector) => vector, - _ => unreachable!("ICE: Expected vector, got {variable:?}"), - } - } - /// Collects the registers that a given variable is stored in. pub(crate) fn extract_registers(&self, variable: RegisterOrMemory) -> Vec { match variable { diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir.rs b/crates/noirc_evaluator/src/brillig/brillig_ir.rs index ac0103dd9ed..4471d507579 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_ir.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_ir.rs @@ -951,6 +951,18 @@ impl BrilligContext { self.deallocate_register(end_value_register); self.deallocate_register(index_at_end_of_array); } + + pub(crate) fn extract_heap_vector(&mut self, variable: RegisterOrMemory) -> HeapVector { + match variable { + RegisterOrMemory::HeapVector(vector) => vector, + RegisterOrMemory::HeapArray(array) => { + let size = self.allocate_register(); + self.const_instruction(size, array.size.into()); + HeapVector { pointer: array.pointer, size } + } + _ => unreachable!("ICE: Expected vector, got {variable:?}"), + } + } } /// Type to encapsulate the binary operation types in Brillig diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs b/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs index 75716e49177..2bb753de760 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs @@ -73,8 +73,9 @@ impl DebugToString for BinaryIntOp { BinaryIntOp::And => "&&".into(), BinaryIntOp::Or => "||".into(), BinaryIntOp::Xor => "^".into(), - BinaryIntOp::Shl => "<<".into(), - BinaryIntOp::Shr => ">>".into(), + BinaryIntOp::Shl | BinaryIntOp::Shr => { + unreachable!("bit shift should have been replaced") + } } } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index 4a7d2e46775..f00f15d8f05 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -796,13 +796,6 @@ impl Context { bit_count, self.current_side_effects_enabled_var, ), - BinaryOp::Shl => self.acir_context.shift_left_var(lhs, rhs, binary_type), - BinaryOp::Shr => self.acir_context.shift_right_var( - lhs, - rhs, - binary_type, - self.current_side_effects_enabled_var, - ), BinaryOp::Xor => self.acir_context.xor_var(lhs, rhs, binary_type), BinaryOp::And => self.acir_context.and_var(lhs, rhs, binary_type), BinaryOp::Or => self.acir_context.or_var(lhs, rhs, binary_type), diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs index 6d74a99e002..a56b12ab875 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs @@ -760,16 +760,6 @@ impl Binary { return SimplifyResult::SimplifiedTo(zero); } } - BinaryOp::Shl => { - if rhs_is_zero { - return SimplifyResult::SimplifiedTo(self.lhs); - } - } - BinaryOp::Shr => { - if rhs_is_zero { - return SimplifyResult::SimplifiedTo(self.lhs); - } - } } SimplifyResult::None } @@ -825,8 +815,6 @@ impl BinaryOp { BinaryOp::And => None, BinaryOp::Or => None, BinaryOp::Xor => None, - BinaryOp::Shl => None, - BinaryOp::Shr => None, } } @@ -840,8 +828,6 @@ impl BinaryOp { BinaryOp::And => |x, y| Some(x & y), BinaryOp::Or => |x, y| Some(x | y), BinaryOp::Xor => |x, y| Some(x ^ y), - BinaryOp::Shl => |x, y| x.checked_shl(y.try_into().ok()?), - BinaryOp::Shr => |x, y| Some(x >> y), BinaryOp::Eq => |x, y| Some((x == y) as u128), BinaryOp::Lt => |x, y| Some((x < y) as u128), } @@ -882,10 +868,6 @@ pub(crate) enum BinaryOp { Or, /// Bitwise xor (^) Xor, - /// Shift lhs left by rhs bits (<<) - Shl, - /// Shift lhs right by rhs bits (>>) - Shr, } impl std::fmt::Display for BinaryOp { @@ -901,8 +883,6 @@ impl std::fmt::Display for BinaryOp { BinaryOp::And => write!(f, "and"), BinaryOp::Or => write!(f, "or"), BinaryOp::Xor => write!(f, "xor"), - BinaryOp::Shl => write!(f, "shl"), - BinaryOp::Shr => write!(f, "shr"), } } } diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs index c485200a53e..a526d93f85b 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs @@ -7,12 +7,12 @@ use iter_extended::vecmap; use noirc_errors::Location; use noirc_frontend::monomorphization::ast::{self, LocalId, Parameters}; use noirc_frontend::monomorphization::ast::{FuncId, Program}; -use noirc_frontend::Signedness; +use noirc_frontend::{BinaryOpKind, Signedness}; use crate::ssa_refactor::ir::dfg::DataFlowGraph; use crate::ssa_refactor::ir::function::FunctionId as IrFunctionId; use crate::ssa_refactor::ir::function::{Function, RuntimeType}; -use crate::ssa_refactor::ir::instruction::BinaryOp; +use crate::ssa_refactor::ir::instruction::{BinaryOp, Endian, Intrinsic}; use crate::ssa_refactor::ir::map::AtomicCounter; use crate::ssa_refactor::ir::types::{NumericType, Type}; use crate::ssa_refactor::ir::value::ValueId; @@ -236,6 +236,46 @@ impl<'a> FunctionContext<'a> { Values::empty() } + /// Insert ssa instructions which computes lhs << rhs by doing lhs*2^rhs + fn insert_shift_left(&mut self, lhs: ValueId, rhs: ValueId) -> ValueId { + let base = self.builder.field_constant(FieldElement::from(2_u128)); + let pow = self.pow(base, rhs); + self.builder.insert_binary(lhs, BinaryOp::Mul, pow) + } + + /// Insert ssa instructions which computes lhs << rhs by doing lhs/2^rhs + fn insert_shift_right(&mut self, lhs: ValueId, rhs: ValueId) -> ValueId { + let base = self.builder.field_constant(FieldElement::from(2_u128)); + let pow = self.pow(base, rhs); + self.builder.insert_binary(lhs, BinaryOp::Div, pow) + } + + /// Computes lhs^rhs via square&multiply, using the bits decomposition of rhs + fn pow(&mut self, lhs: ValueId, rhs: ValueId) -> ValueId { + let typ = self.builder.current_function.dfg.type_of_value(rhs); + if let Type::Numeric(NumericType::Unsigned { bit_size }) = typ { + let to_bits = self.builder.import_intrinsic_id(Intrinsic::ToBits(Endian::Little)); + let length = self.builder.field_constant(FieldElement::from(bit_size as i128)); + let result_types = vec![Type::Array(Rc::new(vec![Type::bool()]), bit_size as usize)]; + let rhs_bits = self.builder.insert_call(to_bits, vec![rhs, length], result_types)[0]; + let one = self.builder.field_constant(FieldElement::one()); + let mut r = one; + for i in 1..bit_size + 1 { + let r1 = self.builder.insert_binary(r, BinaryOp::Mul, r); + let a = self.builder.insert_binary(r1, BinaryOp::Mul, lhs); + let idx = self.builder.field_constant(FieldElement::from((bit_size - i) as i128)); + let b = self.builder.insert_array_get(rhs_bits, idx, Type::field()); + let r2 = self.builder.insert_binary(a, BinaryOp::Mul, b); + let c = self.builder.insert_binary(one, BinaryOp::Sub, b); + let r3 = self.builder.insert_binary(c, BinaryOp::Mul, r1); + r = self.builder.insert_binary(r2, BinaryOp::Add, r3); + } + r + } else { + unreachable!("Value must be unsigned in power operation"); + } + } + /// Insert a binary instruction at the end of the current block. /// Converts the form of the binary instruction as necessary /// (e.g. swapping arguments, inserting a not) to represent it in the IR. @@ -247,17 +287,22 @@ impl<'a> FunctionContext<'a> { mut rhs: ValueId, location: Location, ) -> Values { - let op = convert_operator(operator); - - if op == BinaryOp::Eq && matches!(self.builder.type_of_value(lhs), Type::Array(..)) { - return self.insert_array_equality(lhs, operator, rhs, location); - } - - if operator_requires_swapped_operands(operator) { - std::mem::swap(&mut lhs, &mut rhs); - } - - let mut result = self.builder.set_location(location).insert_binary(lhs, op, rhs); + let mut result = match operator { + BinaryOpKind::ShiftLeft => self.insert_shift_left(lhs, rhs), + BinaryOpKind::ShiftRight => self.insert_shift_right(lhs, rhs), + BinaryOpKind::Equal | BinaryOpKind::NotEqual + if matches!(self.builder.type_of_value(lhs), Type::Array(..)) => + { + return self.insert_array_equality(lhs, operator, rhs, location) + } + _ => { + let op = convert_operator(operator); + if operator_requires_swapped_operands(operator) { + std::mem::swap(&mut lhs, &mut rhs); + } + self.builder.set_location(location).insert_binary(lhs, op, rhs) + } + }; if let Some(max_bit_size) = operator_result_max_bit_size_to_truncate( operator, @@ -704,7 +749,6 @@ fn operator_result_max_bit_size_to_truncate( /// checking operator_requires_not and operator_requires_swapped_operands /// to represent the full operation correctly. fn convert_operator(op: noirc_frontend::BinaryOpKind) -> BinaryOp { - use noirc_frontend::BinaryOpKind; match op { BinaryOpKind::Add => BinaryOp::Add, BinaryOpKind::Subtract => BinaryOp::Sub, @@ -720,8 +764,9 @@ fn convert_operator(op: noirc_frontend::BinaryOpKind) -> BinaryOp { BinaryOpKind::And => BinaryOp::And, BinaryOpKind::Or => BinaryOp::Or, BinaryOpKind::Xor => BinaryOp::Xor, - BinaryOpKind::ShiftRight => BinaryOp::Shr, - BinaryOpKind::ShiftLeft => BinaryOp::Shl, + BinaryOpKind::ShiftRight | BinaryOpKind::ShiftLeft => unreachable!( + "ICE - bit shift operators do not exist in SSA and should have been replaced" + ), } } diff --git a/crates/noirc_frontend/src/ast/expression.rs b/crates/noirc_frontend/src/ast/expression.rs index b1829e8c1ee..b1170ff0ed0 100644 --- a/crates/noirc_frontend/src/ast/expression.rs +++ b/crates/noirc_frontend/src/ast/expression.rs @@ -268,6 +268,10 @@ impl BinaryOpKind { BinaryOpKind::Modulo => Token::Percent, } } + + pub fn is_bit_shift(&self) -> bool { + matches!(self, BinaryOpKind::ShiftRight | BinaryOpKind::ShiftLeft) + } } #[derive(PartialEq, PartialOrd, Eq, Ord, Hash, Debug, Copy, Clone)] diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index 12c11bf20e1..24ac5f3443e 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -12,7 +12,7 @@ use crate::{ }, node_interner::{DefinitionKind, ExprId, FuncId}, token::Attribute::Deprecated, - CompTime, Shared, TypeBinding, TypeVariableKind, UnaryOp, + CompTime, Shared, Signedness, TypeBinding, TypeVariableKind, UnaryOp, }; use super::{errors::TypeCheckError, TypeChecker}; @@ -954,7 +954,7 @@ impl<'interner> TypeChecker<'interner> { if op.is_bitwise() && (other.is_bindable() || other.is_field()) { let other = other.follow_bindings(); - + let kind = op.kind; // This will be an error if these types later resolve to a Field, or stay // polymorphic as the bit size will be unknown. Delay this error until the function // finishes resolving so we can still allow cases like `let x: u8 = 1 << 2;`. @@ -963,6 +963,12 @@ impl<'interner> TypeChecker<'interner> { Err(TypeCheckError::InvalidBitwiseOperationOnField { span }) } else if other.is_bindable() { Err(TypeCheckError::AmbiguousBitWidth { span }) + } else if kind.is_bit_shift() && other.is_signed() { + Err(TypeCheckError::TypeCannotBeUsed { + typ: other, + place: "bit shift", + span, + }) } else { Ok(()) } @@ -1001,8 +1007,14 @@ impl<'interner> TypeChecker<'interner> { span, }); } - let comptime = comptime_x.and(comptime_y, op.location.span); - Ok(Integer(comptime, *sign_x, *bit_width_x)) + if op.is_bit_shift() + && (*sign_x == Signedness::Signed || *sign_y == Signedness::Signed) + { + Err(TypeCheckError::InvalidInfixOp { kind: "Signed integer", span }) + } else { + let comptime = comptime_x.and(comptime_y, op.location.span); + Ok(Integer(comptime, *sign_x, *bit_width_x)) + } } (Integer(..), FieldElement(..)) | (FieldElement(..), Integer(..)) => { Err(TypeCheckError::IntegerAndFieldBinaryOperation { span }) diff --git a/crates/noirc_frontend/src/hir_def/expr.rs b/crates/noirc_frontend/src/hir_def/expr.rs index 5db9751591a..db7db0a803d 100644 --- a/crates/noirc_frontend/src/hir_def/expr.rs +++ b/crates/noirc_frontend/src/hir_def/expr.rs @@ -72,6 +72,10 @@ impl HirBinaryOp { use BinaryOpKind::*; matches!(self.kind, And | Or | Xor | ShiftRight | ShiftLeft) } + + pub fn is_bit_shift(&self) -> bool { + self.kind.is_bit_shift() + } } #[derive(Debug, Clone)] diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs index df4c2f6c229..ff0a4e53fae 100644 --- a/crates/noirc_frontend/src/hir_def/types.rs +++ b/crates/noirc_frontend/src/hir_def/types.rs @@ -659,6 +659,10 @@ impl Type { matches!(self.follow_bindings(), Type::FieldElement(_)) } + pub fn is_signed(&self) -> bool { + matches!(self.follow_bindings(), Type::Integer(_, Signedness::Signed, _)) + } + fn contains_numeric_typevar(&self, target_id: TypeVariableId) -> bool { // True if the given type is a NamedGeneric with the target_id let named_generic_id_matches_target = |typ: &Type| { From 292724fc8b4d3791a87a829ce8d87a1a537dfcc5 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Wed, 2 Aug 2023 15:19:40 +0100 Subject: [PATCH 26/50] chore: create a `const` to hold the panic message (#2122) chore: create a const to hold the panic message --- crates/nargo_cli/src/main.rs | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/crates/nargo_cli/src/main.rs b/crates/nargo_cli/src/main.rs index a73785c64c6..a79c43dad48 100644 --- a/crates/nargo_cli/src/main.rs +++ b/crates/nargo_cli/src/main.rs @@ -3,12 +3,12 @@ use color_eyre::{config::HookBuilder, eyre}; use nargo_cli::cli::start_cli; +const PANIC_MESSAGE: &str = "This is a bug. We may have already fixed this in newer versions of Nargo so try searching for similar issues at https://github.com/noir-lang/noir/issues/.\nIf there isn't an open issue for this bug, consider opening one at https://github.com/noir-lang/noir/issues/new?labels=bug&template=bug_report.yml"; + fn main() -> eyre::Result<()> { // Register a panic hook to display more readable panic messages to end-users - let (panic_hook, _) = HookBuilder::default() - .display_env_section(false) - .panic_section("This is a bug. We may have already fixed this in newer versions of Nargo so try searching for similar issues at https://github.com/noir-lang/noir/issues/.\nIf there isn't an open issue for this bug, consider opening one at https://github.com/noir-lang/noir/issues/new?labels=bug&template=bug_report.yml") - .into_hooks(); + let (panic_hook, _) = + HookBuilder::default().display_env_section(false).panic_section(PANIC_MESSAGE).into_hooks(); panic_hook.install(); start_cli() From 435ab3520d06b6b4f898d41a5ad403c5ddbd7771 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Wed, 2 Aug 2023 16:51:04 +0100 Subject: [PATCH 27/50] feat: replace boolean `AND`s with multiplication (#1954) * feat: replace boolean `AND`s with multiplication * chore: move optimisation to live within ssa-gen * chore: fill out message in `unreachable` * chore: remove `SimplifyResult::None` * chore: abstract away `SimplifyResult::SimplifiedToInstruction(None)` * Revert "chore: abstract away `SimplifyResult::SimplifiedToInstruction(None)`" This reverts commit a7736eb418944864ff9a67b07aea01e7ba0bdb17. * Revert "chore: remove `SimplifyResult::None`" This reverts commit 429ccd473883ac3b210dda3eac59d780a0b45a2f. * chore: add `SimplifyResult.instruction()` --- .../noirc_evaluator/src/ssa_refactor/ir/dfg.rs | 3 ++- .../src/ssa_refactor/ir/instruction.rs | 17 +++++++++++++++++ 2 files changed, 19 insertions(+), 1 deletion(-) diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs index caf65c85a7e..6d74e49b03b 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs @@ -158,7 +158,8 @@ impl DataFlowGraph { SimplifiedToMultiple(simplification) } SimplifyResult::Remove => InstructionRemoved, - SimplifyResult::None => { + result @ (SimplifyResult::SimplifiedToInstruction(_) | SimplifyResult::None) => { + let instruction = result.instruction().unwrap_or(instruction); let id = self.make_instruction(instruction, ctrl_typevars); self.blocks[block].insert_instruction(id); if let Some(location) = location { diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs index a56b12ab875..afb47d423e2 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs @@ -736,6 +736,11 @@ impl Binary { if dfg.resolve(self.lhs) == dfg.resolve(self.rhs) { return SimplifyResult::SimplifiedTo(self.lhs); } + if operand_type == Type::bool() { + // Boolean AND is equivalent to multiplication, which is a cheaper operation. + let instruction = Instruction::binary(BinaryOp::Mul, self.lhs, self.rhs); + return SimplifyResult::SimplifiedToInstruction(instruction); + } } BinaryOp::Or => { if lhs_is_zero { @@ -898,9 +903,21 @@ pub(crate) enum SimplifyResult { /// a function such as a tuple SimplifiedToMultiple(Vec), + /// Replace this function with an simpler but equivalent function. + SimplifiedToInstruction(Instruction), + /// Remove the instruction, it is unnecessary Remove, /// Instruction could not be simplified None, } + +impl SimplifyResult { + pub(crate) fn instruction(self) -> Option { + match self { + SimplifyResult::SimplifiedToInstruction(instruction) => Some(instruction), + _ => None, + } + } +} From 8a1ace792c4550ab1ce8c6044794abdb39d02872 Mon Sep 17 00:00:00 2001 From: jfecher Date: Wed, 2 Aug 2023 11:06:00 -0500 Subject: [PATCH 28/50] fix: Rename `Option::value` to `Option::_value` (#2127) * Rename Option::value to Option::_value * Add unwrap_unchecked method --- noir_stdlib/src/option.nr | 33 ++++++++++++++++++++------------- 1 file changed, 20 insertions(+), 13 deletions(-) diff --git a/noir_stdlib/src/option.nr b/noir_stdlib/src/option.nr index 5cc4dfae887..919c40fd9e0 100644 --- a/noir_stdlib/src/option.nr +++ b/noir_stdlib/src/option.nr @@ -1,17 +1,17 @@ struct Option { _is_some: bool, - value: T, + _value: T, } impl Option { /// Constructs a None value fn none() -> Self { - Self { _is_some: false, value: crate::unsafe::zeroed() } + Self { _is_some: false, _value: crate::unsafe::zeroed() } } /// Constructs a Some wrapper around the given value - fn some(value: T) -> Self { - Self { _is_some: true, value } + fn some(_value: T) -> Self { + Self { _is_some: true, _value } } /// True if this Option is None @@ -27,13 +27,20 @@ impl Option { /// Asserts `self.is_some()` and returns the wrapped value. fn unwrap(self) -> T { assert(self._is_some); - self.value + self._value + } + + /// Returns the inner value without asserting `self.is_some()` + /// Note that if `self` is `None`, there is no guarantee what value will be returned, + /// only that it will be of type `T`. + fn unwrap_unchecked(self) -> T { + self._value } /// Returns the wrapped value if `self.is_some()`. Otherwise, returns the given default value. fn unwrap_or(self, default: T) -> T { if self._is_some { - self.value + self._value } else { default } @@ -43,7 +50,7 @@ impl Option { /// a default value. fn unwrap_or_else(self, default: fn() -> T) -> T { if self._is_some { - self.value + self._value } else { default() } @@ -52,7 +59,7 @@ impl Option { /// If self is `Some(x)`, this returns `Some(f(x))`. Otherwise, this returns `None`. fn map(self, f: fn(T) -> U) -> Option { if self._is_some { - Option::some(f(self.value)) + Option::some(f(self._value)) } else { Option::none() } @@ -61,7 +68,7 @@ impl Option { /// If self is `Some(x)`, this returns `f(x)`. Otherwise, this returns the given default value. fn map_or(self, default: U, f: fn(T) -> U) -> U { if self._is_some { - f(self.value) + f(self._value) } else { default } @@ -70,7 +77,7 @@ impl Option { /// If self is `Some(x)`, this returns `f(x)`. Otherwise, this returns `default()`. fn map_or_else(self, default: fn() -> U, f: fn(T) -> U) -> U { if self._is_some { - f(self.value) + f(self._value) } else { default() } @@ -91,7 +98,7 @@ impl Option { /// In some languages this function is called `flat_map` or `bind`. fn and_then(self, f: fn(T) -> Option) -> Option { if self._is_some { - f(self.value) + f(self._value) } else { Option::none() } @@ -135,7 +142,7 @@ impl Option { /// Otherwise, this returns `None` fn filter(self, predicate: fn(T) -> bool) -> Self { if self._is_some { - if predicate(self.value) { + if predicate(self._value) { self } else { Option::none() @@ -149,7 +156,7 @@ impl Option { /// This returns None if the outer Option is None. Otherwise, this returns the inner Option. fn flatten(option: Option>) -> Option { if option._is_some { - option.value + option._value } else { Option::none() } From 47b372c1762ed1184bf2ed9b90d7dc3e2c161880 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Wed, 2 Aug 2023 17:17:29 +0100 Subject: [PATCH 29/50] feat: Optimize away constant calls to black box functions (#1981) * feat: optimize away constant calls to black box functions * chore: remove `use SimplifyResult::*` * chore: remove unnecessary match arms * Update crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs * Update crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs --------- Co-authored-by: jfecher --- .../src/ssa_refactor/ir/instruction.rs | 156 +------- .../src/ssa_refactor/ir/instruction/call.rs | 334 ++++++++++++++++++ 2 files changed, 338 insertions(+), 152 deletions(-) create mode 100644 crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs index afb47d423e2..7edb74f4206 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs @@ -1,5 +1,3 @@ -use std::rc::Rc; - use acvm::{acir::BlackBoxFunc, FieldElement}; use iter_extended::vecmap; use num_bigint::BigUint; @@ -14,6 +12,10 @@ use super::{ value::{Value, ValueId}, }; +mod call; + +use call::simplify_call; + /// Reference to an instruction /// /// Note that InstructionIds are not unique. That is, two InstructionIds @@ -385,156 +387,6 @@ fn simplify_cast(value: ValueId, dst_typ: &Type, dfg: &mut DataFlowGraph) -> Sim } } -/// Try to simplify this call instruction. If the instruction can be simplified to a known value, -/// that value is returned. Otherwise None is returned. -fn simplify_call(func: ValueId, arguments: &[ValueId], dfg: &mut DataFlowGraph) -> SimplifyResult { - use SimplifyResult::*; - let intrinsic = match &dfg[func] { - Value::Intrinsic(intrinsic) => *intrinsic, - _ => return None, - }; - - let constant_args: Option> = - arguments.iter().map(|value_id| dfg.get_numeric_constant(*value_id)).collect(); - - match intrinsic { - Intrinsic::ToBits(endian) => { - if let Some(constant_args) = constant_args { - let field = constant_args[0]; - let limb_count = constant_args[1].to_u128() as u32; - SimplifiedTo(constant_to_radix(endian, field, 2, limb_count, dfg)) - } else { - None - } - } - Intrinsic::ToRadix(endian) => { - if let Some(constant_args) = constant_args { - let field = constant_args[0]; - let radix = constant_args[1].to_u128() as u32; - let limb_count = constant_args[2].to_u128() as u32; - SimplifiedTo(constant_to_radix(endian, field, radix, limb_count, dfg)) - } else { - None - } - } - Intrinsic::ArrayLen => { - let slice = dfg.get_array_constant(arguments[0]); - if let Some((slice, _)) = slice { - SimplifiedTo(dfg.make_constant((slice.len() as u128).into(), Type::field())) - } else if let Some(length) = dfg.try_get_array_length(arguments[0]) { - SimplifiedTo(dfg.make_constant((length as u128).into(), Type::field())) - } else { - None - } - } - Intrinsic::SlicePushBack => { - let slice = dfg.get_array_constant(arguments[0]); - if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { - slice.push_back(elem); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedTo(new_slice) - } else { - None - } - } - Intrinsic::SlicePushFront => { - let slice = dfg.get_array_constant(arguments[0]); - if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { - slice.push_front(elem); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedTo(new_slice) - } else { - None - } - } - Intrinsic::SlicePopBack => { - let slice = dfg.get_array_constant(arguments[0]); - if let Some((mut slice, element_type)) = slice { - let elem = - slice.pop_back().expect("There are no elements in this slice to be removed"); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedToMultiple(vec![new_slice, elem]) - } else { - None - } - } - Intrinsic::SlicePopFront => { - let slice = dfg.get_array_constant(arguments[0]); - if let Some((mut slice, element_type)) = slice { - let elem = - slice.pop_front().expect("There are no elements in this slice to be removed"); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedToMultiple(vec![elem, new_slice]) - } else { - None - } - } - Intrinsic::SliceInsert => { - let slice = dfg.get_array_constant(arguments[0]); - let index = dfg.get_numeric_constant(arguments[1]); - if let (Some((mut slice, element_type)), Some(index), value) = - (slice, index, arguments[2]) - { - slice.insert(index.to_u128() as usize, value); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedTo(new_slice) - } else { - None - } - } - Intrinsic::SliceRemove => { - let slice = dfg.get_array_constant(arguments[0]); - let index = dfg.get_numeric_constant(arguments[1]); - if let (Some((mut slice, element_type)), Some(index)) = (slice, index) { - let removed_elem = slice.remove(index.to_u128() as usize); - let new_slice = dfg.make_array(slice, element_type); - SimplifiedToMultiple(vec![new_slice, removed_elem]) - } else { - None - } - } - Intrinsic::BlackBox(_) | Intrinsic::Println | Intrinsic::Sort => None, - } -} - -/// Returns a Value::Array of constants corresponding to the limbs of the radix decomposition. -fn constant_to_radix( - endian: Endian, - field: FieldElement, - radix: u32, - limb_count: u32, - dfg: &mut DataFlowGraph, -) -> ValueId { - let bit_size = u32::BITS - (radix - 1).leading_zeros(); - let radix_big = BigUint::from(radix); - assert_eq!(BigUint::from(2u128).pow(bit_size), radix_big, "ICE: Radix must be a power of 2"); - let big_integer = BigUint::from_bytes_be(&field.to_be_bytes()); - - // Decompose the integer into its radix digits in little endian form. - let decomposed_integer = big_integer.to_radix_le(radix); - let mut limbs = vecmap(0..limb_count, |i| match decomposed_integer.get(i as usize) { - Some(digit) => FieldElement::from_be_bytes_reduce(&[*digit]), - None => FieldElement::zero(), - }); - if endian == Endian::Big { - limbs.reverse(); - } - - // For legacy reasons (see #617) the to_radix interface supports 256 bits even though - // FieldElement::max_num_bits() is only 254 bits. Any limbs beyond the specified count - // become zero padding. - let max_decomposable_bits: u32 = 256; - let limb_count_with_padding = max_decomposable_bits / bit_size; - while limbs.len() < limb_count_with_padding as usize { - limbs.push(FieldElement::zero()); - } - let result_constants: im::Vector = - limbs.into_iter().map(|limb| dfg.make_constant(limb, Type::unsigned(bit_size))).collect(); - - let typ = Type::Array(Rc::new(vec![Type::unsigned(bit_size)]), result_constants.len()); - dfg.make_array(result_constants, typ) -} - /// The possible return values for Instruction::return_types pub(crate) enum InstructionResultType { /// The result type of this instruction matches that of this operand diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs new file mode 100644 index 00000000000..96998d92fcf --- /dev/null +++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs @@ -0,0 +1,334 @@ +use std::rc::Rc; + +use acvm::{acir::BlackBoxFunc, BlackBoxResolutionError, FieldElement}; +use iter_extended::vecmap; +use num_bigint::BigUint; + +use crate::ssa_refactor::ir::{ + dfg::DataFlowGraph, + instruction::Intrinsic, + map::Id, + types::Type, + value::{Value, ValueId}, +}; + +use super::{Endian, SimplifyResult}; + +/// Try to simplify this call instruction. If the instruction can be simplified to a known value, +/// that value is returned. Otherwise None is returned. +pub(super) fn simplify_call( + func: ValueId, + arguments: &[ValueId], + dfg: &mut DataFlowGraph, +) -> SimplifyResult { + let intrinsic = match &dfg[func] { + Value::Intrinsic(intrinsic) => *intrinsic, + _ => return SimplifyResult::None, + }; + + let constant_args: Option> = + arguments.iter().map(|value_id| dfg.get_numeric_constant(*value_id)).collect(); + + match intrinsic { + Intrinsic::ToBits(endian) => { + if let Some(constant_args) = constant_args { + let field = constant_args[0]; + let limb_count = constant_args[1].to_u128() as u32; + SimplifyResult::SimplifiedTo(constant_to_radix(endian, field, 2, limb_count, dfg)) + } else { + SimplifyResult::None + } + } + Intrinsic::ToRadix(endian) => { + if let Some(constant_args) = constant_args { + let field = constant_args[0]; + let radix = constant_args[1].to_u128() as u32; + let limb_count = constant_args[2].to_u128() as u32; + SimplifyResult::SimplifiedTo(constant_to_radix( + endian, field, radix, limb_count, dfg, + )) + } else { + SimplifyResult::None + } + } + Intrinsic::ArrayLen => { + let slice = dfg.get_array_constant(arguments[0]); + if let Some((slice, _)) = slice { + SimplifyResult::SimplifiedTo( + dfg.make_constant((slice.len() as u128).into(), Type::field()), + ) + } else if let Some(length) = dfg.try_get_array_length(arguments[0]) { + SimplifyResult::SimplifiedTo( + dfg.make_constant((length as u128).into(), Type::field()), + ) + } else { + SimplifyResult::None + } + } + Intrinsic::SlicePushBack => { + let slice = dfg.get_array_constant(arguments[0]); + if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { + slice.push_back(elem); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedTo(new_slice) + } else { + SimplifyResult::None + } + } + Intrinsic::SlicePushFront => { + let slice = dfg.get_array_constant(arguments[0]); + if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { + slice.push_front(elem); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedTo(new_slice) + } else { + SimplifyResult::None + } + } + Intrinsic::SlicePopBack => { + let slice = dfg.get_array_constant(arguments[0]); + if let Some((mut slice, element_type)) = slice { + let elem = + slice.pop_back().expect("There are no elements in this slice to be removed"); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedToMultiple(vec![new_slice, elem]) + } else { + SimplifyResult::None + } + } + Intrinsic::SlicePopFront => { + let slice = dfg.get_array_constant(arguments[0]); + if let Some((mut slice, element_type)) = slice { + let elem = + slice.pop_front().expect("There are no elements in this slice to be removed"); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedToMultiple(vec![elem, new_slice]) + } else { + SimplifyResult::None + } + } + Intrinsic::SliceInsert => { + let slice = dfg.get_array_constant(arguments[0]); + let index = dfg.get_numeric_constant(arguments[1]); + if let (Some((mut slice, element_type)), Some(index), value) = + (slice, index, arguments[2]) + { + slice.insert(index.to_u128() as usize, value); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedTo(new_slice) + } else { + SimplifyResult::None + } + } + Intrinsic::SliceRemove => { + let slice = dfg.get_array_constant(arguments[0]); + let index = dfg.get_numeric_constant(arguments[1]); + if let (Some((mut slice, element_type)), Some(index)) = (slice, index) { + let removed_elem = slice.remove(index.to_u128() as usize); + let new_slice = dfg.make_array(slice, element_type); + SimplifyResult::SimplifiedToMultiple(vec![new_slice, removed_elem]) + } else { + SimplifyResult::None + } + } + Intrinsic::BlackBox(bb_func) => simplify_black_box_func(bb_func, arguments, dfg), + Intrinsic::Println | Intrinsic::Sort => SimplifyResult::None, + } +} + +/// Try to simplify this black box call. If the call can be simplified to a known value, +/// that value is returned. Otherwise [`SimplifyResult::None`] is returned. +fn simplify_black_box_func( + bb_func: BlackBoxFunc, + arguments: &[ValueId], + dfg: &mut DataFlowGraph, +) -> SimplifyResult { + match bb_func { + BlackBoxFunc::SHA256 => simplify_hash(dfg, arguments, acvm::blackbox_solver::sha256), + BlackBoxFunc::Blake2s => simplify_hash(dfg, arguments, acvm::blackbox_solver::blake2s), + BlackBoxFunc::Keccak256 => { + match (dfg.get_array_constant(arguments[0]), dfg.get_numeric_constant(arguments[1])) { + (Some((input, _)), Some(num_bytes)) if array_is_constant(dfg, &input) => { + let input_bytes: Vec = to_u8_vec(dfg, input); + + let num_bytes = num_bytes.to_u128() as usize; + let truncated_input_bytes = &input_bytes[0..num_bytes]; + let hash = acvm::blackbox_solver::keccak256(truncated_input_bytes) + .expect("Rust solvable black box function should not fail"); + + let hash_values = + vecmap(hash, |byte| FieldElement::from_be_bytes_reduce(&[byte])); + + let result_array = make_constant_array(dfg, hash_values, Type::unsigned(8)); + SimplifyResult::SimplifiedTo(result_array) + } + _ => SimplifyResult::None, + } + } + BlackBoxFunc::HashToField128Security => match dfg.get_array_constant(arguments[0]) { + Some((input, _)) if array_is_constant(dfg, &input) => { + let input_bytes: Vec = to_u8_vec(dfg, input); + + let field = acvm::blackbox_solver::hash_to_field_128_security(&input_bytes) + .expect("Rust solvable black box function should not fail"); + + let field_constant = dfg.make_constant(field, Type::field()); + SimplifyResult::SimplifiedTo(field_constant) + } + _ => SimplifyResult::None, + }, + + BlackBoxFunc::EcdsaSecp256k1 => { + simplify_signature(dfg, arguments, acvm::blackbox_solver::ecdsa_secp256k1_verify) + } + BlackBoxFunc::EcdsaSecp256r1 => { + simplify_signature(dfg, arguments, acvm::blackbox_solver::ecdsa_secp256r1_verify) + } + + BlackBoxFunc::FixedBaseScalarMul | BlackBoxFunc::SchnorrVerify | BlackBoxFunc::Pedersen => { + // Currently unsolvable here as we rely on an implementation in the backend. + SimplifyResult::None + } + + BlackBoxFunc::RecursiveAggregation => SimplifyResult::None, + + BlackBoxFunc::AND => { + unreachable!("ICE: `BlackBoxFunc::AND` calls should be transformed into a `BinaryOp`") + } + BlackBoxFunc::XOR => { + unreachable!("ICE: `BlackBoxFunc::XOR` calls should be transformed into a `BinaryOp`") + } + BlackBoxFunc::RANGE => { + unreachable!( + "ICE: `BlackBoxFunc::RANGE` calls should be transformed into a `Instruction::Cast`" + ) + } + } +} + +fn make_constant_array(dfg: &mut DataFlowGraph, results: Vec, typ: Type) -> ValueId { + let result_constants = vecmap(results, |element| dfg.make_constant(element, typ.clone())); + + let typ = Type::Array(Rc::new(vec![typ]), result_constants.len()); + dfg.make_array(result_constants.into(), typ) +} + +/// Returns a Value::Array of constants corresponding to the limbs of the radix decomposition. +fn constant_to_radix( + endian: Endian, + field: FieldElement, + radix: u32, + limb_count: u32, + dfg: &mut DataFlowGraph, +) -> ValueId { + let bit_size = u32::BITS - (radix - 1).leading_zeros(); + let radix_big = BigUint::from(radix); + assert_eq!(BigUint::from(2u128).pow(bit_size), radix_big, "ICE: Radix must be a power of 2"); + let big_integer = BigUint::from_bytes_be(&field.to_be_bytes()); + + // Decompose the integer into its radix digits in little endian form. + let decomposed_integer = big_integer.to_radix_le(radix); + let mut limbs = vecmap(0..limb_count, |i| match decomposed_integer.get(i as usize) { + Some(digit) => FieldElement::from_be_bytes_reduce(&[*digit]), + None => FieldElement::zero(), + }); + if endian == Endian::Big { + limbs.reverse(); + } + + // For legacy reasons (see #617) the to_radix interface supports 256 bits even though + // FieldElement::max_num_bits() is only 254 bits. Any limbs beyond the specified count + // become zero padding. + let max_decomposable_bits: u32 = 256; + let limb_count_with_padding = max_decomposable_bits / bit_size; + while limbs.len() < limb_count_with_padding as usize { + limbs.push(FieldElement::zero()); + } + + make_constant_array(dfg, limbs, Type::unsigned(bit_size)) +} + +fn to_u8_vec(dfg: &DataFlowGraph, values: im::Vector>) -> Vec { + values + .iter() + .map(|id| { + let field = dfg + .get_numeric_constant(*id) + .expect("value id from array should point at constant"); + *field.to_be_bytes().last().unwrap() + }) + .collect() +} + +fn array_is_constant(dfg: &DataFlowGraph, values: &im::Vector>) -> bool { + values.iter().all(|value| dfg.get_numeric_constant(*value).is_some()) +} + +fn simplify_hash( + dfg: &mut DataFlowGraph, + arguments: &[ValueId], + hash_function: fn(&[u8]) -> Result<[u8; 32], BlackBoxResolutionError>, +) -> SimplifyResult { + match dfg.get_array_constant(arguments[0]) { + Some((input, _)) if array_is_constant(dfg, &input) => { + let input_bytes: Vec = to_u8_vec(dfg, input); + + let hash = hash_function(&input_bytes) + .expect("Rust solvable black box function should not fail"); + + let hash_values = vecmap(hash, |byte| FieldElement::from_be_bytes_reduce(&[byte])); + + let result_array = make_constant_array(dfg, hash_values, Type::unsigned(8)); + SimplifyResult::SimplifiedTo(result_array) + } + _ => SimplifyResult::None, + } +} + +type ECDSASignatureVerifier = fn( + hashed_msg: &[u8], + public_key_x: &[u8; 32], + public_key_y: &[u8; 32], + signature: &[u8; 64], +) -> Result; +fn simplify_signature( + dfg: &mut DataFlowGraph, + arguments: &[ValueId], + signature_verifier: ECDSASignatureVerifier, +) -> SimplifyResult { + match ( + dfg.get_array_constant(arguments[0]), + dfg.get_array_constant(arguments[1]), + dfg.get_array_constant(arguments[2]), + dfg.get_array_constant(arguments[3]), + ) { + ( + Some((public_key_x, _)), + Some((public_key_y, _)), + Some((signature, _)), + Some((hashed_message, _)), + ) if array_is_constant(dfg, &public_key_x) + && array_is_constant(dfg, &public_key_y) + && array_is_constant(dfg, &signature) + && array_is_constant(dfg, &hashed_message) => + { + let public_key_x: [u8; 32] = to_u8_vec(dfg, public_key_x) + .try_into() + .expect("ECDSA public key fields are 32 bytes"); + let public_key_y: [u8; 32] = to_u8_vec(dfg, public_key_y) + .try_into() + .expect("ECDSA public key fields are 32 bytes"); + let signature: [u8; 64] = + to_u8_vec(dfg, signature).try_into().expect("ECDSA signatures are 64 bytes"); + let hashed_message: Vec = to_u8_vec(dfg, hashed_message); + + let valid_signature = + signature_verifier(&hashed_message, &public_key_x, &public_key_y, &signature) + .expect("Rust solvable black box function should not fail"); + + let valid_signature = dfg.make_constant(valid_signature.into(), Type::bool()); + SimplifyResult::SimplifiedTo(valid_signature) + } + _ => SimplifyResult::None, + } +} From 1c21d0caf1e3b3a92266b4b8238f3e6e6c394d05 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Wed, 2 Aug 2023 17:21:35 +0100 Subject: [PATCH 30/50] fix(globals): Accurately filter literals for resolving globals (#2126) accurately filter literals for resolving globals --- .../tests/test_data/global_consts/src/main.nr | 7 +++++++ .../tests/test_data/strings/src/main.nr | 6 +++++- .../src/hir/def_collector/dc_crate.rs | 20 ++++++++++--------- 3 files changed, 23 insertions(+), 10 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/global_consts/src/main.nr b/crates/nargo_cli/tests/test_data/global_consts/src/main.nr index 9bcca2b8071..2ed6e4593dd 100644 --- a/crates/nargo_cli/tests/test_data/global_consts/src/main.nr +++ b/crates/nargo_cli/tests/test_data/global_consts/src/main.nr @@ -12,12 +12,19 @@ struct Dummy { y: [Field; foo::MAGIC_NUMBER] } +struct Test { + v: Field, +} +global VALS: [Test; 1] = [Test { v: 100 }]; +global NESTED = [VALS, VALS]; + fn main(a: [Field; M + N - N], b: [Field; 30 + N / 2], c : pub [Field; foo::MAGIC_NUMBER], d: [Field; foo::bar::N]) { let test_struct = Dummy { x: d, y: c }; for i in 0..foo::MAGIC_NUMBER { assert(c[i] == foo::MAGIC_NUMBER); assert(test_struct.y[i] == foo::MAGIC_NUMBER); + assert(test_struct.y[i] != NESTED[1][0].v); } assert(N != M); diff --git a/crates/nargo_cli/tests/test_data/strings/src/main.nr b/crates/nargo_cli/tests/test_data/strings/src/main.nr index bee2370201c..edf5fff55b4 100644 --- a/crates/nargo_cli/tests/test_data/strings/src/main.nr +++ b/crates/nargo_cli/tests/test_data/strings/src/main.nr @@ -1,10 +1,13 @@ use dep::std; +// Test global string literals +global HELLO_WORLD = "hello world"; + fn main(message : pub str<11>, y : Field, hex_as_string : str<4>, hex_as_field : Field) { let mut bad_message = "hello world"; assert(message == "hello world"); - bad_message = "helld world"; + assert(message == HELLO_WORLD); let x = 10; let z = x * 5; std::println(10); @@ -16,6 +19,7 @@ fn main(message : pub str<11>, y : Field, hex_as_string : str<4>, hex_as_field : assert(y == 5); // Change to y != 5 to see how the later print statements are not called std::println(array); + bad_message = "helld world"; std::println(bad_message); assert(message != bad_message); diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs index e974961a405..76fbea289be 100644 --- a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs +++ b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs @@ -13,7 +13,7 @@ use crate::hir::Context; use crate::node_interner::{FuncId, NodeInterner, StmtId, StructId, TypeAliasId}; use crate::{ ExpressionKind, Generics, Ident, LetStatement, NoirFunction, NoirStruct, NoirTypeAlias, - ParsedModule, Shared, Type, TypeBinding, UnresolvedGenerics, UnresolvedType, + ParsedModule, Shared, Type, TypeBinding, UnresolvedGenerics, UnresolvedType, Literal, }; use fm::FileId; use iter_extended::vecmap; @@ -161,10 +161,10 @@ impl DefCollector { // // Additionally, we must resolve integer globals before structs since structs may refer to // the values of integer globals as numeric generics. - let (integer_globals, other_globals) = - filter_integer_globals(def_collector.collected_globals); + let (literal_globals, other_globals) = + filter_literal_globals(def_collector.collected_globals); - let mut file_global_ids = resolve_globals(context, integer_globals, crate_id, errors); + let mut file_global_ids = resolve_globals(context, literal_globals, crate_id, errors); resolve_type_aliases(context, def_collector.collected_type_aliases, crate_id, errors); @@ -274,13 +274,15 @@ where } /// Separate the globals Vec into two. The first element in the tuple will be the -/// integer literal globals, and the second will be all other globals. -fn filter_integer_globals( +/// literal globals, except for arrays, and the second will be all other globals. +/// We exclude array literals as they can contain complex types +fn filter_literal_globals( globals: Vec, ) -> (Vec, Vec) { - globals - .into_iter() - .partition(|global| matches!(&global.stmt_def.expression.kind, ExpressionKind::Literal(_))) + globals.into_iter().partition(|global| match &global.stmt_def.expression.kind { + ExpressionKind::Literal(literal) => !matches!(literal, Literal::Array(_)), + _ => false, + }) } fn resolve_globals( From 27ab78f3e298e94202b8dcc9ea44075a185a78e7 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Wed, 2 Aug 2023 19:15:45 +0100 Subject: [PATCH 31/50] chore: Use `--show-output` flag on execution rather than compilation (#2116) * move show-output to occur on execute rather than compilation * remove assert(false) from test * fix compile err * report compile errors in tests * aupdate failing constraint test * change comment and link issue --- crates/nargo/src/ops/execute.rs | 3 +- crates/nargo/src/ops/foreign_calls.rs | 5 ++- crates/nargo_cli/src/cli/execute_cmd.rs | 2 +- crates/nargo_cli/src/cli/test_cmd.rs | 9 +++-- .../tests/test_data/strings/src/main.nr | 20 ++++++++-- crates/noirc_driver/src/lib.rs | 8 ++-- crates/noirc_evaluator/src/ssa_refactor.rs | 6 +-- .../acir_gen/acir_ir/acir_variable.rs | 13 ------- .../src/ssa_refactor/acir_gen/mod.rs | 37 +++++-------------- crates/wasm/src/compile.rs | 4 +- 10 files changed, 46 insertions(+), 61 deletions(-) diff --git a/crates/nargo/src/ops/execute.rs b/crates/nargo/src/ops/execute.rs index 13ea64ed261..2a126443468 100644 --- a/crates/nargo/src/ops/execute.rs +++ b/crates/nargo/src/ops/execute.rs @@ -10,6 +10,7 @@ pub fn execute_circuit( _backend: &B, circuit: Circuit, initial_witness: WitnessMap, + show_output: bool, ) -> Result { let mut acvm = ACVM::new(B::default(), circuit.opcodes, initial_witness); @@ -23,7 +24,7 @@ pub fn execute_circuit( } ACVMStatus::Failure(error) => return Err(error.into()), ACVMStatus::RequiresForeignCall(foreign_call) => { - let foreign_call_result = ForeignCall::execute(&foreign_call)?; + let foreign_call_result = ForeignCall::execute(&foreign_call, show_output)?; acvm.resolve_pending_foreign_call(foreign_call_result); } } diff --git a/crates/nargo/src/ops/foreign_calls.rs b/crates/nargo/src/ops/foreign_calls.rs index 2abc62b1032..4d2f5988e38 100644 --- a/crates/nargo/src/ops/foreign_calls.rs +++ b/crates/nargo/src/ops/foreign_calls.rs @@ -42,11 +42,14 @@ impl ForeignCall { pub(crate) fn execute( foreign_call: &ForeignCallWaitInfo, + show_output: bool, ) -> Result { let foreign_call_name = foreign_call.function.as_str(); match Self::lookup(foreign_call_name) { Some(ForeignCall::Println) => { - Self::execute_println(&foreign_call.inputs)?; + if show_output { + Self::execute_println(&foreign_call.inputs)?; + } Ok(ForeignCallResult { values: vec![] }) } Some(ForeignCall::Sequence) => { diff --git a/crates/nargo_cli/src/cli/execute_cmd.rs b/crates/nargo_cli/src/cli/execute_cmd.rs index ca5c18585ab..a2700caee0f 100644 --- a/crates/nargo_cli/src/cli/execute_cmd.rs +++ b/crates/nargo_cli/src/cli/execute_cmd.rs @@ -132,7 +132,7 @@ pub(crate) fn execute_program( debug_data: Option<(DebugInfo, Context)>, ) -> Result> { let initial_witness = abi.encode(inputs_map, None)?; - let solved_witness_err = nargo::ops::execute_circuit(backend, circuit, initial_witness); + let solved_witness_err = nargo::ops::execute_circuit(backend, circuit, initial_witness, true); match solved_witness_err { Ok(solved_witness) => Ok(solved_witness), Err(err) => { diff --git a/crates/nargo_cli/src/cli/test_cmd.rs b/crates/nargo_cli/src/cli/test_cmd.rs index 7eb1c9bff74..e52e3e5aa8d 100644 --- a/crates/nargo_cli/src/cli/test_cmd.rs +++ b/crates/nargo_cli/src/cli/test_cmd.rs @@ -106,14 +106,17 @@ fn run_test( show_output: bool, config: &CompileOptions, ) -> Result<(), CliError> { - let mut program = compile_no_check(context, show_output, config, main) - .map_err(|_| CliError::Generic(format!("Test '{test_name}' failed to compile")))?; + let mut program = compile_no_check(context, config, main).map_err(|err| { + noirc_errors::reporter::report_all(&context.file_manager, &[err], config.deny_warnings); + CliError::Generic(format!("Test '{test_name}' failed to compile")) + })?; + // Note: We could perform this test using the unoptimized ACIR as generated by `compile_no_check`. program.circuit = optimize_circuit(backend, program.circuit).unwrap().0; // Run the backend to ensure the PWG evaluates functions like std::hash::pedersen, // otherwise constraints involving these expressions will not error. - match execute_circuit(backend, program.circuit, WitnessMap::new()) { + match execute_circuit(backend, program.circuit, WitnessMap::new(), show_output) { Ok(_) => Ok(()), Err(error) => { let writer = StandardStream::stderr(ColorChoice::Always); diff --git a/crates/nargo_cli/tests/test_data/strings/src/main.nr b/crates/nargo_cli/tests/test_data/strings/src/main.nr index edf5fff55b4..9f122c3a137 100644 --- a/crates/nargo_cli/tests/test_data/strings/src/main.nr +++ b/crates/nargo_cli/tests/test_data/strings/src/main.nr @@ -43,9 +43,8 @@ fn test_prints_strings() { fn test_prints_array() { let array = [1, 2, 3, 5, 8]; - // TODO: Printing structs currently not supported - // let s = Test { a: 1, b: 2, c: [3, 4] }; - // std::println(s); + let s = Test { a: 1, b: 2, c: [3, 4] }; + std::println(s); std::println(array); @@ -53,6 +52,21 @@ fn test_prints_array() { std::println(hash); } +fn failed_constraint(hex_as_field: Field) { + // TODO(#2116): Note that `println` will not work if a failed constraint can be + // evaluated at compile time. + // When this method is called from a test method or with constant values + // a `Failed constraint` compile error will be caught before this `println` + // is executed as the input will be a constant. + std::println(hex_as_field); + assert(hex_as_field != 0x41); +} + +#[test] +fn test_failed_constraint() { + failed_constraint(0x41); +} + struct Test { a: Field, b: Field, diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs index 4d1b7fe2675..27109af6a2f 100644 --- a/crates/noirc_driver/src/lib.rs +++ b/crates/noirc_driver/src/lib.rs @@ -163,7 +163,7 @@ pub fn compile_main( } }; - let compiled_program = compile_no_check(context, true, options, main)?; + let compiled_program = compile_no_check(context, options, main)?; if options.print_acir { println!("Compiled ACIR for main (unoptimized):"); @@ -230,7 +230,7 @@ fn compile_contract( let mut errs = Vec::new(); for function_id in &contract.functions { let name = context.function_name(function_id).to_owned(); - let function = match compile_no_check(context, true, options, *function_id) { + let function = match compile_no_check(context, options, *function_id) { Ok(function) => function, Err(err) => { errs.push(err); @@ -267,14 +267,12 @@ fn compile_contract( #[allow(deprecated)] pub fn compile_no_check( context: &Context, - show_output: bool, options: &CompileOptions, main_function: FuncId, ) -> Result { let program = monomorphize(main_function, &context.def_interner); - let (circuit, debug, abi) = - create_circuit(program, options.show_ssa, options.show_brillig, show_output)?; + let (circuit, debug, abi) = create_circuit(program, options.show_ssa, options.show_brillig)?; Ok(CompiledProgram { circuit, debug, abi }) } diff --git a/crates/noirc_evaluator/src/ssa_refactor.rs b/crates/noirc_evaluator/src/ssa_refactor.rs index 6326b45554d..c57bb330b09 100644 --- a/crates/noirc_evaluator/src/ssa_refactor.rs +++ b/crates/noirc_evaluator/src/ssa_refactor.rs @@ -35,7 +35,6 @@ pub mod ssa_gen; /// convert the final SSA into ACIR and return it. pub(crate) fn optimize_into_acir( program: Program, - allow_log_ops: bool, print_ssa_passes: bool, print_brillig_trace: bool, ) -> Result { @@ -63,7 +62,7 @@ pub(crate) fn optimize_into_acir( .dead_instruction_elimination() .print(print_ssa_passes, "After Dead Instruction Elimination:"); } - ssa.into_acir(brillig, abi_distinctness, allow_log_ops) + ssa.into_acir(brillig, abi_distinctness) } /// Compiles the Program into ACIR and applies optimizations to the arithmetic gates @@ -74,7 +73,6 @@ pub fn create_circuit( program: Program, enable_ssa_logging: bool, enable_brillig_logging: bool, - show_output: bool, ) -> Result<(Circuit, DebugInfo, Abi), RuntimeError> { let func_sig = program.main_function_signature.clone(); let GeneratedAcir { @@ -84,7 +82,7 @@ pub fn create_circuit( locations, input_witnesses, .. - } = optimize_into_acir(program, show_output, enable_ssa_logging, enable_brillig_logging)?; + } = optimize_into_acir(program, enable_ssa_logging, enable_brillig_logging)?; let abi = gen_abi(func_sig, &input_witnesses, return_witnesses.clone()); let public_abi = abi.clone().public_abi(); diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs index 9177dc9ae6c..d1479ef1f1b 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs @@ -827,19 +827,6 @@ impl AcirContext { self.radix_decompose(endian, input_var, two_var, limb_count_var, result_element_type) } - /// Prints the given `AcirVar`s as witnesses. - pub(crate) fn print(&mut self, input: Vec) -> Result<(), RuntimeError> { - let input = Self::flatten_values(input); - - let witnesses = vecmap(input, |acir_var| { - let var_data = &self.vars[&acir_var]; - let expr = var_data.to_expression(); - self.acir_ir.get_or_create_witness(&expr) - }); - self.acir_ir.call_print(witnesses); - Ok(()) - } - /// Flatten the given Vector of AcirValues into a single vector of only variables. /// Each AcirValue::Array in the vector is recursively flattened, so each element /// will flattened into the resulting Vec. E.g. flatten_values([1, [2, 3]) == [1, 2, 3]. diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs index f00f15d8f05..62a9dd5969d 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs @@ -103,10 +103,9 @@ impl Ssa { self, brillig: Brillig, abi_distinctness: AbiDistinctness, - allow_log_ops: bool, ) -> Result { let context = Context::new(); - let mut generated_acir = context.convert_ssa(self, brillig, allow_log_ops)?; + let mut generated_acir = context.convert_ssa(self, brillig)?; match abi_distinctness { AbiDistinctness::Distinct => { @@ -144,15 +143,10 @@ impl Context { } /// Converts SSA into ACIR - fn convert_ssa( - self, - ssa: Ssa, - brillig: Brillig, - allow_log_ops: bool, - ) -> Result { + fn convert_ssa(self, ssa: Ssa, brillig: Brillig) -> Result { let main_func = ssa.main(); match main_func.runtime() { - RuntimeType::Acir => self.convert_acir_main(main_func, &ssa, brillig, allow_log_ops), + RuntimeType::Acir => self.convert_acir_main(main_func, &ssa, brillig), RuntimeType::Brillig => self.convert_brillig_main(main_func, brillig), } } @@ -162,14 +156,13 @@ impl Context { main_func: &Function, ssa: &Ssa, brillig: Brillig, - allow_log_ops: bool, ) -> Result { let dfg = &main_func.dfg; let entry_block = &dfg[main_func.entry_block()]; let input_witness = self.convert_ssa_block_params(entry_block.parameters(), dfg)?; for instruction_id in entry_block.instructions() { - self.convert_ssa_instruction(*instruction_id, dfg, ssa, &brillig, allow_log_ops)?; + self.convert_ssa_instruction(*instruction_id, dfg, ssa, &brillig)?; } self.convert_ssa_return(entry_block.unwrap_terminator(), dfg)?; @@ -294,7 +287,6 @@ impl Context { dfg: &DataFlowGraph, ssa: &Ssa, brillig: &Brillig, - allow_log_ops: bool, ) -> Result<(), RuntimeError> { let instruction = &dfg[instruction_id]; self.acir_context.set_location(dfg.get_location(&instruction_id)); @@ -339,13 +331,8 @@ impl Context { } } Value::Intrinsic(intrinsic) => { - let outputs = self.convert_ssa_intrinsic_call( - *intrinsic, - arguments, - dfg, - allow_log_ops, - result_ids, - )?; + let outputs = self + .convert_ssa_intrinsic_call(*intrinsic, arguments, dfg, result_ids)?; // Issue #1438 causes this check to fail with intrinsics that return 0 // results but the ssa form instead creates 1 unit result value. @@ -929,7 +916,6 @@ impl Context { intrinsic: Intrinsic, arguments: &[ValueId], dfg: &DataFlowGraph, - allow_log_ops: bool, result_ids: &[ValueId], ) -> Result, RuntimeError> { match intrinsic { @@ -959,13 +945,8 @@ impl Context { self.acir_context.bit_decompose(endian, field, bit_size, result_type) } - Intrinsic::Println => { - let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg)); - if allow_log_ops { - self.acir_context.print(inputs)?; - } - Ok(Vec::new()) - } + // TODO(#2115): Remove the println intrinsic as the oracle println is now used instead + Intrinsic::Println => Ok(Vec::new()), Intrinsic::Sort => { let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg)); // We flatten the inputs and retrieve the bit_size of the elements @@ -1133,7 +1114,7 @@ mod tests { let ssa = builder.finish(); let context = Context::new(); - let acir = context.convert_ssa(ssa, Brillig::default(), false).unwrap(); + let acir = context.convert_ssa(ssa, Brillig::default()).unwrap(); let expected_opcodes = vec![Opcode::Arithmetic(&Expression::one() - &Expression::from(Witness(1)))]; diff --git a/crates/wasm/src/compile.rs b/crates/wasm/src/compile.rs index 15d8d5107ea..4254110b849 100644 --- a/crates/wasm/src/compile.rs +++ b/crates/wasm/src/compile.rs @@ -107,8 +107,8 @@ pub fn compile(args: JsValue) -> JsValue { ::from_serde(&optimized_contracts).unwrap() } else { let main = context.get_main_function(&crate_id).expect("Could not find main function!"); - let mut compiled_program = compile_no_check(&context, true, &options.compile_options, main) - .expect("Compilation failed"); + let mut compiled_program = + compile_no_check(&context, &options.compile_options, main).expect("Compilation failed"); compiled_program.circuit = optimize_circuit(compiled_program.circuit); From a07b8a48924865d8425d35e40c75f48a13a81935 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Wed, 2 Aug 2023 20:00:23 +0100 Subject: [PATCH 32/50] chore: rename `ssa_refactor` module to `ssa` (#2129) --- .gitignore | 2 -- .../noirc_evaluator/src/brillig/brillig_gen.rs | 2 +- .../src/brillig/brillig_gen/brillig_block.rs | 9 +++++---- .../src/brillig/brillig_gen/brillig_fn.rs | 2 +- crates/noirc_evaluator/src/brillig/mod.rs | 2 +- crates/noirc_evaluator/src/lib.rs | 4 ++-- .../src/{ssa_refactor.rs => ssa.rs} | 0 .../src/{ssa_refactor => ssa}/abi_gen/mod.rs | 0 .../{ssa_refactor => ssa}/acir_gen/acir_ir.rs | 0 .../acir_gen/acir_ir/acir_variable.rs | 6 +++--- .../acir_gen/acir_ir/generated_acir.rs | 0 .../acir_gen/acir_ir/sort.rs | 0 .../src/{ssa_refactor => ssa}/acir_gen/mod.rs | 2 +- .../src/{ssa_refactor => ssa}/ir.rs | 0 .../src/{ssa_refactor => ssa}/ir/basic_block.rs | 0 .../src/{ssa_refactor => ssa}/ir/cfg.rs | 2 +- .../src/{ssa_refactor => ssa}/ir/dfg.rs | 4 ++-- .../src/{ssa_refactor => ssa}/ir/dom.rs | 2 +- .../src/{ssa_refactor => ssa}/ir/function.rs | 0 .../ir/function_inserter.rs | 0 .../src/{ssa_refactor => ssa}/ir/instruction.rs | 4 +--- .../{ssa_refactor => ssa}/ir/instruction/call.rs | 2 +- .../src/{ssa_refactor => ssa}/ir/map.rs | 0 .../src/{ssa_refactor => ssa}/ir/post_order.rs | 4 ++-- .../src/{ssa_refactor => ssa}/ir/printer.rs | 0 .../src/{ssa_refactor => ssa}/ir/types.rs | 0 .../src/{ssa_refactor => ssa}/ir/value.rs | 2 +- .../opt/constant_folding.rs | 4 ++-- .../{ssa_refactor => ssa}/opt/defunctionalize.rs | 2 +- .../src/{ssa_refactor => ssa}/opt/die.rs | 4 ++-- .../src/{ssa_refactor => ssa}/opt/flatten_cfg.rs | 6 +++--- .../opt/flatten_cfg/branch_analysis.rs | 6 ++---- .../src/{ssa_refactor => ssa}/opt/inlining.rs | 4 ++-- .../src/{ssa_refactor => ssa}/opt/mem2reg.rs | 4 ++-- .../src/{ssa_refactor => ssa}/opt/mod.rs | 0 .../{ssa_refactor => ssa}/opt/simplify_cfg.rs | 4 ++-- .../src/{ssa_refactor => ssa}/opt/unrolling.rs | 4 ++-- .../src/{ssa_refactor => ssa}/ssa_builder/mod.rs | 4 ++-- .../src/{ssa_refactor => ssa}/ssa_gen/context.rs | 16 ++++++++-------- .../src/{ssa_refactor => ssa}/ssa_gen/mod.rs | 0 .../src/{ssa_refactor => ssa}/ssa_gen/program.rs | 2 +- .../src/{ssa_refactor => ssa}/ssa_gen/value.rs | 4 ++-- 42 files changed, 54 insertions(+), 59 deletions(-) rename crates/noirc_evaluator/src/{ssa_refactor.rs => ssa.rs} (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/abi_gen/mod.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/acir_gen/acir_ir.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/acir_gen/acir_ir/acir_variable.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/acir_gen/acir_ir/generated_acir.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/acir_gen/acir_ir/sort.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/acir_gen/mod.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/basic_block.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/cfg.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/dfg.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/dom.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/function.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/function_inserter.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/instruction.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/instruction/call.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/map.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/post_order.rs (97%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/printer.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/types.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ir/value.rs (98%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/constant_folding.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/defunctionalize.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/die.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/flatten_cfg.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/flatten_cfg/branch_analysis.rs (98%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/inlining.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/mem2reg.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/mod.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/simplify_cfg.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/opt/unrolling.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ssa_builder/mod.rs (99%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ssa_gen/context.rs (98%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ssa_gen/mod.rs (100%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ssa_gen/program.rs (98%) rename crates/noirc_evaluator/src/{ssa_refactor => ssa}/ssa_gen/value.rs (98%) diff --git a/.gitignore b/.gitignore index af3a8e8beb2..8aec0edeadc 100644 --- a/.gitignore +++ b/.gitignore @@ -22,5 +22,3 @@ result **/target !crates/nargo_cli/tests/test_data/*/target !crates/nargo_cli/tests/test_data/*/target/witness.tr -!crates/nargo_cli/tests/test_data_ssa_refactor/*/target -!crates/nargo_cli/tests/test_data_ssa_refactor/*/target/witness.tr \ No newline at end of file diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen.rs b/crates/noirc_evaluator/src/brillig/brillig_gen.rs index 3ba04ed1afb..a1e82bbf443 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen.rs @@ -4,7 +4,7 @@ pub(crate) mod brillig_directive; pub(crate) mod brillig_fn; pub(crate) mod brillig_slice_ops; -use crate::ssa_refactor::ir::{function::Function, post_order::PostOrder}; +use crate::ssa::ir::{function::Function, post_order::PostOrder}; use std::collections::HashMap; diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs index a9bbe189e57..ded6be71bd5 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs @@ -4,12 +4,13 @@ use crate::brillig::brillig_gen::brillig_slice_ops::{ use crate::brillig::brillig_ir::{ BrilligBinaryOp, BrilligContext, BRILLIG_INTEGER_ARITHMETIC_BIT_SIZE, }; -use crate::ssa_refactor::ir::function::FunctionId; -use crate::ssa_refactor::ir::instruction::{Endian, Intrinsic}; -use crate::ssa_refactor::ir::{ +use crate::ssa::ir::{ basic_block::{BasicBlock, BasicBlockId}, dfg::DataFlowGraph, - instruction::{Binary, BinaryOp, Instruction, InstructionId, TerminatorInstruction}, + function::FunctionId, + instruction::{ + Binary, BinaryOp, Endian, Instruction, InstructionId, Intrinsic, TerminatorInstruction, + }, types::{NumericType, Type}, value::{Value, ValueId}, }; diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs index 210d6da7be6..7c4cb5e2ced 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs @@ -8,7 +8,7 @@ use crate::{ artifact::{BrilligParameter, Label}, BrilligContext, }, - ssa_refactor::ir::{ + ssa::ir::{ dfg::DataFlowGraph, function::{Function, FunctionId}, types::{CompositeType, Type}, diff --git a/crates/noirc_evaluator/src/brillig/mod.rs b/crates/noirc_evaluator/src/brillig/mod.rs index 105475323a7..0c6ddd53a4e 100644 --- a/crates/noirc_evaluator/src/brillig/mod.rs +++ b/crates/noirc_evaluator/src/brillig/mod.rs @@ -5,7 +5,7 @@ use self::{ brillig_gen::{brillig_fn::FunctionContext, convert_ssa_function}, brillig_ir::artifact::{BrilligArtifact, Label}, }; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ function::{Function, FunctionId, RuntimeType}, value::Value, diff --git a/crates/noirc_evaluator/src/lib.rs b/crates/noirc_evaluator/src/lib.rs index c7d4f5baed6..f5403e1cf49 100644 --- a/crates/noirc_evaluator/src/lib.rs +++ b/crates/noirc_evaluator/src/lib.rs @@ -7,8 +7,8 @@ mod errors; // SSA code to create the SSA based IR // for functions and execute different optimizations. -pub mod ssa_refactor; +pub mod ssa; pub mod brillig; -pub use ssa_refactor::create_circuit; +pub use ssa::create_circuit; diff --git a/crates/noirc_evaluator/src/ssa_refactor.rs b/crates/noirc_evaluator/src/ssa.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor.rs rename to crates/noirc_evaluator/src/ssa.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs b/crates/noirc_evaluator/src/ssa/abi_gen/mod.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs rename to crates/noirc_evaluator/src/ssa/abi_gen/mod.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs rename to crates/noirc_evaluator/src/ssa/acir_gen/acir_ir.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/acir_variable.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs rename to crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/acir_variable.rs index d1479ef1f1b..779aaa559ed 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/acir_variable.rs @@ -1,9 +1,9 @@ use super::generated_acir::GeneratedAcir; use crate::brillig::brillig_gen::brillig_directive; use crate::errors::{InternalError, RuntimeError}; -use crate::ssa_refactor::acir_gen::{AcirDynamicArray, AcirValue}; -use crate::ssa_refactor::ir::types::Type as SsaType; -use crate::ssa_refactor::ir::{instruction::Endian, types::NumericType}; +use crate::ssa::acir_gen::{AcirDynamicArray, AcirValue}; +use crate::ssa::ir::types::Type as SsaType; +use crate::ssa::ir::{instruction::Endian, types::NumericType}; use acvm::acir::circuit::opcodes::{BlockId, MemOp}; use acvm::acir::circuit::Opcode; use acvm::acir::{ diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs rename to crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/sort.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs rename to crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/sort.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs rename to crates/noirc_evaluator/src/ssa/acir_gen/mod.rs index 62a9dd5969d..331c56f59d7 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs @@ -1086,7 +1086,7 @@ mod tests { use crate::{ brillig::Brillig, - ssa_refactor::{ + ssa::{ ir::{function::RuntimeType, map::Id, types::Type}, ssa_builder::FunctionBuilder, }, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir.rs b/crates/noirc_evaluator/src/ssa/ir.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir.rs rename to crates/noirc_evaluator/src/ssa/ir.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/basic_block.rs b/crates/noirc_evaluator/src/ssa/ir/basic_block.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/basic_block.rs rename to crates/noirc_evaluator/src/ssa/ir/basic_block.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/cfg.rs b/crates/noirc_evaluator/src/ssa/ir/cfg.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ir/cfg.rs rename to crates/noirc_evaluator/src/ssa/ir/cfg.rs index f08b477696a..a91123438fa 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/cfg.rs +++ b/crates/noirc_evaluator/src/ssa/ir/cfg.rs @@ -128,7 +128,7 @@ impl ControlFlowGraph { #[cfg(test)] mod tests { - use crate::ssa_refactor::ir::{instruction::TerminatorInstruction, map::Id, types::Type}; + use crate::ssa::ir::{instruction::TerminatorInstruction, map::Id, types::Type}; use super::{super::function::Function, ControlFlowGraph}; diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs b/crates/noirc_evaluator/src/ssa/ir/dfg.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs rename to crates/noirc_evaluator/src/ssa/ir/dfg.rs index 6d74e49b03b..29f5156a88c 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs +++ b/crates/noirc_evaluator/src/ssa/ir/dfg.rs @@ -1,6 +1,6 @@ use std::{borrow::Cow, collections::HashMap}; -use crate::ssa_refactor::ir::instruction::SimplifyResult; +use crate::ssa::ir::instruction::SimplifyResult; use super::{ basic_block::{BasicBlock, BasicBlockId}, @@ -503,7 +503,7 @@ impl<'dfg> InsertInstructionResult<'dfg> { #[cfg(test)] mod tests { use super::DataFlowGraph; - use crate::ssa_refactor::ir::instruction::Instruction; + use crate::ssa::ir::instruction::Instruction; #[test] fn make_instruction() { diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/dom.rs b/crates/noirc_evaluator/src/ssa/ir/dom.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ir/dom.rs rename to crates/noirc_evaluator/src/ssa/ir/dom.rs index 4763ffffbd1..b7b1728d035 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/dom.rs +++ b/crates/noirc_evaluator/src/ssa/ir/dom.rs @@ -245,7 +245,7 @@ impl DominatorTree { mod tests { use std::cmp::Ordering; - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ basic_block::BasicBlockId, dom::DominatorTree, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function.rs b/crates/noirc_evaluator/src/ssa/ir/function.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/function.rs rename to crates/noirc_evaluator/src/ssa/ir/function.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs b/crates/noirc_evaluator/src/ssa/ir/function_inserter.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs rename to crates/noirc_evaluator/src/ssa/ir/function_inserter.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa/ir/instruction.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs rename to crates/noirc_evaluator/src/ssa/ir/instruction.rs index 7edb74f4206..680715fb0ec 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs +++ b/crates/noirc_evaluator/src/ssa/ir/instruction.rs @@ -2,13 +2,11 @@ use acvm::{acir::BlackBoxFunc, FieldElement}; use iter_extended::vecmap; use num_bigint::BigUint; -use crate::ssa_refactor::ir::types::NumericType; - use super::{ basic_block::BasicBlockId, dfg::DataFlowGraph, map::Id, - types::Type, + types::{NumericType, Type}, value::{Value, ValueId}, }; diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs b/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs rename to crates/noirc_evaluator/src/ssa/ir/instruction/call.rs index 96998d92fcf..2f0c077a1a7 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction/call.rs +++ b/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs @@ -4,7 +4,7 @@ use acvm::{acir::BlackBoxFunc, BlackBoxResolutionError, FieldElement}; use iter_extended::vecmap; use num_bigint::BigUint; -use crate::ssa_refactor::ir::{ +use crate::ssa::ir::{ dfg::DataFlowGraph, instruction::Intrinsic, map::Id, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/map.rs b/crates/noirc_evaluator/src/ssa/ir/map.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/map.rs rename to crates/noirc_evaluator/src/ssa/ir/map.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/post_order.rs b/crates/noirc_evaluator/src/ssa/ir/post_order.rs similarity index 97% rename from crates/noirc_evaluator/src/ssa_refactor/ir/post_order.rs rename to crates/noirc_evaluator/src/ssa/ir/post_order.rs index 2f7b5edebe6..202f5cff716 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/post_order.rs +++ b/crates/noirc_evaluator/src/ssa/ir/post_order.rs @@ -5,7 +5,7 @@ use std::collections::HashSet; -use crate::ssa_refactor::ir::{basic_block::BasicBlockId, function::Function}; +use crate::ssa::ir::{basic_block::BasicBlockId, function::Function}; /// Depth-first traversal stack state marker for computing the cfg post-order. enum Visit { @@ -67,7 +67,7 @@ impl PostOrder { #[cfg(test)] mod tests { - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ function::{Function, RuntimeType}, map::Id, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/printer.rs b/crates/noirc_evaluator/src/ssa/ir/printer.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/printer.rs rename to crates/noirc_evaluator/src/ssa/ir/printer.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/types.rs b/crates/noirc_evaluator/src/ssa/ir/types.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ir/types.rs rename to crates/noirc_evaluator/src/ssa/ir/types.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs b/crates/noirc_evaluator/src/ssa/ir/value.rs similarity index 98% rename from crates/noirc_evaluator/src/ssa_refactor/ir/value.rs rename to crates/noirc_evaluator/src/ssa/ir/value.rs index cea526058b4..54831eb4a07 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs +++ b/crates/noirc_evaluator/src/ssa/ir/value.rs @@ -1,6 +1,6 @@ use acvm::FieldElement; -use crate::ssa_refactor::ir::basic_block::BasicBlockId; +use crate::ssa::ir::basic_block::BasicBlockId; use super::{ function::FunctionId, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs b/crates/noirc_evaluator/src/ssa/opt/constant_folding.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs rename to crates/noirc_evaluator/src/ssa/opt/constant_folding.rs index acf048595d7..ea46ddf1d4f 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs +++ b/crates/noirc_evaluator/src/ssa/opt/constant_folding.rs @@ -2,7 +2,7 @@ use std::collections::HashSet; use iter_extended::vecmap; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, dfg::InsertInstructionResult, function::Function, instruction::InstructionId, @@ -94,7 +94,7 @@ impl Context { mod test { use std::rc::Rc; - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ function::RuntimeType, instruction::{BinaryOp, TerminatorInstruction}, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs b/crates/noirc_evaluator/src/ssa/opt/defunctionalize.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs rename to crates/noirc_evaluator/src/ssa/opt/defunctionalize.rs index fc3bc5d9aa6..10561bf731f 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs +++ b/crates/noirc_evaluator/src/ssa/opt/defunctionalize.rs @@ -9,7 +9,7 @@ use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet}; use acvm::FieldElement; use iter_extended::vecmap; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, function::{Function, FunctionId, RuntimeType, Signature}, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/die.rs b/crates/noirc_evaluator/src/ssa/opt/die.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/die.rs rename to crates/noirc_evaluator/src/ssa/opt/die.rs index ef73938cc37..935568af2db 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/die.rs +++ b/crates/noirc_evaluator/src/ssa/opt/die.rs @@ -2,7 +2,7 @@ //! which the results are unused. use std::collections::HashSet; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::{BasicBlock, BasicBlockId}, dfg::DataFlowGraph, @@ -133,7 +133,7 @@ impl Context { #[cfg(test)] mod test { - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{function::RuntimeType, instruction::BinaryOp, map::Id, types::Type}, ssa_builder::FunctionBuilder, }; diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs b/crates/noirc_evaluator/src/ssa/opt/flatten_cfg.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs rename to crates/noirc_evaluator/src/ssa/opt/flatten_cfg.rs index fdc4be085d7..1bcdf433d79 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs +++ b/crates/noirc_evaluator/src/ssa/opt/flatten_cfg.rs @@ -137,7 +137,7 @@ use acvm::FieldElement; use iter_extended::vecmap; use noirc_errors::Location; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, cfg::ControlFlowGraph, @@ -213,7 +213,7 @@ fn flatten_function_cfg(function: &mut Function) { // TODO This loops forever, if the predecessors are not then processed // TODO Because it will visit the same block again, pop it out of the queue // TODO then back into the queue again. - if let crate::ssa_refactor::ir::function::RuntimeType::Brillig = function.runtime() { + if let crate::ssa::ir::function::RuntimeType::Brillig = function.runtime() { return; } let cfg = ControlFlowGraph::with_function(function); @@ -739,7 +739,7 @@ impl<'f> Context<'f> { mod test { use std::rc::Rc; - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ dfg::DataFlowGraph, function::{Function, RuntimeType}, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg/branch_analysis.rs b/crates/noirc_evaluator/src/ssa/opt/flatten_cfg/branch_analysis.rs similarity index 98% rename from crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg/branch_analysis.rs rename to crates/noirc_evaluator/src/ssa/opt/flatten_cfg/branch_analysis.rs index bed0686e45b..1203d03f562 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg/branch_analysis.rs +++ b/crates/noirc_evaluator/src/ssa/opt/flatten_cfg/branch_analysis.rs @@ -21,9 +21,7 @@ //! the resulting map from each split block to each join block is returned. use std::collections::HashMap; -use crate::ssa_refactor::ir::{ - basic_block::BasicBlockId, cfg::ControlFlowGraph, function::Function, -}; +use crate::ssa::ir::{basic_block::BasicBlockId, cfg::ControlFlowGraph, function::Function}; /// Returns a `HashMap` mapping blocks that start a branch (i.e. blocks terminated with jmpif) to /// their corresponding blocks that end the branch. @@ -114,7 +112,7 @@ impl<'cfg> Context<'cfg> { #[cfg(test)] mod test { - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{cfg::ControlFlowGraph, function::RuntimeType, map::Id, types::Type}, opt::flatten_cfg::branch_analysis::find_branch_ends, ssa_builder::FunctionBuilder, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs b/crates/noirc_evaluator/src/ssa/opt/inlining.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs rename to crates/noirc_evaluator/src/ssa/opt/inlining.rs index 7aa2f9d176a..d4c118fd3f4 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs +++ b/crates/noirc_evaluator/src/ssa/opt/inlining.rs @@ -6,7 +6,7 @@ use std::collections::{HashMap, HashSet}; use iter_extended::vecmap; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, dfg::InsertInstructionResult, @@ -482,7 +482,7 @@ impl<'function> PerFunctionContext<'function> { mod test { use acvm::FieldElement; - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ basic_block::BasicBlockId, function::RuntimeType, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs b/crates/noirc_evaluator/src/ssa/opt/mem2reg.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs rename to crates/noirc_evaluator/src/ssa/opt/mem2reg.rs index 15108abc490..b9e849bb77c 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs +++ b/crates/noirc_evaluator/src/ssa/opt/mem2reg.rs @@ -5,7 +5,7 @@ use std::collections::{BTreeMap, HashMap, HashSet}; use iter_extended::vecmap; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, dfg::DataFlowGraph, @@ -182,7 +182,7 @@ mod tests { use acvm::FieldElement; use im::vector; - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ basic_block::BasicBlockId, dfg::DataFlowGraph, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/mod.rs b/crates/noirc_evaluator/src/ssa/opt/mod.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/opt/mod.rs rename to crates/noirc_evaluator/src/ssa/opt/mod.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/simplify_cfg.rs b/crates/noirc_evaluator/src/ssa/opt/simplify_cfg.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/simplify_cfg.rs rename to crates/noirc_evaluator/src/ssa/opt/simplify_cfg.rs index 22991e38b94..58259cec90c 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/simplify_cfg.rs +++ b/crates/noirc_evaluator/src/ssa/opt/simplify_cfg.rs @@ -11,7 +11,7 @@ //! Currently, 1 and 4 are unimplemented. use std::collections::HashSet; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, cfg::ControlFlowGraph, function::Function, instruction::TerminatorInstruction, @@ -148,7 +148,7 @@ fn try_inline_into_predecessor( #[cfg(test)] mod test { - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{ function::RuntimeType, instruction::{BinaryOp, TerminatorInstruction}, diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/unrolling.rs b/crates/noirc_evaluator/src/ssa/opt/unrolling.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/opt/unrolling.rs rename to crates/noirc_evaluator/src/ssa/opt/unrolling.rs index e5d7d6f0d5c..f6d7c952277 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/opt/unrolling.rs +++ b/crates/noirc_evaluator/src/ssa/opt/unrolling.rs @@ -14,7 +14,7 @@ //! program that will need to be removed by a later simplify cfg pass. use std::collections::{HashMap, HashSet}; -use crate::ssa_refactor::{ +use crate::ssa::{ ir::{ basic_block::BasicBlockId, cfg::ControlFlowGraph, dfg::DataFlowGraph, dom::DominatorTree, function::Function, function_inserter::FunctionInserter, @@ -424,7 +424,7 @@ impl<'f> LoopIteration<'f> { #[cfg(test)] mod tests { - use crate::ssa_refactor::{ + use crate::ssa::{ ir::{function::RuntimeType, instruction::BinaryOp, map::Id, types::Type}, ssa_builder::FunctionBuilder, }; diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs b/crates/noirc_evaluator/src/ssa/ssa_builder/mod.rs similarity index 99% rename from crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs rename to crates/noirc_evaluator/src/ssa/ssa_builder/mod.rs index 02350d9ed17..066b5b51199 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_builder/mod.rs @@ -3,7 +3,7 @@ use std::borrow::Cow; use acvm::FieldElement; use noirc_errors::Location; -use crate::ssa_refactor::ir::{ +use crate::ssa::ir::{ basic_block::BasicBlockId, function::{Function, FunctionId}, instruction::{Binary, BinaryOp, Instruction, TerminatorInstruction}, @@ -363,7 +363,7 @@ mod tests { use acvm::FieldElement; - use crate::ssa_refactor::ir::{ + use crate::ssa::ir::{ function::RuntimeType, instruction::{Endian, Intrinsic}, map::Id, diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs similarity index 98% rename from crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs rename to crates/noirc_evaluator/src/ssa/ssa_gen/context.rs index a526d93f85b..3e0bbff2a83 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs @@ -9,14 +9,14 @@ use noirc_frontend::monomorphization::ast::{self, LocalId, Parameters}; use noirc_frontend::monomorphization::ast::{FuncId, Program}; use noirc_frontend::{BinaryOpKind, Signedness}; -use crate::ssa_refactor::ir::dfg::DataFlowGraph; -use crate::ssa_refactor::ir::function::FunctionId as IrFunctionId; -use crate::ssa_refactor::ir::function::{Function, RuntimeType}; -use crate::ssa_refactor::ir::instruction::{BinaryOp, Endian, Intrinsic}; -use crate::ssa_refactor::ir::map::AtomicCounter; -use crate::ssa_refactor::ir::types::{NumericType, Type}; -use crate::ssa_refactor::ir::value::ValueId; -use crate::ssa_refactor::ssa_builder::FunctionBuilder; +use crate::ssa::ir::dfg::DataFlowGraph; +use crate::ssa::ir::function::FunctionId as IrFunctionId; +use crate::ssa::ir::function::{Function, RuntimeType}; +use crate::ssa::ir::instruction::{BinaryOp, Endian, Intrinsic}; +use crate::ssa::ir::map::AtomicCounter; +use crate::ssa::ir::types::{NumericType, Type}; +use crate::ssa::ir::value::ValueId; +use crate::ssa::ssa_builder::FunctionBuilder; use super::value::{Tree, Value, Values}; diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/mod.rs similarity index 100% rename from crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs rename to crates/noirc_evaluator/src/ssa/ssa_gen/mod.rs diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/program.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/program.rs similarity index 98% rename from crates/noirc_evaluator/src/ssa_refactor/ssa_gen/program.rs rename to crates/noirc_evaluator/src/ssa/ssa_gen/program.rs index aec0e4262c8..509f778f3b0 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/program.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_gen/program.rs @@ -2,7 +2,7 @@ use std::{collections::BTreeMap, fmt::Display}; use iter_extended::btree_map; -use crate::ssa_refactor::ir::{ +use crate::ssa::ir::{ function::{Function, FunctionId}, map::AtomicCounter, }; diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/value.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/value.rs similarity index 98% rename from crates/noirc_evaluator/src/ssa_refactor/ssa_gen/value.rs rename to crates/noirc_evaluator/src/ssa/ssa_gen/value.rs index 2d209635610..e7bb515465b 100644 --- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/value.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_gen/value.rs @@ -1,7 +1,7 @@ use iter_extended::vecmap; -use crate::ssa_refactor::ir::types::Type; -use crate::ssa_refactor::ir::value::ValueId as IrValueId; +use crate::ssa::ir::types::Type; +use crate::ssa::ir::value::ValueId as IrValueId; use super::context::FunctionContext; From ed67b10f0180aa93b04bcbd7a65864f2d898dadf Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Wed, 2 Aug 2023 21:37:22 +0200 Subject: [PATCH 33/50] chore: Initialize copy array from previous values in `array_set` (#2106) * Initialize copy array from previous values in array_set * chore: use `try_vecmap` in place of for-loop * Update crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs * Update crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs --------- Co-authored-by: Tom French Co-authored-by: jfecher --- crates/noirc_evaluator/src/ssa/acir_gen/mod.rs | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs index 331c56f59d7..f1e71922b0b 100644 --- a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs @@ -589,19 +589,17 @@ impl Context { let result_array_id = result_id.to_usize() as u32; let result_block_id = BlockId(result_array_id); - // Initialize the new array with zero values - self.initialize_array(result_block_id, len, None)?; - - // Copy the values from the old array into the newly created zeroed array - for i in 0..len { + // Initialize the new array with the values from the old array + let init_values = try_vecmap(0..len, |i| { let index = AcirValue::Var( self.acir_context.add_constant(FieldElement::from(i as u128)), AcirType::NumericType(NumericType::NativeField), ); let var = index.into_var()?; let read = self.acir_context.read_from_memory(block_id, &var)?; - self.acir_context.write_to_memory(result_block_id, &var, &read)?; - } + Ok(AcirValue::Var(read, AcirType::NumericType(NumericType::NativeField))) + })?; + self.initialize_array(result_block_id, len, Some(&init_values))?; // Write the new value into the new array at the specified index let index_var = self.convert_value(index, dfg).into_var()?; From f3f6fbe45254ea206b778d191861498eef880064 Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Wed, 2 Aug 2023 21:38:28 +0200 Subject: [PATCH 34/50] chore: Decouple acir blockid from ssa valueid (#2103) Decouple acir blokid from ssa valueid Co-authored-by: Tom French --- .../noirc_evaluator/src/ssa/acir_gen/mod.rs | 36 ++++++++++++++----- 1 file changed, 28 insertions(+), 8 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs index f1e71922b0b..25a0c2ee2e8 100644 --- a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs @@ -55,6 +55,15 @@ struct Context { /// This set is used to ensure that a MemoryOp opcode is only pushed to the circuit /// if there is already a MemoryInit opcode. initialized_arrays: HashSet, + + /// Maps SSA values to BlockId + /// A BlockId is an ACIR structure which identifies a memory block + /// Each acir memory block corresponds to a different SSA array. + memory_blocks: HashMap, BlockId>, + + /// Number of the next BlockId, it is used to construct + /// a new BlockId + max_block_id: u32, } #[derive(Clone)] @@ -139,6 +148,8 @@ impl Context { current_side_effects_enabled_var, acir_context, initialized_arrays: HashSet::new(), + memory_blocks: HashMap::new(), + max_block_id: 0, } } @@ -221,7 +232,7 @@ impl Context { match &value { AcirValue::Var(_, _) => (), AcirValue::Array(values) => { - let block_id = BlockId(param_id.to_usize() as u32); + let block_id = self.block_id(param_id); let v = vecmap(values, |v| v.clone()); self.initialize_array(block_id, values.len(), Some(&v))?; } @@ -264,6 +275,18 @@ impl Context { } } + /// Get the BlockId corresponding to the ValueId + /// If there is no matching BlockId, we create a new one. + fn block_id(&mut self, value: &ValueId) -> BlockId { + if let Some(block_id) = self.memory_blocks.get(value) { + return *block_id; + } + let block_id = BlockId(self.max_block_id); + self.max_block_id += 1; + self.memory_blocks.insert(*value, block_id); + block_id + } + /// Creates an `AcirVar` corresponding to a parameter witness to appears in the abi. A range /// constraint is added if the numeric type requires it. /// @@ -500,7 +523,7 @@ impl Context { dfg: &DataFlowGraph, ) -> Result<(), RuntimeError> { let array = dfg.resolve(array); - let block_id = BlockId(array.to_usize() as u32); + let block_id = self.block_id(&array); if !self.initialized_arrays.contains(&block_id) { match &dfg[array] { Value::Array { array, .. } => { @@ -548,11 +571,9 @@ impl Context { ) -> Result<(), InternalError> { // Fetch the internal SSA ID for the array let array = dfg.resolve(array); - let array_ssa_id = array.to_usize() as u32; - // Use the SSA ID to create a block ID - // There is currently a 1-1 mapping from array SSA ID to block ID - let block_id = BlockId(array_ssa_id); + // Use the SSA ID to get or create its block ID + let block_id = self.block_id(&array); // Every array has a length in its type, so we fetch that from // the SSA IR. @@ -586,8 +607,7 @@ impl Context { .instruction_results(instruction) .first() .expect("Array set does not have one result"); - let result_array_id = result_id.to_usize() as u32; - let result_block_id = BlockId(result_array_id); + let result_block_id = self.block_id(result_id); // Initialize the new array with the values from the old array let init_values = try_vecmap(0..len, |i| { From 35404ba9b2916cebf35519546eec0f0ae54b5516 Mon Sep 17 00:00:00 2001 From: Alexander Ivanov Date: Wed, 2 Aug 2023 23:09:01 +0300 Subject: [PATCH 35/50] =?UTF-8?q?feat:=20Initial=20work=20on=20rewriting?= =?UTF-8?q?=20closures=20to=20regular=20functions=20with=20hi=E2=80=A6=20(?= =?UTF-8?q?#1959)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * feat: Initial work on rewriting closures to regular functions with hidden env This commit implements the following mechanism: On a line where a lambda expression is encountered, we initialize a tuple for the captured lambda environment and we rewrite the lambda to a regular function taking this environment as an additional parameter. All calls to the closure are then modified to insert this hidden parameter. In other words, the following code: ``` let x = some_value; let closure = |a| x + a; println(closure(10)); println(closure(20)); ``` is rewritten to: ``` fn closure(env: (Field,), a: Field) -> Field { env.0 + a } let x = some_value; let closure_env = (x,); println(closure(closure_env, 10)); println(closure(closure_env, 20)); ``` In the presence of nested closures, we propagate the captured variables implicitly through all intermediate closures: ``` let x = some_value; let closure = |a, c| # here, `x` is initialized from the hidden env of the outer closure let inner_closure = |b| a + b + x inner_closure(c) ``` To make these transforms possible, the following changes were made to the logic of the HIR resolver and the monomorphization pass: * In the HIR resolver pass, the code determines the precise list of variables captured by each lambda. Along with the list, we compute the index of each captured var within the parent closure's environment (when the capture is propagated). * Introduction of a new `Closure` type in order to be able to recognize the call-sites that need the automatic environment variable treatment. It's a bit unfortunate that the Closure type is defined within the `AST` modules that are used to describe the output of the monomorphization pass, because we aim to eliminate all closures during the pass. A better solution would have been possible if the type check pass after HIR resolution was outputting types specific to the HIR pass (then the closures would exist only within this separate non-simplified type system). * The majority of the work is in the Lambda processing step in the monomorphizer which performs the necessary transformations based on the above information. Remaining things to do: * There are a number of pending TODO items for various minor unresolved loose ends in the code. * There are a lot of possible additional tests to be written. * Update docs * refactor: use panic, instead of println+assert Co-authored-by: jfecher * test: add an initial monomorphization rewrite test a lot of the machinery is copied from similar existing tests the original authors also note some of those can be refactored in something reusable * fix: address some PR comments: comment/refactor/small fixes * fix: use an unified Function object, fix some problems, comments * fix: fix code, addressing `cargo clippy` warnings * fix: replace type_of usage and remove it, as hinted in review * test: move closure-related tests to test_data * test: update closure rewrite test output * chore: apply cargo fmt changes * test: capture some variables in some tests, fix warnings, add a TODO add a TODO about returning closures * test: add simplification of #1088 as a resolve test, enable another test * fix: fix unify for closures, fix display for fn/closure types * test: update closure tests after resolving mutable bug * fix: address some review comments for closure PR: fixes/cleanup * refactor: cleanup, remove a line Co-authored-by: jfecher * refactor: cleanup Co-authored-by: jfecher * fix: fix bind_function_type env_type handling type variable binding * test: improve higher_order_fn_selector test * fix: remove skip_params/additional param logic from typechecking/display * fix: don't use closure capture logic for lambdas without captures * fix: apply cargo fmt & clippy * chore: apply cargo fmt * test: fix closure rewrite test: actually capture * chore: remove type annotation for `params` * chore: run cargo fmt --------- Co-authored-by: jfecher Co-authored-by: Alex Vitkov --- .../test_data/closures_mut_ref/Nargo.toml | 6 + .../test_data/closures_mut_ref/Prover.toml | 1 + .../test_data/closures_mut_ref/src/main.nr | 20 + .../higher_order_fn_selector/Nargo.toml | 6 + .../higher_order_fn_selector/src/main.nr | 39 ++ .../higher_order_functions/Nargo.toml | 6 + .../higher_order_functions/Prover.toml | 0 .../higher_order_functions/src/main.nr | 87 ++++ .../higher_order_functions/target/c.json | 1 + .../higher_order_functions/target/main.json | 1 + .../higher_order_functions/target/witness.tr | Bin 0 -> 112 bytes .../tests/test_data/inner_outer_cl/Nargo.toml | 6 + .../test_data/inner_outer_cl/src/main.nr | 12 + .../tests/test_data/ret_fn_ret_cl/Nargo.toml | 6 + .../tests/test_data/ret_fn_ret_cl/Prover.toml | 1 + .../tests/test_data/ret_fn_ret_cl/src/main.nr | 39 ++ .../src/ssa/ssa_gen/context.rs | 2 +- .../src/hir/def_collector/dc_crate.rs | 4 +- .../src/hir/resolution/resolver.rs | 345 ++++++++++++-- .../noirc_frontend/src/hir/type_check/expr.rs | 73 +-- .../noirc_frontend/src/hir/type_check/mod.rs | 29 +- crates/noirc_frontend/src/hir_def/expr.rs | 16 + crates/noirc_frontend/src/hir_def/function.rs | 4 +- crates/noirc_frontend/src/hir_def/types.rs | 52 ++- .../src/monomorphization/ast.rs | 17 +- .../src/monomorphization/mod.rs | 428 +++++++++++++++++- crates/noirc_frontend/src/node_interner.rs | 2 +- 27 files changed, 1078 insertions(+), 125 deletions(-) create mode 100644 crates/nargo_cli/tests/test_data/closures_mut_ref/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/closures_mut_ref/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/closures_mut_ref/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/higher_order_fn_selector/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/higher_order_fn_selector/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr create mode 100644 crates/nargo_cli/tests/test_data/inner_outer_cl/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/inner_outer_cl/src/main.nr create mode 100644 crates/nargo_cli/tests/test_data/ret_fn_ret_cl/Nargo.toml create mode 100644 crates/nargo_cli/tests/test_data/ret_fn_ret_cl/Prover.toml create mode 100644 crates/nargo_cli/tests/test_data/ret_fn_ret_cl/src/main.nr diff --git a/crates/nargo_cli/tests/test_data/closures_mut_ref/Nargo.toml b/crates/nargo_cli/tests/test_data/closures_mut_ref/Nargo.toml new file mode 100644 index 00000000000..c829bb160b1 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/closures_mut_ref/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "closures_mut_ref" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/closures_mut_ref/Prover.toml b/crates/nargo_cli/tests/test_data/closures_mut_ref/Prover.toml new file mode 100644 index 00000000000..11497a473bc --- /dev/null +++ b/crates/nargo_cli/tests/test_data/closures_mut_ref/Prover.toml @@ -0,0 +1 @@ +x = "0" diff --git a/crates/nargo_cli/tests/test_data/closures_mut_ref/src/main.nr b/crates/nargo_cli/tests/test_data/closures_mut_ref/src/main.nr new file mode 100644 index 00000000000..ae990e004fd --- /dev/null +++ b/crates/nargo_cli/tests/test_data/closures_mut_ref/src/main.nr @@ -0,0 +1,20 @@ +use dep::std; + +fn main(mut x: Field) { + let one = 1; + let add1 = |z| { + *z = *z + one; + }; + + let two = 2; + let add2 = |z| { + *z = *z + two; + }; + + add1(&mut x); + assert(x == 1); + + add2(&mut x); + assert(x == 3); + +} diff --git a/crates/nargo_cli/tests/test_data/higher_order_fn_selector/Nargo.toml b/crates/nargo_cli/tests/test_data/higher_order_fn_selector/Nargo.toml new file mode 100644 index 00000000000..3c2277e35a5 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_fn_selector/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "higher_order_fn_selector" +authors = [""] +compiler_version = "0.8.0" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/higher_order_fn_selector/src/main.nr b/crates/nargo_cli/tests/test_data/higher_order_fn_selector/src/main.nr new file mode 100644 index 00000000000..767cff0c409 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_fn_selector/src/main.nr @@ -0,0 +1,39 @@ +use dep::std; + +fn g(x: &mut Field) -> () { + *x *= 2; +} + +fn h(x: &mut Field) -> () { + *x *= 3; +} + +fn selector(flag: &mut bool) -> fn(&mut Field) -> () { + let my_func = if *flag { + g + } else { + h + }; + + // Flip the flag for the next function call + *flag = !(*flag); + my_func +} + +fn main() { + + let mut flag: bool = true; + + let mut x: Field = 100; + let returned_func = selector(&mut flag); + returned_func(&mut x); + + assert(x == 200); + + let mut y: Field = 100; + let returned_func2 = selector(&mut flag); + returned_func2(&mut y); + + assert(y == 300); + +} diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml b/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml new file mode 100644 index 00000000000..cf7526abc7f --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml @@ -0,0 +1,6 @@ +[package] +name = "higher_order_functions" +authors = [""] +compiler_version = "0.1" + +[dependencies] \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/Prover.toml b/crates/nargo_cli/tests/test_data/higher_order_functions/Prover.toml new file mode 100644 index 00000000000..e69de29bb2d diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr b/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr new file mode 100644 index 00000000000..fefd23b7dbc --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr @@ -0,0 +1,87 @@ +use dep::std; + +fn main() -> pub Field { + let f = if 3 * 7 > 200 as u32 { foo } else { bar }; + assert(f()[1] == 2); + // Lambdas: + assert(twice(|x| x * 2, 5) == 20); + assert((|x, y| x + y + 1)(2, 3) == 6); + + // nested lambdas + assert((|a, b| { + a + (|c| c + 2)(b) + })(0, 1) == 3); + + + // Closures: + let a = 42; + let g = || a; + assert(g() == 42); + + // When you copy mutable variables, + // the capture of the copies shouldn't change: + let mut x = 2; + x = x + 1; + let z = x; + + // Add extra mutations to ensure we can mutate x without the + // captured z changing. + x = x + 1; + assert((|y| y + z)(1) == 4); + + // When you capture mutable variables, + // again, the captured variable doesn't change: + let closure_capturing_mutable = (|y| y + x); + assert(closure_capturing_mutable(1) == 5); + x += 1; + assert(closure_capturing_mutable(1) == 5); + + let ret = twice(add1, 3); + + test_array_functions(); + ret +} + +/// Test the array functions in std::array +fn test_array_functions() { + let myarray: [i32; 3] = [1, 2, 3]; + assert(myarray.any(|n| n > 2)); + + let evens: [i32; 3] = [2, 4, 6]; + assert(evens.all(|n| n > 1)); + + assert(evens.fold(0, |a, b| a + b) == 12); + assert(evens.reduce(|a, b| a + b) == 12); + + // TODO: is this a sort_via issue with the new backend, + // or something more general? + // + // currently it fails only with `--experimental-ssa` with + // "not yet implemented: Cast into signed" + // but it worked with the original ssa backend + // (before dropping it) + // + // opened #2121 for it + // https://github.com/noir-lang/noir/issues/2121 + + // let descending = myarray.sort_via(|a, b| a > b); + // assert(descending == [3, 2, 1]); + + assert(evens.map(|n| n / 2) == myarray); +} + +fn foo() -> [u32; 2] { + [1, 3] +} + +fn bar() -> [u32; 2] { + [3, 2] +} + +fn add1(x: Field) -> Field { + x + 1 +} + +fn twice(f: fn(Field) -> Field, x: Field) -> Field { + f(f(x)) +} diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json b/crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json new file mode 100644 index 00000000000..c1233b8160b --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json @@ -0,0 +1 @@ +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":[155,194,56,97,194,4,0],"proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json b/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json new file mode 100644 index 00000000000..8d7a1566313 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json @@ -0,0 +1 @@ +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WUTW6DMBSEJ/yFhoY26bYLjoAxBLPrVYpK7n+EgmoHamWXeShYQsYSvJ+Z9/kDwCf+1m58ArsXi3PgnUN7dt/u7P9fdi8fW8rlATduCW89GFe5l2iMES90YBd+EyTyjIjtGYIm+HF1eanroa0GpdV3WXW9acq66S9GGdWY5qcyWg+mNm3Xd23ZqVoP6tp0+moDJ5AxNOTUWdk6VUTsOSb6wtRPCuDYziaZAzGA92OMFCsAPCUqMAOcQg5gZwIb4BdsA+A9seeU6AtTPymAUzubZA7EAD6MMTKsAPCUqMAMcAY5gJ0JbIBfsQ2AD8SeM6IvTP2kAM7sbJI5EAP4OMbIsQLAU6ICM8A55AB2JrABfsM2AD4Se86Jvjy5freeQ2LPObGud6J+Ce5ADz6LzJqX9Z4W75HdgzszkQj0BC+Pr6PohSpl0kkg7hm84Zfq+8z36N/l9OyaLtcv2EfpKJUUAAA=","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr b/crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr new file mode 100644 index 0000000000000000000000000000000000000000..a539f87a55498eeaff3e546ac9126cea0091fa70 GIT binary patch literal 112 zcmV-$0FVD4iwFP!00002|E<$W3cw%?h2hTg=t&aVF5LAhrT4#sir&CKAZGQE2Z Field { + x + 1 +} + +fn ret_fn() -> fn(Field) -> Field { + f +} + +// TODO: in the advanced implicitly generic function with closures branch +// which would support higher-order functions in a better way +// support returning closures: +// +// fn ret_closure() -> fn(Field) -> Field { +// let y = 1; +// let inner_closure = |z| -> Field{ +// z + y +// }; +// inner_closure +// } + +fn ret_lambda() -> fn(Field) -> Field { + let cl = |z: Field| -> Field { + z + 1 + }; + cl +} + +fn main(x : Field) { + let result_fn = ret_fn(); + assert(result_fn(x) == x + 1); + + // let result_closure = ret_closure(); + // assert(result_closure(x) == x + 1); + + let result_lambda = ret_lambda(); + assert(result_lambda(x) == x + 1); +} diff --git a/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs index 3e0bbff2a83..c3578e5ee7e 100644 --- a/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs @@ -218,7 +218,7 @@ impl<'a> FunctionContext<'a> { } ast::Type::Unit => panic!("convert_non_tuple_type called on a unit type"), ast::Type::Tuple(_) => panic!("convert_non_tuple_type called on a tuple: {typ}"), - ast::Type::Function(_, _) => Type::Function, + ast::Type::Function(_, _, _) => Type::Function, ast::Type::Slice(element) => { let element_types = Self::convert_type(element).flatten(); Type::Slice(Rc::new(element_types)) diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs index 76fbea289be..2beebf6871c 100644 --- a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs +++ b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs @@ -12,8 +12,8 @@ use crate::hir::type_check::{type_check_func, TypeChecker}; use crate::hir::Context; use crate::node_interner::{FuncId, NodeInterner, StmtId, StructId, TypeAliasId}; use crate::{ - ExpressionKind, Generics, Ident, LetStatement, NoirFunction, NoirStruct, NoirTypeAlias, - ParsedModule, Shared, Type, TypeBinding, UnresolvedGenerics, UnresolvedType, Literal, + ExpressionKind, Generics, Ident, LetStatement, Literal, NoirFunction, NoirStruct, + NoirTypeAlias, ParsedModule, Shared, Type, TypeBinding, UnresolvedGenerics, UnresolvedType, }; use fm::FileId; use iter_extended::vecmap; diff --git a/crates/noirc_frontend/src/hir/resolution/resolver.rs b/crates/noirc_frontend/src/hir/resolution/resolver.rs index 8b4f97dbd8e..681c853899f 100644 --- a/crates/noirc_frontend/src/hir/resolution/resolver.rs +++ b/crates/noirc_frontend/src/hir/resolution/resolver.rs @@ -12,10 +12,10 @@ // // XXX: Resolver does not check for unused functions use crate::hir_def::expr::{ - HirArrayLiteral, HirBinaryOp, HirBlockExpression, HirCallExpression, HirCastExpression, - HirConstructorExpression, HirExpression, HirForExpression, HirIdent, HirIfExpression, - HirIndexExpression, HirInfixExpression, HirLambda, HirLiteral, HirMemberAccess, - HirMethodCallExpression, HirPrefixExpression, + HirArrayLiteral, HirBinaryOp, HirBlockExpression, HirCallExpression, HirCapturedVar, + HirCastExpression, HirConstructorExpression, HirExpression, HirForExpression, HirIdent, + HirIfExpression, HirIndexExpression, HirInfixExpression, HirLambda, HirLiteral, + HirMemberAccess, HirMethodCallExpression, HirPrefixExpression, }; use crate::token::Attribute; use regex::Regex; @@ -58,6 +58,13 @@ type Scope = GenericScope; type ScopeTree = GenericScopeTree; type ScopeForest = GenericScopeForest; +pub struct LambdaContext { + captures: Vec, + /// the index in the scope tree + /// (sometimes being filled by ScopeTree's find method) + scope_index: usize, +} + /// The primary jobs of the Resolver are to validate that every variable found refers to exactly 1 /// definition in scope, and to convert the AST into the HIR. /// @@ -81,12 +88,10 @@ pub struct Resolver<'a> { /// were declared in. generics: Vec<(Rc, TypeVariable, Span)>, - /// Lambdas share the function scope of the function they're defined in, - /// so to identify whether they use any variables from the parent function - /// we keep track of the scope index a variable is declared in. When a lambda - /// is declared we push a scope and set this lambda_index to the scope index. - /// Any variable from a scope less than that must be from the parent function. - lambda_index: usize, + /// When resolving lambda expressions, we need to keep track of the variables + /// that are captured. We do this in order to create the hidden environment + /// parameter for the lambda function. + lambda_stack: Vec, } /// ResolverMetas are tagged onto each definition to track how many times they are used @@ -112,7 +117,7 @@ impl<'a> Resolver<'a> { self_type: None, generics: Vec::new(), errors: Vec::new(), - lambda_index: 0, + lambda_stack: Vec::new(), file, } } @@ -125,10 +130,6 @@ impl<'a> Resolver<'a> { self.errors.push(err); } - fn current_lambda_index(&self) -> usize { - self.scopes.current_scope_index() - } - /// Resolving a function involves interning the metadata /// interning any statements inside of the function /// and interning the function itself @@ -279,25 +280,25 @@ impl<'a> Resolver<'a> { // // If a variable is not found, then an error is logged and a dummy id // is returned, for better error reporting UX - fn find_variable_or_default(&mut self, name: &Ident) -> HirIdent { + fn find_variable_or_default(&mut self, name: &Ident) -> (HirIdent, usize) { self.find_variable(name).unwrap_or_else(|error| { self.push_err(error); let id = DefinitionId::dummy_id(); let location = Location::new(name.span(), self.file); - HirIdent { location, id } + (HirIdent { location, id }, 0) }) } - fn find_variable(&mut self, name: &Ident) -> Result { + fn find_variable(&mut self, name: &Ident) -> Result<(HirIdent, usize), ResolverError> { // Find the definition for this Ident let scope_tree = self.scopes.current_scope_tree(); let variable = scope_tree.find(&name.0.contents); let location = Location::new(name.span(), self.file); - if let Some((variable_found, _)) = variable { + if let Some((variable_found, scope)) = variable { variable_found.num_times_used += 1; let id = variable_found.ident.id; - Ok(HirIdent { location, id }) + Ok((HirIdent { location, id }, scope)) } else { Err(ResolverError::VariableNotDeclared { name: name.0.contents.clone(), @@ -363,7 +364,8 @@ impl<'a> Resolver<'a> { UnresolvedType::Function(args, ret) => { let args = vecmap(args, |arg| self.resolve_type_inner(arg, new_variables)); let ret = Box::new(self.resolve_type_inner(*ret, new_variables)); - Type::Function(args, ret) + let env = Box::new(Type::Unit); + Type::Function(args, ret, env) } UnresolvedType::MutableReference(element) => { Type::MutableReference(Box::new(self.resolve_type_inner(*element, new_variables))) @@ -517,24 +519,24 @@ impl<'a> Resolver<'a> { } } - fn get_ident_from_path(&mut self, path: Path) -> HirIdent { + fn get_ident_from_path(&mut self, path: Path) -> (HirIdent, usize) { let location = Location::new(path.span(), self.file); let error = match path.as_ident().map(|ident| self.find_variable(ident)) { - Some(Ok(ident)) => return ident, + Some(Ok(found)) => return found, // Try to look it up as a global, but still issue the first error if we fail Some(Err(error)) => match self.lookup_global(path) { - Ok(id) => return HirIdent { location, id }, + Ok(id) => return (HirIdent { location, id }, 0), Err(_) => error, }, None => match self.lookup_global(path) { - Ok(id) => return HirIdent { location, id }, + Ok(id) => return (HirIdent { location, id }, 0), Err(error) => error, }, }; self.push_err(error); let id = DefinitionId::dummy_id(); - HirIdent { location, id } + (HirIdent { location, id }, 0) } /// Translates an UnresolvedType to a Type @@ -705,7 +707,7 @@ impl<'a> Resolver<'a> { }); } - let mut typ = Type::Function(parameter_types, return_type); + let mut typ = Type::Function(parameter_types, return_type, Box::new(Type::Unit)); if !generics.is_empty() { typ = Type::Forall(generics, Box::new(typ)); @@ -837,12 +839,14 @@ impl<'a> Resolver<'a> { Self::find_numeric_generics_in_type(field, found); } } - Type::Function(parameters, return_type) => { + + Type::Function(parameters, return_type, _env) => { for parameter in parameters { Self::find_numeric_generics_in_type(parameter, found); } Self::find_numeric_generics_in_type(return_type, found); } + Type::Struct(struct_type, generics) => { for (i, generic) in generics.iter().enumerate() { if let Type::NamedGeneric(type_variable, name) = generic { @@ -915,7 +919,7 @@ impl<'a> Resolver<'a> { fn resolve_lvalue(&mut self, lvalue: LValue) -> HirLValue { match lvalue { LValue::Ident(ident) => { - HirLValue::Ident(self.find_variable_or_default(&ident), Type::Error) + HirLValue::Ident(self.find_variable_or_default(&ident).0, Type::Error) } LValue::MemberAccess { object, field_name } => { let object = Box::new(self.resolve_lvalue(*object)); @@ -933,6 +937,39 @@ impl<'a> Resolver<'a> { } } + fn resolve_local_variable(&mut self, hir_ident: HirIdent, var_scope_index: usize) { + let mut transitive_capture_index: Option = None; + + for lambda_index in 0..self.lambda_stack.len() { + if self.lambda_stack[lambda_index].scope_index > var_scope_index { + // Beware: the same variable may be captured multiple times, so we check + // for its presence before adding the capture below. + let pos = self.lambda_stack[lambda_index] + .captures + .iter() + .position(|capture| capture.ident.id == hir_ident.id); + + if pos.is_none() { + self.lambda_stack[lambda_index] + .captures + .push(HirCapturedVar { ident: hir_ident, transitive_capture_index }); + } + + if lambda_index + 1 < self.lambda_stack.len() { + // There is more than one closure between the current scope and + // the scope of the variable, so this is a propagated capture. + // We need to track the transitive capture index as we go up in + // the closure stack. + transitive_capture_index = Some(pos.unwrap_or( + // If this was a fresh capture, we added it to the end of + // the captures vector: + self.lambda_stack[lambda_index].captures.len() - 1, + )); + } + } + } + } + pub fn resolve_expression(&mut self, expr: Expression) -> ExprId { let hir_expr = match expr.kind { ExpressionKind::Literal(literal) => HirExpression::Literal(match literal { @@ -965,7 +1002,20 @@ impl<'a> Resolver<'a> { // Otherwise, then it is referring to an Identifier // This lookup allows support of such statements: let x = foo::bar::SOME_GLOBAL + 10; // If the expression is a singular indent, we search the resolver's current scope as normal. - let hir_ident = self.get_ident_from_path(path); + let (hir_ident, var_scope_index) = self.get_ident_from_path(path); + + if hir_ident.id != DefinitionId::dummy_id() { + match self.interner.definition(hir_ident.id).kind { + DefinitionKind::Function(_) => {} + DefinitionKind::Global(_) => {} + DefinitionKind::GenericType(_) => {} + // We ignore the above definition kinds because only local variables can be captured by closures. + DefinitionKind::Local(_) => { + self.resolve_local_variable(hir_ident, var_scope_index); + } + } + } + HirExpression::Ident(hir_ident) } ExpressionKind::Prefix(prefix) => { @@ -1087,8 +1137,9 @@ impl<'a> Resolver<'a> { // We must stay in the same function scope as the parent function to allow for closures // to capture variables. This is currently limited to immutable variables. ExpressionKind::Lambda(lambda) => self.in_new_scope(|this| { - let new_index = this.current_lambda_index(); - let old_index = std::mem::replace(&mut this.lambda_index, new_index); + let scope_index = this.scopes.current_scope_index(); + + this.lambda_stack.push(LambdaContext { captures: Vec::new(), scope_index }); let parameters = vecmap(lambda.parameters, |(pattern, typ)| { let parameter = DefinitionKind::Local(None); @@ -1098,8 +1149,14 @@ impl<'a> Resolver<'a> { let return_type = this.resolve_inferred_type(lambda.return_type); let body = this.resolve_expression(lambda.body); - this.lambda_index = old_index; - HirExpression::Lambda(HirLambda { parameters, return_type, body }) + let lambda_context = this.lambda_stack.pop().unwrap(); + + HirExpression::Lambda(HirLambda { + parameters, + return_type, + body, + captures: lambda_context.captures, + }) }), }; @@ -1411,6 +1468,7 @@ pub fn verify_mutable_reference(interner: &NodeInterner, rhs: ExprId) -> Result< #[cfg(test)] mod test { + use core::panic; use std::collections::HashMap; use fm::FileId; @@ -1419,10 +1477,14 @@ mod test { use crate::hir::def_map::{ModuleData, ModuleId, ModuleOrigin}; use crate::hir::resolution::errors::ResolverError; use crate::hir::resolution::import::PathResolutionError; + use crate::hir::resolution::resolver::StmtId; use crate::graph::CrateId; + use crate::hir_def::expr::HirExpression; use crate::hir_def::function::HirFunction; + use crate::hir_def::stmt::HirStatement; use crate::node_interner::{FuncId, NodeInterner}; + use crate::ParsedModule; use crate::{ hir::def_map::{CrateDefMap, LocalModuleId, ModuleDefId}, parse_program, Path, @@ -1432,29 +1494,24 @@ mod test { // func_namespace is used to emulate the fact that functions can be imported // and functions can be forward declared - fn resolve_src_code(src: &str, func_namespace: Vec<&str>) -> Vec { + fn init_src_code_resolution( + src: &str, + ) -> (ParsedModule, NodeInterner, HashMap, FileId, TestPathResolver) { let (program, errors) = parse_program(src); - assert!(errors.is_empty()); - - let mut interner = NodeInterner::default(); - - let func_ids = vecmap(&func_namespace, |name| { - let id = interner.push_fn(HirFunction::empty()); - interner.push_function_definition(name.to_string(), id); - id - }); - - let mut path_resolver = TestPathResolver(HashMap::new()); - for (name, id) in func_namespace.into_iter().zip(func_ids) { - path_resolver.insert_func(name.to_owned(), id); + if !errors.is_empty() { + panic!("Unexpected parse errors in test code: {:?}", errors); } + let interner: NodeInterner = NodeInterner::default(); + let mut def_maps: HashMap = HashMap::new(); let file = FileId::default(); let mut modules = arena::Arena::new(); modules.insert(ModuleData::new(None, ModuleOrigin::File(file), false)); + let path_resolver = TestPathResolver(HashMap::new()); + def_maps.insert( CrateId::dummy_id(), CrateDefMap { @@ -1465,10 +1522,30 @@ mod test { }, ); + (program, interner, def_maps, file, path_resolver) + } + + // func_namespace is used to emulate the fact that functions can be imported + // and functions can be forward declared + fn resolve_src_code(src: &str, func_namespace: Vec<&str>) -> Vec { + let (program, mut interner, def_maps, file, mut path_resolver) = + init_src_code_resolution(src); + + let func_ids = vecmap(&func_namespace, |name| { + let id = interner.push_fn(HirFunction::empty()); + interner.push_function_definition(name.to_string(), id); + id + }); + + for (name, id) in func_namespace.into_iter().zip(func_ids) { + path_resolver.insert_func(name.to_owned(), id); + } + let mut errors = Vec::new(); for func in program.functions { let id = interner.push_fn(HirFunction::empty()); interner.push_function_definition(func.name().to_string(), id); + let resolver = Resolver::new(&mut interner, &path_resolver, &def_maps, file); let (_, _, err) = resolver.resolve_function(func, id, ModuleId::dummy_id()); errors.extend(err); @@ -1477,6 +1554,81 @@ mod test { errors } + fn get_program_captures(src: &str) -> Vec> { + let (program, mut interner, def_maps, file, mut path_resolver) = + init_src_code_resolution(src); + + let mut all_captures: Vec> = Vec::new(); + for func in program.functions { + let id = interner.push_fn(HirFunction::empty()); + interner.push_function_definition(func.name().clone().to_string(), id); + path_resolver.insert_func(func.name().to_owned(), id); + + let resolver = Resolver::new(&mut interner, &path_resolver, &def_maps, file); + let (hir_func, _, _) = resolver.resolve_function(func, id, ModuleId::dummy_id()); + + // Iterate over function statements and apply filtering function + parse_statement_blocks( + hir_func.block(&interner).statements(), + &interner, + &mut all_captures, + ); + } + all_captures + } + + fn parse_statement_blocks( + stmts: &[StmtId], + interner: &NodeInterner, + result: &mut Vec>, + ) { + let mut expr: HirExpression; + + for stmt_id in stmts.iter() { + let hir_stmt = interner.statement(stmt_id); + match hir_stmt { + HirStatement::Expression(expr_id) => { + expr = interner.expression(&expr_id); + } + HirStatement::Let(let_stmt) => { + expr = interner.expression(&let_stmt.expression); + } + HirStatement::Assign(assign_stmt) => { + expr = interner.expression(&assign_stmt.expression); + } + HirStatement::Constrain(constr_stmt) => { + expr = interner.expression(&constr_stmt.0); + } + HirStatement::Semi(semi_expr) => { + expr = interner.expression(&semi_expr); + } + HirStatement::Error => panic!("Invalid HirStatement!"), + } + get_lambda_captures(expr, &interner, result); // TODO: dyn filter function as parameter + } + } + + fn get_lambda_captures( + expr: HirExpression, + interner: &NodeInterner, + result: &mut Vec>, + ) { + if let HirExpression::Lambda(lambda_expr) = expr { + let mut cur_capture = Vec::new(); + + for capture in lambda_expr.captures.iter() { + cur_capture.push(interner.definition(capture.ident.id).name.clone()); + } + result.push(cur_capture); + + // Check for other captures recursively within the lambda body + let hir_body_expr = interner.expression(&lambda_expr.body); + if let HirExpression::Block(block_expr) = hir_body_expr.clone() { + parse_statement_blocks(block_expr.statements(), interner, result); + } + } + } + #[test] fn resolve_empty_function() { let src = " @@ -1656,9 +1808,103 @@ mod test { x } "#; + let errors = resolve_src_code(src, vec!["main", "foo"]); + if !errors.is_empty() { + println!("Unexpected errors: {:?}", errors); + assert!(false); // there should be no errors + } + } + + #[test] + fn resolve_basic_closure() { + let src = r#" + fn main(x : Field) -> pub Field { + let closure = |y| y + x; + closure(x) + } + "#; + + let errors = resolve_src_code(src, vec!["main", "foo"]); + if !errors.is_empty() { + panic!("Unexpected errors: {:?}", errors); + } + } + + #[test] + fn resolve_simplified_closure() { + // based on bug https://github.com/noir-lang/noir/issues/1088 + + let src = r#"fn do_closure(x: Field) -> Field { + let y = x; + let ret_capture = || { + y + }; + ret_capture() + } + + fn main(x: Field) { + assert(do_closure(x) == 100); + } + + "#; + let parsed_captures = get_program_captures(src); + let mut expected_captures = vec![]; + expected_captures.push(vec!["y".to_string()]); + assert_eq!(expected_captures, parsed_captures); + } + + #[test] + fn resolve_complex_closures() { + let src = r#" + fn main(x: Field) -> pub Field { + let closure_without_captures = |x| x + x; + let a = closure_without_captures(1); + + let closure_capturing_a_param = |y| y + x; + let b = closure_capturing_a_param(2); + + let closure_capturing_a_local_var = |y| y + b; + let c = closure_capturing_a_local_var(3); + + let closure_with_transitive_captures = |y| { + let d = 5; + let nested_closure = |z| { + let doubly_nested_closure = |w| w + x + b; + a + z + y + d + x + doubly_nested_closure(4) + x + y + }; + let res = nested_closure(5); + res + }; + + a + b + c + closure_with_transitive_captures(6) + } + "#; let errors = resolve_src_code(src, vec!["main", "foo"]); assert!(errors.is_empty()); + if !errors.is_empty() { + println!("Unexpected errors: {:?}", errors); + assert!(false); // there should be no errors + } + + let expected_captures = vec![ + vec![], + vec!["x".to_string()], + vec!["b".to_string()], + vec!["x".to_string(), "b".to_string(), "a".to_string()], + vec![ + "x".to_string(), + "b".to_string(), + "a".to_string(), + "y".to_string(), + "d".to_string(), + ], + vec!["x".to_string(), "b".to_string()], + ]; + + let parsed_captures = get_program_captures(src); + + assert_eq!(expected_captures, parsed_captures); } #[test] @@ -1694,6 +1940,9 @@ mod test { } } + // possible TODO: Create a more sophisticated set of search functions over the HIR, so we can check + // that the correct variables are captured in each closure + fn path_unresolved_error(err: ResolverError, expected_unresolved_path: &str) { match err { ResolverError::PathResolutionError(PathResolutionError::Unresolved(name)) => { diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs index 24ac5f3443e..6c111a1d6a0 100644 --- a/crates/noirc_frontend/src/hir/type_check/expr.rs +++ b/crates/noirc_frontend/src/hir/type_check/expr.rs @@ -279,6 +279,12 @@ impl<'interner> TypeChecker<'interner> { Type::Tuple(vecmap(&elements, |elem| self.check_expression(elem))) } HirExpression::Lambda(lambda) => { + let captured_vars = + vecmap(lambda.captures, |capture| self.interner.id_type(capture.ident.id)); + + let env_type: Type = + if captured_vars.is_empty() { Type::Unit } else { Type::Tuple(captured_vars) }; + let params = vecmap(lambda.parameters, |(pattern, typ)| { self.bind_pattern(&pattern, typ.clone()); typ @@ -294,7 +300,8 @@ impl<'interner> TypeChecker<'interner> { expr_span: span, } }); - Type::Function(params, Box::new(lambda.return_type)) + + Type::Function(params, Box::new(lambda.return_type), Box::new(env_type)) } }; @@ -319,9 +326,9 @@ impl<'interner> TypeChecker<'interner> { argument_types: &mut [(Type, ExprId, noirc_errors::Span)], ) { let expected_object_type = match function_type { - Type::Function(args, _) => args.get(0), + Type::Function(args, _, _) => args.get(0), Type::Forall(_, typ) => match typ.as_ref() { - Type::Function(args, _) => args.get(0), + Type::Function(args, _, _) => args.get(0), typ => unreachable!("Unexpected type for function: {typ}"), }, typ => unreachable!("Unexpected type for function: {typ}"), @@ -870,6 +877,35 @@ impl<'interner> TypeChecker<'interner> { } } + fn bind_function_type_impl( + &mut self, + fn_params: &Vec, + fn_ret: &Type, + callsite_args: &Vec<(Type, ExprId, Span)>, + span: Span, + ) -> Type { + if fn_params.len() != callsite_args.len() { + self.errors.push(TypeCheckError::ParameterCountMismatch { + expected: fn_params.len(), + found: callsite_args.len(), + span, + }); + return Type::Error; + } + + for (param, (arg, _, arg_span)) in fn_params.iter().zip(callsite_args) { + arg.make_subtype_of(param, *arg_span, &mut self.errors, || { + TypeCheckError::TypeMismatch { + expected_typ: param.to_string(), + expr_typ: arg.to_string(), + expr_span: *arg_span, + } + }); + } + + fn_ret.clone() + } + fn bind_function_type( &mut self, function: Type, @@ -886,38 +922,17 @@ impl<'interner> TypeChecker<'interner> { let ret = self.interner.next_type_variable(); let args = vecmap(args, |(arg, _, _)| arg); - let expected = Type::Function(args, Box::new(ret.clone())); + let env_type = self.interner.next_type_variable(); + let expected = Type::Function(args, Box::new(ret.clone()), Box::new(env_type)); if let Err(error) = binding.borrow_mut().bind_to(expected, span) { self.errors.push(error); } ret } - Type::Function(parameters, ret) => { - if parameters.len() != args.len() { - self.errors.push(TypeCheckError::ParameterCountMismatch { - expected: parameters.len(), - found: args.len(), - span, - }); - return Type::Error; - } - - for (param, (arg, arg_id, arg_span)) in parameters.iter().zip(args) { - arg.make_subtype_with_coercions( - param, - arg_id, - self.interner, - &mut self.errors, - || TypeCheckError::TypeMismatch { - expected_typ: param.to_string(), - expr_typ: arg.to_string(), - expr_span: arg_span, - }, - ); - } - - *ret + Type::Function(parameters, ret, _env) => { + // ignoring env for subtype on purpose + self.bind_function_type_impl(parameters.as_ref(), ret.as_ref(), args.as_ref(), span) } Type::Error => Type::Error, found => { diff --git a/crates/noirc_frontend/src/hir/type_check/mod.rs b/crates/noirc_frontend/src/hir/type_check/mod.rs index 26d0e36abf9..1883c0abf62 100644 --- a/crates/noirc_frontend/src/hir/type_check/mod.rs +++ b/crates/noirc_frontend/src/hir/type_check/mod.rs @@ -152,6 +152,7 @@ impl<'interner> TypeChecker<'interner> { #[cfg(test)] mod test { use std::collections::HashMap; + use std::vec; use fm::FileId; use iter_extended::vecmap; @@ -245,7 +246,11 @@ mod test { contract_function_type: None, is_internal: None, is_unconstrained: false, - typ: Type::Function(vec![Type::field(None), Type::field(None)], Box::new(Type::Unit)), + typ: Type::Function( + vec![Type::field(None), Type::field(None)], + Box::new(Type::Unit), + Box::new(Type::Unit), + ), parameters: vec![ Param(Identifier(x), Type::field(None), noirc_abi::AbiVisibility::Private), Param(Identifier(y), Type::field(None), noirc_abi::AbiVisibility::Private), @@ -314,7 +319,29 @@ mod test { type_check_src_code(src, vec![String::from("main"), String::from("foo")]); } + #[test] + fn basic_closure() { + let src = r#" + fn main(x : Field) -> pub Field { + let closure = |y| y + x; + closure(x) + } + "#; + + type_check_src_code(src, vec![String::from("main"), String::from("foo")]); + } + #[test] + fn closure_with_no_args() { + let src = r#" + fn main(x : Field) -> pub Field { + let closure = || x; + closure() + } + "#; + + type_check_src_code(src, vec![String::from("main")]); + } // This is the same Stub that is in the resolver, maybe we can pull this out into a test module and re-use? struct TestPathResolver(HashMap); diff --git a/crates/noirc_frontend/src/hir_def/expr.rs b/crates/noirc_frontend/src/hir_def/expr.rs index db7db0a803d..fd980328f5f 100644 --- a/crates/noirc_frontend/src/hir_def/expr.rs +++ b/crates/noirc_frontend/src/hir_def/expr.rs @@ -197,9 +197,25 @@ impl HirBlockExpression { } } +/// A variable captured inside a closure +#[derive(Debug, Clone)] +pub struct HirCapturedVar { + pub ident: HirIdent, + + /// This will be None when the capture refers to a local variable declared + /// in the same scope as the closure. In a closure-inside-another-closure + /// scenarios, we might have a transitive captures of variables that must + /// be propagated during the construction of each closure. In this case, + /// we store the index of the captured variable in the environment of our + /// direct parent closure. We do this in order to simplify the HIR to AST + /// transformation in the monomorphization pass. + pub transitive_capture_index: Option, +} + #[derive(Debug, Clone)] pub struct HirLambda { pub parameters: Vec<(HirPattern, Type)>, pub return_type: Type, pub body: ExprId, + pub captures: Vec, } diff --git a/crates/noirc_frontend/src/hir_def/function.rs b/crates/noirc_frontend/src/hir_def/function.rs index a69e8bb08b5..225731626f0 100644 --- a/crates/noirc_frontend/src/hir_def/function.rs +++ b/crates/noirc_frontend/src/hir_def/function.rs @@ -180,9 +180,9 @@ impl FuncMeta { /// Gives the (uninstantiated) return type of this function. pub fn return_type(&self) -> &Type { match &self.typ { - Type::Function(_, ret) => ret, + Type::Function(_, ret, _env) => ret, Type::Forall(_, typ) => match typ.as_ref() { - Type::Function(_, ret) => ret, + Type::Function(_, ret, _env) => ret, _ => unreachable!(), }, _ => unreachable!(), diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs index ff0a4e53fae..d77b8033ba1 100644 --- a/crates/noirc_frontend/src/hir_def/types.rs +++ b/crates/noirc_frontend/src/hir_def/types.rs @@ -70,8 +70,11 @@ pub enum Type { /// like `fn foo(...) {}`. Unlike TypeVariables, they cannot be bound over. NamedGeneric(TypeVariable, Rc), - /// A functions with arguments, and a return type. - Function(Vec, Box), + /// A functions with arguments, a return type and environment. + /// the environment should be `Unit` by default, + /// for closures it should contain a `Tuple` type with the captured + /// variable types. + Function(Vec, Box, Box), /// &mut T MutableReference(Box), @@ -697,9 +700,10 @@ impl Type { Type::Tuple(fields) => { fields.iter().any(|field| field.contains_numeric_typevar(target_id)) } - Type::Function(parameters, return_type) => { + Type::Function(parameters, return_type, env) => { parameters.iter().any(|parameter| parameter.contains_numeric_typevar(target_id)) || return_type.contains_numeric_typevar(target_id) + || env.contains_numeric_typevar(target_id) } Type::Struct(struct_type, generics) => { generics.iter().enumerate().any(|(i, generic)| { @@ -797,9 +801,15 @@ impl std::fmt::Display for Type { let typevars = vecmap(typevars, |(var, _)| var.to_string()); write!(f, "forall {}. {}", typevars.join(" "), typ) } - Type::Function(args, ret) => { - let args = vecmap(args, ToString::to_string); - write!(f, "fn({}) -> {}", args.join(", "), ret) + Type::Function(args, ret, env) => { + let closure_env_text = match **env { + Type::Unit => "".to_string(), + _ => format!(" with closure environment {env}"), + }; + + let args = vecmap(args.iter(), ToString::to_string); + + write!(f, "fn({}) -> {ret}{closure_env_text}", args.join(", ")) } Type::MutableReference(element) => { write!(f, "&mut {element}") @@ -1196,9 +1206,9 @@ impl Type { } } - (Function(params_a, ret_a), Function(params_b, ret_b)) => { + (Function(params_a, ret_a, _env_a), Function(params_b, ret_b, _env_b)) => { if params_a.len() == params_b.len() { - for (a, b) in params_a.iter().zip(params_b) { + for (a, b) in params_a.iter().zip(params_b.iter()) { a.try_unify(b, span)?; } @@ -1403,7 +1413,7 @@ impl Type { } } - (Function(params_a, ret_a), Function(params_b, ret_b)) => { + (Function(params_a, ret_a, _env_a), Function(params_b, ret_b, _env_b)) => { if params_a.len() == params_b.len() { for (a, b) in params_a.iter().zip(params_b) { a.is_subtype_of(b, span)?; @@ -1505,7 +1515,7 @@ impl Type { Type::TypeVariable(_, _) => unreachable!(), Type::NamedGeneric(..) => unreachable!(), Type::Forall(..) => unreachable!(), - Type::Function(_, _) => unreachable!(), + Type::Function(_, _, _) => unreachable!(), Type::MutableReference(_) => unreachable!("&mut cannot be used in the abi"), Type::NotConstant => unreachable!(), } @@ -1620,10 +1630,11 @@ impl Type { let typ = Box::new(typ.substitute(type_bindings)); Type::Forall(typevars.clone(), typ) } - Type::Function(args, ret) => { + Type::Function(args, ret, env) => { let args = vecmap(args, |arg| arg.substitute(type_bindings)); let ret = Box::new(ret.substitute(type_bindings)); - Type::Function(args, ret) + let env = Box::new(env.substitute(type_bindings)); + Type::Function(args, ret, env) } Type::MutableReference(element) => { Type::MutableReference(Box::new(element.substitute(type_bindings))) @@ -1660,8 +1671,10 @@ impl Type { Type::Forall(typevars, typ) => { !typevars.iter().any(|(id, _)| *id == target_id) && typ.occurs(target_id) } - Type::Function(args, ret) => { - args.iter().any(|arg| arg.occurs(target_id)) || ret.occurs(target_id) + Type::Function(args, ret, env) => { + args.iter().any(|arg| arg.occurs(target_id)) + || ret.occurs(target_id) + || env.occurs(target_id) } Type::MutableReference(element) => element.occurs(target_id), @@ -1706,11 +1719,13 @@ impl Type { self.clone() } - Function(args, ret) => { + Function(args, ret, env) => { let args = vecmap(args, |arg| arg.follow_bindings()); let ret = Box::new(ret.follow_bindings()); - Function(args, ret) + let env = Box::new(env.follow_bindings()); + Function(args, ret, env) } + MutableReference(element) => MutableReference(Box::new(element.follow_bindings())), // Expect that this function should only be called on instantiated types @@ -1751,7 +1766,10 @@ fn convert_array_expression_to_slice( interner.push_expr_location(func, location.span, location.file); interner.push_expr_type(&call, target_type.clone()); - interner.push_expr_type(&func, Type::Function(vec![array_type], Box::new(target_type))); + interner.push_expr_type( + &func, + Type::Function(vec![array_type], Box::new(target_type), Box::new(Type::Unit)), + ); } impl BinaryTypeOperator { diff --git a/crates/noirc_frontend/src/monomorphization/ast.rs b/crates/noirc_frontend/src/monomorphization/ast.rs index 7ad05f09231..33c3bbebff4 100644 --- a/crates/noirc_frontend/src/monomorphization/ast.rs +++ b/crates/noirc_frontend/src/monomorphization/ast.rs @@ -29,7 +29,6 @@ pub enum Expression { Tuple(Vec), ExtractTupleField(Box, usize), Call(Call), - Let(Let), Constrain(Box, Location), Assign(Assign), @@ -103,6 +102,12 @@ pub struct Binary { pub location: Location, } +#[derive(Debug, Clone)] +pub struct Lambda { + pub function: Ident, + pub env: Ident, +} + #[derive(Debug, Clone)] pub struct If { pub condition: Box, @@ -213,7 +218,7 @@ pub enum Type { Tuple(Vec), Slice(Box), MutableReference(Box), - Function(/*args:*/ Vec, /*ret:*/ Box), + Function(/*args:*/ Vec, /*ret:*/ Box, /*env:*/ Box), } impl Type { @@ -324,9 +329,13 @@ impl std::fmt::Display for Type { let elements = vecmap(elements, ToString::to_string); write!(f, "({})", elements.join(", ")) } - Type::Function(args, ret) => { + Type::Function(args, ret, env) => { let args = vecmap(args, ToString::to_string); - write!(f, "fn({}) -> {}", args.join(", "), ret) + let closure_env_text = match **env { + Type::Unit => "".to_string(), + _ => format!(" with closure environment {env}"), + }; + write!(f, "fn({}) -> {}{}", args.join(", "), ret, closure_env_text) } Type::Slice(element) => write!(f, "[{element}"), Type::MutableReference(element) => write!(f, "&mut {element}"), diff --git a/crates/noirc_frontend/src/monomorphization/mod.rs b/crates/noirc_frontend/src/monomorphization/mod.rs index dbe2ee080bf..c8167baf6bb 100644 --- a/crates/noirc_frontend/src/monomorphization/mod.rs +++ b/crates/noirc_frontend/src/monomorphization/mod.rs @@ -19,6 +19,7 @@ use crate::{ expr::*, function::{FuncMeta, Param, Parameters}, stmt::{HirAssignStatement, HirLValue, HirLetStatement, HirPattern, HirStatement}, + types, }, node_interner::{self, DefinitionKind, NodeInterner, StmtId}, token::Attribute, @@ -30,6 +31,11 @@ use self::ast::{Definition, FuncId, Function, LocalId, Program}; pub mod ast; pub mod printer; +struct LambdaContext { + env_ident: Box, + captures: Vec, +} + /// The context struct for the monomorphization pass. /// /// This struct holds the FIFO queue of functions to monomorphize, which is added to @@ -58,6 +64,8 @@ struct Monomorphizer<'interner> { /// Used to reference existing definitions in the HIR interner: &'interner NodeInterner, + lambda_envs_stack: Vec, + next_local_id: u32, next_function_id: u32, } @@ -103,6 +111,7 @@ impl<'interner> Monomorphizer<'interner> { next_local_id: 0, next_function_id: 0, interner, + lambda_envs_stack: Vec::new(), } } @@ -348,7 +357,7 @@ impl<'interner> Monomorphizer<'interner> { } HirExpression::Constructor(constructor) => self.constructor(constructor, expr), - HirExpression::Lambda(lambda) => self.lambda(lambda), + HirExpression::Lambda(lambda) => self.lambda(lambda, expr), HirExpression::MethodCall(_) => { unreachable!("Encountered HirExpression::MethodCall during monomorphization") @@ -541,6 +550,15 @@ impl<'interner> Monomorphizer<'interner> { ast::Expression::Block(definitions) } + /// Find a captured variable in the innermost closure + fn lookup_captured(&mut self, id: node_interner::DefinitionId) -> Option { + let ctx = self.lambda_envs_stack.last()?; + ctx.captures + .iter() + .position(|capture| capture.ident.id == id) + .map(|index| ast::Expression::ExtractTupleField(ctx.env_ident.clone(), index)) + } + /// A local (ie non-global) ident only fn local_ident(&mut self, ident: &HirIdent) -> Option { let definition = self.interner.definition(ident.id); @@ -564,14 +582,25 @@ impl<'interner> Monomorphizer<'interner> { let definition = self.lookup_function(*func_id, expr_id, &typ); let typ = Self::convert_type(&typ); - let ident = ast::Ident { location, mutable, definition, name, typ }; - ast::Expression::Ident(ident) + let ident = ast::Ident { location, mutable, definition, name, typ: typ.clone() }; + let ident_expression = ast::Expression::Ident(ident); + if self.is_function_closure_type(&typ) { + ast::Expression::Tuple(vec![ + ast::Expression::ExtractTupleField( + Box::new(ident_expression.clone()), + 0usize, + ), + ast::Expression::ExtractTupleField(Box::new(ident_expression), 1usize), + ]) + } else { + ident_expression + } } DefinitionKind::Global(expr_id) => self.expr(*expr_id), - DefinitionKind::Local(_) => { + DefinitionKind::Local(_) => self.lookup_captured(ident.id).unwrap_or_else(|| { let ident = self.local_ident(&ident).unwrap(); ast::Expression::Ident(ident) - } + }), DefinitionKind::GenericType(type_variable) => { let value = match &*type_variable.borrow() { TypeBinding::Unbound(_) => { @@ -657,10 +686,11 @@ impl<'interner> Monomorphizer<'interner> { ast::Type::Tuple(fields) } - HirType::Function(args, ret) => { + HirType::Function(args, ret, env) => { let args = vecmap(args, Self::convert_type); let ret = Box::new(Self::convert_type(ret)); - ast::Type::Function(args, ret) + let env = Box::new(Self::convert_type(env)); + ast::Type::Function(args, ret, env) } HirType::MutableReference(element) => { @@ -677,19 +707,44 @@ impl<'interner> Monomorphizer<'interner> { } } + fn is_function_closure(&self, raw_func_id: node_interner::ExprId) -> bool { + let t = Self::convert_type(&self.interner.id_type(raw_func_id)); + if self.is_function_closure_type(&t) { + true + } else if let ast::Type::Tuple(elements) = t { + if elements.len() == 2 { + matches!(elements[1], ast::Type::Function(_, _, _)) + } else { + false + } + } else { + false + } + } + + fn is_function_closure_type(&self, t: &ast::Type) -> bool { + if let ast::Type::Function(_, _, env) = t { + let e = (*env).clone(); + matches!(*e, ast::Type::Tuple(_captures)) + } else { + false + } + } + fn function_call( &mut self, call: HirCallExpression, id: node_interner::ExprId, ) -> ast::Expression { - let func = Box::new(self.expr(call.func)); + let original_func = Box::new(self.expr(call.func)); let mut arguments = vecmap(&call.arguments, |id| self.expr(*id)); let hir_arguments = vecmap(&call.arguments, |id| self.interner.expression(id)); + let func: Box; let return_type = self.interner.id_type(id); let return_type = Self::convert_type(&return_type); let location = call.location; - if let ast::Expression::Ident(ident) = func.as_ref() { + if let ast::Expression::Ident(ident) = original_func.as_ref() { if let Definition::Oracle(name) = &ident.definition { if name.as_str() == "println" { // Oracle calls are required to be wrapped in an unconstrained function @@ -699,12 +754,39 @@ impl<'interner> Monomorphizer<'interner> { } } - self.try_evaluate_call(&func, &return_type).unwrap_or(ast::Expression::Call(ast::Call { - func, - arguments, - return_type, - location, - })) + let mut block_expressions = vec![]; + + let is_closure = self.is_function_closure(call.func); + if is_closure { + let extracted_func: ast::Expression; + let hir_call_func = self.interner.expression(&call.func); + if let HirExpression::Lambda(l) = hir_call_func { + let (setup, closure_variable) = self.lambda_with_setup(l, call.func); + block_expressions.push(setup); + extracted_func = closure_variable; + } else { + extracted_func = *original_func; + } + func = Box::new(ast::Expression::ExtractTupleField( + Box::new(extracted_func.clone()), + 1usize, + )); + let env_argument = ast::Expression::ExtractTupleField(Box::new(extracted_func), 0usize); + arguments.insert(0, env_argument); + } else { + func = original_func.clone(); + }; + + let call = self + .try_evaluate_call(&func, &return_type) + .unwrap_or(ast::Expression::Call(ast::Call { func, arguments, return_type, location })); + + if !block_expressions.is_empty() { + block_expressions.push(call); + ast::Expression::Block(block_expressions) + } else { + call + } } /// Adds a function argument that contains type metadata that is required to tell @@ -914,7 +996,16 @@ impl<'interner> Monomorphizer<'interner> { } } - fn lambda(&mut self, lambda: HirLambda) -> ast::Expression { + fn lambda(&mut self, lambda: HirLambda, expr: node_interner::ExprId) -> ast::Expression { + if lambda.captures.is_empty() { + self.lambda_no_capture(lambda) + } else { + let (setup, closure_variable) = self.lambda_with_setup(lambda, expr); + ast::Expression::Block(vec![setup, closure_variable]) + } + } + + fn lambda_no_capture(&mut self, lambda: HirLambda) -> ast::Expression { let ret_type = Self::convert_type(&lambda.return_type); let lambda_name = "lambda"; let parameter_types = vecmap(&lambda.parameters, |(_, typ)| Self::convert_type(typ)); @@ -935,7 +1026,8 @@ impl<'interner> Monomorphizer<'interner> { let function = ast::Function { id, name, parameters, body, return_type, unconstrained }; self.push_function(id, function); - let typ = ast::Type::Function(parameter_types, Box::new(ret_type)); + let typ = + ast::Type::Function(parameter_types, Box::new(ret_type), Box::new(ast::Type::Unit)); let name = lambda_name.to_owned(); ast::Expression::Ident(ast::Ident { @@ -947,6 +1039,133 @@ impl<'interner> Monomorphizer<'interner> { }) } + fn lambda_with_setup( + &mut self, + lambda: HirLambda, + expr: node_interner::ExprId, + ) -> (ast::Expression, ast::Expression) { + // returns (, ) + // which can be used directly in callsites or transformed + // directly to a single `Expression` + // for other cases by `lambda` which is called by `expr` + // + // it solves the problem of detecting special cases where + // we call something like + // `{let env$.. = ..;}.1({let env$.. = ..;}.0, ..)` + // which was leading to redefinition errors + // + // instead of detecting and extracting + // patterns in the resulting tree, + // which seems more fragile, we directly reuse the return parameters + // of this function in those cases + let ret_type = Self::convert_type(&lambda.return_type); + let lambda_name = "lambda"; + let parameter_types = vecmap(&lambda.parameters, |(_, typ)| Self::convert_type(typ)); + + // Manually convert to Parameters type so we can reuse the self.parameters method + let parameters = Parameters(vecmap(lambda.parameters, |(pattern, typ)| { + Param(pattern, typ, noirc_abi::AbiVisibility::Private) + })); + + let mut converted_parameters = self.parameters(parameters); + + let id = self.next_function_id(); + let name = lambda_name.to_owned(); + let return_type = ret_type.clone(); + + let env_local_id = self.next_local_id(); + let env_name = "env"; + let env_tuple = ast::Expression::Tuple(vecmap(&lambda.captures, |capture| { + match capture.transitive_capture_index { + Some(field_index) => match self.lambda_envs_stack.last() { + Some(lambda_ctx) => ast::Expression::ExtractTupleField( + lambda_ctx.env_ident.clone(), + field_index, + ), + None => unreachable!( + "Expected to find a parent closure environment, but found none" + ), + }, + None => { + let ident = self.local_ident(&capture.ident).unwrap(); + ast::Expression::Ident(ident) + } + } + })); + let expr_type = self.interner.id_type(expr); + let env_typ = if let types::Type::Function(_, _, function_env_type) = expr_type { + Self::convert_type(&function_env_type) + } else { + unreachable!("expected a Function type for a Lambda node") + }; + + let env_let_stmt = ast::Expression::Let(ast::Let { + id: env_local_id, + mutable: false, + name: env_name.to_string(), + expression: Box::new(env_tuple), + }); + + let location = None; // TODO: This should match the location of the lambda expression + let mutable = false; + let definition = Definition::Local(env_local_id); + + let env_ident = ast::Expression::Ident(ast::Ident { + location, + mutable, + definition, + name: env_name.to_string(), + typ: env_typ.clone(), + }); + + self.lambda_envs_stack.push(LambdaContext { + env_ident: Box::new(env_ident.clone()), + captures: lambda.captures, + }); + let body = self.expr(lambda.body); + self.lambda_envs_stack.pop(); + + let lambda_fn_typ: ast::Type = + ast::Type::Function(parameter_types, Box::new(ret_type), Box::new(env_typ.clone())); + let lambda_fn = ast::Expression::Ident(ast::Ident { + definition: Definition::Function(id), + mutable: false, + location: None, // TODO: This should match the location of the lambda expression + name: name.clone(), + typ: lambda_fn_typ.clone(), + }); + + let mut parameters = vec![]; + parameters.push((env_local_id, true, env_name.to_string(), env_typ.clone())); + parameters.append(&mut converted_parameters); + + let unconstrained = false; + let function = ast::Function { id, name, parameters, body, return_type, unconstrained }; + self.push_function(id, function); + + let lambda_value = ast::Expression::Tuple(vec![env_ident, lambda_fn]); + let block_local_id = self.next_local_id(); + let block_ident_name = "closure_variable"; + let block_let_stmt = ast::Expression::Let(ast::Let { + id: block_local_id, + mutable: false, + name: block_ident_name.to_string(), + expression: Box::new(ast::Expression::Block(vec![env_let_stmt, lambda_value])), + }); + + let closure_definition = Definition::Local(block_local_id); + + let closure_ident = ast::Expression::Ident(ast::Ident { + location, + mutable: false, + definition: closure_definition, + name: block_ident_name.to_string(), + typ: ast::Type::Tuple(vec![env_typ, lambda_fn_typ]), + }); + + (block_let_stmt, closure_ident) + } + /// Implements std::unsafe::zeroed by returning an appropriate zeroed /// ast literal or collection node for the given type. Note that for functions /// there is no obvious zeroed value so this should be considered unsafe to use. @@ -984,8 +1203,8 @@ impl<'interner> Monomorphizer<'interner> { ast::Type::Tuple(fields) => { ast::Expression::Tuple(vecmap(fields, |field| self.zeroed_value_of_type(field))) } - ast::Type::Function(parameter_types, ret_type) => { - self.create_zeroed_function(parameter_types, ret_type) + ast::Type::Function(parameter_types, ret_type, env) => { + self.create_zeroed_function(parameter_types, ret_type, env) } ast::Type::Slice(element_type) => { ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { @@ -1012,6 +1231,7 @@ impl<'interner> Monomorphizer<'interner> { &mut self, parameter_types: &[ast::Type], ret_type: &ast::Type, + env_type: &ast::Type, ) -> ast::Expression { let lambda_name = "zeroed_lambda"; @@ -1034,7 +1254,11 @@ impl<'interner> Monomorphizer<'interner> { mutable: false, location: None, name: lambda_name.to_owned(), - typ: ast::Type::Function(parameter_types.to_owned(), Box::new(ret_type.clone())), + typ: ast::Type::Function( + parameter_types.to_owned(), + Box::new(ret_type.clone()), + Box::new(env_type.clone()), + ), }) } } @@ -1072,3 +1296,167 @@ fn undo_instantiation_bindings(bindings: TypeBindings) { *var.borrow_mut() = TypeBinding::Unbound(id); } } + +#[cfg(test)] +mod tests { + use std::collections::HashMap; + + use fm::FileId; + use iter_extended::vecmap; + + use crate::{ + graph::CrateId, + hir::{ + def_map::{ + CrateDefMap, LocalModuleId, ModuleData, ModuleDefId, ModuleId, ModuleOrigin, + }, + resolution::{ + import::PathResolutionError, path_resolver::PathResolver, resolver::Resolver, + }, + }, + hir_def::function::HirFunction, + node_interner::{FuncId, NodeInterner}, + parse_program, + }; + + use super::monomorphize; + + // TODO: refactor into a more general test utility? + // mostly copied from hir / type_check / mod.rs and adapted a bit + fn type_check_src_code(src: &str, func_namespace: Vec) -> (FuncId, NodeInterner) { + let (program, errors) = parse_program(src); + let mut interner = NodeInterner::default(); + + // Using assert_eq here instead of assert(errors.is_empty()) displays + // the whole vec if the assert fails rather than just two booleans + assert_eq!(errors, vec![]); + + let main_id = interner.push_fn(HirFunction::empty()); + interner.push_function_definition("main".into(), main_id); + + let func_ids = vecmap(&func_namespace, |name| { + let id = interner.push_fn(HirFunction::empty()); + interner.push_function_definition(name.into(), id); + id + }); + + let mut path_resolver = TestPathResolver(HashMap::new()); + for (name, id) in func_namespace.into_iter().zip(func_ids.clone()) { + path_resolver.insert_func(name.to_owned(), id); + } + + let mut def_maps: HashMap = HashMap::new(); + let file = FileId::default(); + + let mut modules = arena::Arena::new(); + modules.insert(ModuleData::new(None, ModuleOrigin::File(file), false)); + + def_maps.insert( + CrateId::dummy_id(), + CrateDefMap { + root: path_resolver.local_module_id(), + modules, + krate: CrateId::dummy_id(), + extern_prelude: HashMap::new(), + }, + ); + + let func_meta = vecmap(program.functions, |nf| { + let resolver = Resolver::new(&mut interner, &path_resolver, &def_maps, file); + let (hir_func, func_meta, _resolver_errors) = + resolver.resolve_function(nf, main_id, ModuleId::dummy_id()); + // TODO: not sure why, we do get an error here, + // but otherwise seem to get an ok monomorphization result + // assert_eq!(resolver_errors, vec![]); + (hir_func, func_meta) + }); + + println!("Before update_fn"); + + for ((hir_func, meta), func_id) in func_meta.into_iter().zip(func_ids.clone()) { + interner.update_fn(func_id, hir_func); + interner.push_fn_meta(meta, func_id); + } + + println!("Before type_check_func"); + + // Type check section + let errors = crate::hir::type_check::type_check_func( + &mut interner, + func_ids.first().cloned().unwrap(), + ); + assert_eq!(errors, vec![]); + (func_ids.first().cloned().unwrap(), interner) + } + + // TODO: refactor into a more general test utility? + // TestPathResolver struct and impls copied from hir / type_check / mod.rs + struct TestPathResolver(HashMap); + + impl PathResolver for TestPathResolver { + fn resolve( + &self, + _def_maps: &HashMap, + path: crate::Path, + ) -> Result { + // Not here that foo::bar and hello::foo::bar would fetch the same thing + let name = path.segments.last().unwrap(); + let mod_def = self.0.get(&name.0.contents).cloned(); + mod_def.ok_or_else(move || PathResolutionError::Unresolved(name.clone())) + } + + fn local_module_id(&self) -> LocalModuleId { + // This is not LocalModuleId::dummy since we need to use this to index into a Vec + // later and do not want to push u32::MAX number of elements before we do. + LocalModuleId(arena::Index::from_raw_parts(0, 0)) + } + + fn module_id(&self) -> ModuleId { + ModuleId { krate: CrateId::dummy_id(), local_id: self.local_module_id() } + } + } + + impl TestPathResolver { + fn insert_func(&mut self, name: String, func_id: FuncId) { + self.0.insert(name, func_id.into()); + } + } + + // a helper test method + // TODO: maybe just compare trimmed src/expected + // for easier formatting? + fn check_rewrite(src: &str, expected: &str) { + let (func, interner) = type_check_src_code(src, vec!["main".to_string()]); + let program = monomorphize(func, &interner); + // println!("[{}]", program); + assert!(format!("{}", program) == expected); + } + + #[test] + fn simple_closure_with_no_captured_variables() { + let src = r#" + fn main() -> Field { + let x = 1; + let closure = || x; + closure() + } + "#; + + let expected_rewrite = r#"fn main$f0() -> Field { + let x$0 = 1; + let closure$3 = { + let closure_variable$2 = { + let env$1 = (x$l0); + (env$l1, lambda$f1) + }; + closure_variable$l2 + }; + closure$l3.1(closure$l3.0) +} +fn lambda$f1(mut env$l1: (Field)) -> Field { + env$l1.0 +} +"#; + check_rewrite(src, expected_rewrite); + } +} diff --git a/crates/noirc_frontend/src/node_interner.rs b/crates/noirc_frontend/src/node_interner.rs index f5fea5c1ea7..6b3d2757c14 100644 --- a/crates/noirc_frontend/src/node_interner.rs +++ b/crates/noirc_frontend/src/node_interner.rs @@ -672,7 +672,7 @@ fn get_type_method_key(typ: &Type) -> Option { Type::String(_) => Some(String), Type::Unit => Some(Unit), Type::Tuple(_) => Some(Tuple), - Type::Function(_, _) => Some(Function), + Type::Function(_, _, _) => Some(Function), Type::MutableReference(element) => get_type_method_key(element), // We do not support adding methods to these types From 602168cac35ecb336c6fd23c002bcfd5bea96bfb Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Thu, 3 Aug 2023 08:55:30 +0100 Subject: [PATCH 36/50] chore: clippy fix (#2136) --- crates/noirc_evaluator/src/ssa/acir_gen/mod.rs | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs index 25a0c2ee2e8..f473becd966 100644 --- a/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/mod.rs @@ -736,13 +736,11 @@ impl Context { ) -> Result { match self.convert_value(value_id, dfg) { AcirValue::Var(acir_var, _) => Ok(acir_var), - AcirValue::Array(array) => { - return Err(InternalError::UnExpected { - expected: "a numeric value".to_string(), - found: format!("{array:?}"), - location: self.acir_context.get_location(), - }) - } + AcirValue::Array(array) => Err(InternalError::UnExpected { + expected: "a numeric value".to_string(), + found: format!("{array:?}"), + location: self.acir_context.get_location(), + }), AcirValue::DynamicArray(_) => Err(InternalError::UnExpected { expected: "a numeric value".to_string(), found: "an array".to_string(), From 8e976ea2104153b428d9df6e06ab53051e2832a7 Mon Sep 17 00:00:00 2001 From: guipublic <47281315+guipublic@users.noreply.github.com> Date: Thu, 3 Aug 2023 10:12:07 +0200 Subject: [PATCH 37/50] chore: replace usage of `Directive::Quotient` with brillig opcode (#1766) * Use brillig instead of inverse directive * *wip* * Remove usage of quotient directive in favor of brillig * chore: improve import * chore: remove unnecessary brillig quotient * chore: remove unnecessary comment change * chore: comment change * chore: push clone further up call stack * chore: correct comment on `brillig_quotient` * chore: improve docs for `directive_quotient` * chore: ignore pseudocode entirely --------- Co-authored-by: TomAFrench --- .../brillig/brillig_gen/brillig_directive.rs | 60 +++++++++++++++- .../ssa/acir_gen/acir_ir/generated_acir.rs | 68 +++++++++---------- 2 files changed, 93 insertions(+), 35 deletions(-) diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_directive.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_directive.rs index 219a954a595..93e760f9737 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_directive.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_directive.rs @@ -1,4 +1,6 @@ -use acvm::acir::brillig::{BinaryFieldOp, Opcode as BrilligOpcode, RegisterIndex, Value}; +use acvm::acir::brillig::{ + BinaryFieldOp, BinaryIntOp, Opcode as BrilligOpcode, RegisterIndex, Value, +}; /// Generates brillig bytecode which computes the inverse of its input if not null, and zero else. pub(crate) fn directive_invert() -> Vec { @@ -29,3 +31,59 @@ pub(crate) fn directive_invert() -> Vec { BrilligOpcode::Stop, ] } + +/// Generates brillig bytecode which computes `a / b` and returns the quotient and remainder. +/// It returns `(0,0)` if the predicate is null. +/// +/// +/// This is equivalent to the Noir (psuedo)code +/// +/// ```ignore +/// fn quotient(a: T, b: T, predicate: bool) -> (T,T) { +/// if predicate != 0 { +/// (a/b, a-a/b*b) +/// } else { +/// (0,0) +/// } +/// } +/// ``` +pub(crate) fn directive_quotient(bit_size: u32) -> Vec { + // `a` is (0) (i.e register index 0) + // `b` is (1) + // `predicate` is (2) + vec![ + // If the predicate is zero, we jump to the exit segment + BrilligOpcode::JumpIfNot { condition: RegisterIndex::from(2), location: 6 }, + //q = a/b is set into register (3) + BrilligOpcode::BinaryIntOp { + op: BinaryIntOp::UnsignedDiv, + lhs: RegisterIndex::from(0), + rhs: RegisterIndex::from(1), + destination: RegisterIndex::from(3), + bit_size, + }, + //(1)= q*b + BrilligOpcode::BinaryIntOp { + op: BinaryIntOp::Mul, + lhs: RegisterIndex::from(3), + rhs: RegisterIndex::from(1), + destination: RegisterIndex::from(1), + bit_size, + }, + //(1) = a-q*b + BrilligOpcode::BinaryIntOp { + op: BinaryIntOp::Sub, + lhs: RegisterIndex::from(0), + rhs: RegisterIndex::from(1), + destination: RegisterIndex::from(1), + bit_size, + }, + //(0) = q + BrilligOpcode::Mov { destination: RegisterIndex::from(0), source: RegisterIndex::from(3) }, + BrilligOpcode::Stop, + // Exit segment: we return 0,0 + BrilligOpcode::Const { destination: RegisterIndex::from(0), value: Value::from(0_usize) }, + BrilligOpcode::Const { destination: RegisterIndex::from(1), value: Value::from(0_usize) }, + BrilligOpcode::Stop, + ] +} diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs index 738387fbaab..b425eab42d3 100644 --- a/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs +++ b/crates/noirc_evaluator/src/ssa/acir_gen/acir_ir/generated_acir.rs @@ -11,7 +11,7 @@ use acvm::acir::{ brillig::Opcode as BrilligOpcode, circuit::{ brillig::{Brillig as AcvmBrillig, BrilligInputs, BrilligOutputs}, - directives::{LogInfo, QuotientDirective}, + directives::LogInfo, opcodes::{BlackBoxFuncCall, FunctionInput, Opcode as AcirOpcode}, }, native_types::Witness, @@ -432,13 +432,13 @@ impl GeneratedAcir { } } - let (q_witness, r_witness) = self.quotient_directive( - lhs.clone(), - rhs.clone(), - Some(predicate.clone()), - max_q_bits, - max_rhs_bits, - )?; + let (q_witness, r_witness) = + self.brillig_quotient(lhs.clone(), rhs.clone(), predicate.clone(), max_bit_size + 1); + + // Apply range constraints to injected witness values. + // Constrains `q` to be 0 <= q < 2^{q_max_bits}, etc. + self.range_constraint(q_witness, max_q_bits)?; + self.range_constraint(r_witness, max_rhs_bits)?; // Constrain r < rhs self.bound_constraint_with_offset(&r_witness.into(), rhs, predicate, max_rhs_bits)?; @@ -457,6 +457,32 @@ impl GeneratedAcir { Ok((q_witness, r_witness)) } + /// Adds a brillig opcode which injects witnesses with values `q = a / b` and `r = a % b`. + /// + /// Suitable range constraints for `q` and `r` must be applied externally. + pub(crate) fn brillig_quotient( + &mut self, + lhs: Expression, + rhs: Expression, + predicate: Expression, + max_bit_size: u32, + ) -> (Witness, Witness) { + // Create the witness for the result + let q_witness = self.next_witness_index(); + let r_witness = self.next_witness_index(); + + let quotient_code = brillig_directive::directive_quotient(max_bit_size); + let inputs = vec![ + BrilligInputs::Single(lhs), + BrilligInputs::Single(rhs), + BrilligInputs::Single(predicate.clone()), + ]; + let outputs = vec![BrilligOutputs::Simple(q_witness), BrilligOutputs::Simple(r_witness)]; + self.brillig(Some(predicate), quotient_code, inputs, outputs); + + (q_witness, r_witness) + } + /// Generate constraints that are satisfied iff /// lhs < rhs , when offset is 1, or /// lhs <= rhs, when offset is 0 @@ -692,32 +718,6 @@ impl GeneratedAcir { Ok(()) } - /// Adds a directive which injects witnesses with values `q = a / b` and `r = a % b`. - /// - /// Suitable range constraints are also applied to `q` and `r`. - pub(crate) fn quotient_directive( - &mut self, - a: Expression, - b: Expression, - predicate: Option, - q_max_bits: u32, - r_max_bits: u32, - ) -> Result<(Witness, Witness), RuntimeError> { - let q_witness = self.next_witness_index(); - let r_witness = self.next_witness_index(); - - let directive = - Directive::Quotient(QuotientDirective { a, b, q: q_witness, r: r_witness, predicate }); - self.push_opcode(AcirOpcode::Directive(directive)); - - // Apply range constraints to injected witness values. - // Constrains `q` to be 0 <= q < 2^{q_max_bits}, etc. - self.range_constraint(q_witness, q_max_bits)?; - self.range_constraint(r_witness, r_max_bits)?; - - Ok((q_witness, r_witness)) - } - /// Returns a `Witness` that is constrained to be: /// - `1` if lhs >= rhs /// - `0` otherwise From de072ae832561590d6cf10dab6fca8c55766572b Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Thu, 3 Aug 2023 10:52:27 +0100 Subject: [PATCH 38/50] chore: remove short flags for `--show-ssa` and `--deny-warnings` (#2141) --- crates/noirc_driver/src/lib.rs | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs index 27109af6a2f..9a1cc8a534d 100644 --- a/crates/noirc_driver/src/lib.rs +++ b/crates/noirc_driver/src/lib.rs @@ -25,7 +25,7 @@ pub use program::CompiledProgram; #[derive(Args, Clone, Debug, Default, Serialize, Deserialize)] pub struct CompileOptions { /// Emit debug information for the intermediate SSA IR - #[arg(short, long)] + #[arg(long)] pub show_ssa: bool, #[arg(long)] @@ -36,7 +36,7 @@ pub struct CompileOptions { pub print_acir: bool, /// Treat all warnings as errors - #[arg(short, long)] + #[arg(long)] pub deny_warnings: bool, } From 482e73c763361085fe082a41071da088174ee359 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Thu, 3 Aug 2023 14:50:18 +0100 Subject: [PATCH 39/50] chore: Rebuild ACIR test artifacts (#2147) * chore: update `rebuild.sh` script * chore: refresh test acir artifacts --- .../tests/test_data/1_mul/target/main.json | 2 +- .../tests/test_data/2_div/target/main.json | 2 +- .../tests/test_data/3_add/target/main.json | 2 +- .../tests/test_data/4_sub/target/main.json | 2 +- .../tests/test_data/5_over/target/main.json | 2 +- .../tests/test_data/6/target/main.json | 2 +- .../tests/test_data/6/target/witness.tr | Bin 791 -> 782 bytes .../tests/test_data/6_array/target/main.json | 2 +- .../tests/test_data/7/target/main.json | 2 +- .../tests/test_data/7/target/witness.tr | Bin 672 -> 664 bytes .../test_data/7_function/target/main.json | 2 +- .../test_data/7_function/target/witness.tr | Bin 1282 -> 1293 bytes .../test_data/8_integration/target/main.json | 2 +- .../test_data/8_integration/target/witness.tr | Bin 8074 -> 8060 bytes .../test_data/9_conditional/target/main.json | 2 +- .../test_data/9_conditional/target/witness.tr | Bin 32163 -> 31787 bytes .../test_data/array_dynamic/target/main.json | 2 +- .../test_data/array_dynamic/target/witness.tr | Bin 639 -> 581 bytes .../test_data/array_len/target/main.json | 2 +- .../test_data/array_len/target/witness.tr | Bin 76 -> 181 bytes .../test_data/array_neq/target/main.json | 2 +- .../test_data/array_neq/target/witness.tr | Bin 721 -> 712 bytes .../test_data/array_sort/target/main.json | 2 +- .../tests/test_data/bit_and/target/main.json | 2 +- .../tests/test_data/bit_and/target/witness.tr | Bin 115 -> 110 bytes .../bit_shifts_comptime/target/main.json | 2 +- .../bit_shifts_runtime/target/main.json | 1 + .../bit_shifts_runtime/target/witness.tr | Bin 0 -> 6362 bytes .../brillig_acir_as_brillig/target/main.json | 2 +- .../test_data/brillig_assert/target/main.json | 2 +- .../brillig_blake2s/target/main.json | 2 +- .../brillig_blake2s/target/witness.tr | Bin 672 -> 664 bytes .../test_data/brillig_calls/target/main.json | 2 +- .../brillig_conditional/target/main.json | 2 +- .../brillig_fns_as_values/target/main.json | 2 +- .../brillig_identity_function/target/c.json | 1 - .../target/main.json | 2 +- .../test_data/brillig_keccak/target/main.json | 2 +- .../brillig_keccak/target/witness.tr | Bin 3346 -> 3315 bytes .../test_data/brillig_not/target/main.json | 2 +- .../brillig_references/target/main.json | 2 +- .../test_data/brillig_sha256/target/main.json | 2 +- .../brillig_sha256/target/witness.tr | Bin 656 -> 649 bytes .../closures_mut_ref/target/main.json | 1 + .../closures_mut_ref/target/witness.tr | Bin 0 -> 57 bytes .../test_data/debug_logs/target/main.json | 2 +- .../test_data/debug_logs/target/witness.tr | Bin 51 -> 69 bytes .../ecdsa_secp256k1/target/main.json | 2 +- .../ecdsa_secp256k1/target/witness.tr | Bin 1328 -> 1321 bytes .../test_data/global_consts/target/main.json | 2 +- .../test_data/global_consts/target/witness.tr | Bin 879 -> 997 bytes .../target/main.json} | 2 +- .../target/witness.tr | Bin 0 -> 23 bytes .../higher_order_functions/target/main.json | 2 +- .../higher_order_functions/target/witness.tr | Bin 112 -> 374 bytes .../test_data/if_else_chain/target/main.json | 2 +- .../test_data/if_else_chain/target/witness.tr | Bin 494 -> 517 bytes .../target/main.json} | 2 +- .../inner_outer_cl/target/witness.tr | Bin 0 -> 23 bytes .../test_data/keccak256/target/main.json | 2 +- .../test_data/keccak256/target/witness.tr | Bin 3435 -> 663 bytes .../test_data/main_bool_arg/target/main.json | 2 +- .../test_data/merkle_insert/target/main.json | 2 +- .../tests/test_data/option/target/main.json | 1 + .../tests/test_data/option/target/witness.tr | Bin 0 -> 23 bytes .../poseidon_bn254_hash/target/main.json | 2 +- crates/nargo_cli/tests/test_data/rebuild.sh | 6 +++++- .../test_data/regression/target/main.json | 2 +- .../test_data/regression/target/witness.tr | Bin 1051 -> 1067 bytes .../regression_2099/target/main.json | 1 + .../regression_2099/target/witness.tr | Bin 0 -> 23 bytes .../target/main.json | 2 +- .../test_data/ret_fn_ret_cl/target/main.json | 1 + .../test_data/ret_fn_ret_cl/target/witness.tr | Bin 0 -> 67 bytes .../tests/test_data/schnorr/target/main.json | 2 +- .../tests/test_data/sha256/target/main.json | 2 +- .../tests/test_data/sha256/target/witness.tr | Bin 663 -> 656 bytes .../test_data/sha2_blocks/target/main.json | 2 +- .../test_data/sha2_blocks/target/witness.tr | Bin 301149 -> 301102 bytes .../test_data/sha2_byte/target/main.json | 2 +- .../test_data/sha2_byte/target/witness.tr | Bin 123589 -> 123571 bytes .../signed_division/target/main.json | 2 +- .../test_data/simple_bitwise/target/main.json | 2 +- .../simple_bitwise/target/witness.tr | Bin 191 -> 187 bytes .../simple_comparison/target/main.json | 2 +- .../test_data/simple_print/target/main.json | 2 +- .../test_data/simple_shield/target/main.json | 2 +- .../simple_shift_left_right/target/main.json | 2 +- .../tests/test_data/strings/target/main.json | 2 +- .../tests/test_data/strings/target/witness.tr | Bin 578 -> 678 bytes .../test_data/struct_inputs/target/main.json | 2 +- .../test_data/struct_inputs/target/witness.tr | Bin 397 -> 381 bytes .../tests/test_data/tuples/target/main.json | 2 +- .../test_data/type_aliases/target/main.json | 1 + .../test_data/type_aliases/target/witness.tr | Bin 0 -> 112 bytes .../workspace_default_member/target/main.json | 2 +- .../target/witness.tr | Bin 102 -> 58 bytes 97 files changed, 66 insertions(+), 57 deletions(-) create mode 100644 crates/nargo_cli/tests/test_data/bit_shifts_runtime/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/bit_shifts_runtime/target/witness.tr delete mode 100644 crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json create mode 100644 crates/nargo_cli/tests/test_data/closures_mut_ref/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/closures_mut_ref/target/witness.tr rename crates/nargo_cli/tests/test_data/{1_mul/target/c.json => higher_order_fn_selector/target/main.json} (59%) create mode 100644 crates/nargo_cli/tests/test_data/higher_order_fn_selector/target/witness.tr rename crates/nargo_cli/tests/test_data/{higher_order_functions/target/c.json => inner_outer_cl/target/main.json} (59%) create mode 100644 crates/nargo_cli/tests/test_data/inner_outer_cl/target/witness.tr create mode 100644 crates/nargo_cli/tests/test_data/option/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/option/target/witness.tr create mode 100644 crates/nargo_cli/tests/test_data/regression_2099/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/regression_2099/target/witness.tr create mode 100644 crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/witness.tr create mode 100644 crates/nargo_cli/tests/test_data/type_aliases/target/main.json create mode 100644 crates/nargo_cli/tests/test_data/type_aliases/target/witness.tr diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/main.json b/crates/nargo_cli/tests/test_data/1_mul/target/main.json index f53b31bda01..f7d824175a6 100644 --- a/crates/nargo_cli/tests/test_data/1_mul/target/main.json +++ b/crates/nargo_cli/tests/test_data/1_mul/target/main.json @@ -1 +1 @@ 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of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2Z326CMBTGP2SIyCTLsmw3u+ARWv5ouZuPMjN8/0fYyFo5MHbFV6KJJyG1jf16/vT8NPoG4B2/Fvw8KzvmYr4azUM7D+0Dsb+zDzuqeabdeeDqKkzYTG3tUftyhszFgx0jsZbY0dWss7WoTSj2HsW+QIyB0DiKPVPvCf7RScSa258JX8DLiVqDfu9UJjTZDl8udVeEHH1TRXYO+GuksW6p9lXVHopWl/pTFc3J1KqqT3ujja5N/VWYsmxNZQ7NqTmoRldlq891U56t8BP8NGXI8bOwfuoHYswRsS7M/PmGcYQhbFh+Y8Jmai8OYwe2WKzdYczRXATGneM5ehjH8Adj10hsGD/jNmC8JsYcE+vCzJ9vGMcYwoblNyZspvbiMN7YUYLvDmOO5iIw7gqYo4dxAn8wdo3EhvELbgPGG2LMCbEuzPz5hnGCYWOz/MaEzdReHMZbO6Zi7Q5jjuYiMO4KmKOHcQp/MHaNxIbxK24DxltizCmxLleev0vMITHmlOjXI7gfZn+aHvxeZPos/d2J1+437NXEnfAATI3ROeM8egWqryLtPOhm4F1+X3Fn/BoN4HTNOZXfdtwfcmP7BvHx78jZGwAA","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/2_div/target/main.json b/crates/nargo_cli/tests/test_data/2_div/target/main.json index cea0d39c0f5..5122bd9b948 100644 --- a/crates/nargo_cli/tests/test_data/2_div/target/main.json +++ b/crates/nargo_cli/tests/test_data/2_div/target/main.json @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/3_add/target/main.json b/crates/nargo_cli/tests/test_data/3_add/target/main.json index ad8718ffc05..e1d1586231d 100644 --- a/crates/nargo_cli/tests/test_data/3_add/target/main.json +++ b/crates/nargo_cli/tests/test_data/3_add/target/main.json @@ -1 +1 @@ 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+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/4_sub/target/main.json b/crates/nargo_cli/tests/test_data/4_sub/target/main.json index 0cd34dd035f..62485ea47a0 100644 --- a/crates/nargo_cli/tests/test_data/4_sub/target/main.json +++ b/crates/nargo_cli/tests/test_data/4_sub/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VWbQ6CMAwdgwHR6Bk8wroP2P55FYnj/kcQYmfmNP6QLtEmpCshb++9Ng17xtiB3aNaHo75lNQ8q2us47cxOOYzZrktoEqwtByMCaMKoOEilZ+clcZOgwMH1tmrcloHZ9zoJz9KD0YHmK3XM4Lx7bwgHlgWVLjNgiEyT8kNXY1o8JJYC2xoGvWfNHMr1o5Oo/zk35c8FfKEhlCzIOwrgX9Q0L+H5ppQsyDk1RLO36rxZXkk76j0U3JO+XbJucHM38xEW0ATy+7JfTyygou5VJO6Arg9oxv+Urp7+h49Ladf9rROOMa/tTxuSXEzsPYJAAA=","proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81WbW7DIAzlI0nbTesZqp4AB2jg366yaOn9j7BFheqVpv3RGKlIkTHCz882OHwKIb7EZcj/TyV5AF0Vuk66Tl85VJLfSZp1gyRgWXNybhr6iSz9mD6OwRvnx1OgQD743z5YOwUXhjjGwURydqKzj/acwNR6XpQnC6G/M/bVhwLMJskW1nZQx7y3S3KuhQbbI9hJkBIwjmCztEc+wNnBWrbfAxfBlxPTgV8uzD1gchOmfBkbSOasz4U8FD51Bd8Zi/NCrsX64IvRPMvfizz7xJMaxphbxroy5I8q5u8as2aMuWXk1TGevznGu+Yh2JsUcXJGvhuY55+MWjgTFRovicJPmceqjblWkTYVcLeC7/DXinvLX6Ob5vTOOcVXU355l+MPfrsSyMILAAA=","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/5_over/target/main.json b/crates/nargo_cli/tests/test_data/5_over/target/main.json index a7076380486..520a680c05c 100644 --- a/crates/nargo_cli/tests/test_data/5_over/target/main.json +++ b/crates/nargo_cli/tests/test_data/5_over/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81XUW6DMAx1E9YWqvVvn5N2hJgQSP52laGF+x9hsAY1jfrHM6ollESgZ/v5JTFXIvqgmx3mR6XxK1urtF7fHdL332k024xzTCCuocI24vI60TNGVcQMJ2QhWxeFqNKaBItQ4lrTd10c2siWf0wbRu9M58bes2fn3W/rrY2+80MYw2ACdzby5IKdEvA7yRRUY+JsU5ysgTlXwLrsxZ/ZZqyE+NuK9QbkT9OTTU/4vYiMOY/3mM2rNKonmjgK5ESFn5LHKwkeqFJFkiDqRDjxS+V9wtfo4XB6ZU4VPQoVHSvw8kB3QKv584xR0w4d0OLok+4d0OJUFz7RNxni9onTv4UzUHg1LkdxEQNj7UlIxM2McaEdRNzQvbVWyam0iGugiBugiC9CwkD/tjSE3WyU1b+0P+cFO+aEDwAA","proving_key":null,"verification_key":null} \ No newline at end of file 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a/crates/nargo_cli/tests/test_data/6/target/main.json b/crates/nargo_cli/tests/test_data/6/target/main.json index 9e04a849f70..63cceafe477 100644 --- a/crates/nargo_cli/tests/test_data/6/target/main.json +++ b/crates/nargo_cli/tests/test_data/6/target/main.json @@ -1 +1 @@ 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a/crates/nargo_cli/tests/test_data/7_function/target/main.json +++ b/crates/nargo_cli/tests/test_data/7_function/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"arr1","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"arr2","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"a":[3],"arr1":[4,5,6,7,8,9,10,11,12],"arr2":[13,14,15,16,17,18,19,20,21],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json index 31861cc70c0..ee69d405a9c 100644 --- a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json +++ b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":64},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1VUW6DMAw1hFJYp/3sIjFJSvIz7SpDDfc/whqVqKnVr2JXVOqTEIFIz/Gz4/cJAN9wQXV+6uX9W6yh2IdlL0Gvw1DxcWkgeJAX6Y+kgSI6cIqAWfQsdv5WRYwMJVgAo4/WxnGIaPBPD2HyTls3HT16dN6dBm9M9NaPYQqjDtqaiLMLZl7yqB/nQsKlFcg0Rs1cO8WYc8PAFecEj3cbFtgvMDZ8XLo8765YN6R2CfketAI5AYlDdfwCwWEgVaSdAG8LfM0vlXfLX6ObgbJlTYXdGzfo3hR2f+bo4AnunQL9wNW9O7idWAlKIPbaZrk4xnzaMzZeB6/h3pw593y1eJp79yDj3h/F+u3eKzn7RVBu3gNs271T3gf+Gom6N6emFTljiX/W0KRotA8AAA==","proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":64},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/target/main.json b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/target/main.json new file mode 100644 index 00000000000..be2c752ef28 --- /dev/null +++ b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/target/main.json @@ -0,0 +1 @@ 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b/crates/nargo_cli/tests/test_data/brillig_blake2s/target/main.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json deleted file mode 100644 index 09089ad1fa0..00000000000 --- a/crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json +++ /dev/null @@ -1 +0,0 @@ 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json index f7b5b675d9f..e9ea0637f20 100644 --- a/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json +++ b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json b/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json index fae667945ae..2479c628955 100644 --- a/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json +++ b/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null} \ No newline at end of file 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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":38,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70],"message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"pub_key_x":[71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"pub_key_y":[103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134],"signature":[135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198]},"return_type":null,"return_witnesses":[]},"bytecode":"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\ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":38,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70],"message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"pub_key_x":[71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"pub_key_y":[103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134],"signature":[135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198]},"return_type":null,"return_witnesses":[]},"bytecode":"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a/crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json b/crates/nargo_cli/tests/test_data/inner_outer_cl/target/main.json similarity index 59% rename from crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json rename to crates/nargo_cli/tests/test_data/inner_outer_cl/target/main.json index c1233b8160b..4c3bb072cb3 100644 --- a/crates/nargo_cli/tests/test_data/higher_order_functions/target/c.json +++ b/crates/nargo_cli/tests/test_data/inner_outer_cl/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":[155,194,56,97,194,4,0],"proving_key":null,"verification_key":null} \ No newline at end of file +{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null} \ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/inner_outer_cl/target/witness.tr b/crates/nargo_cli/tests/test_data/inner_outer_cl/target/witness.tr new file mode 100644 index 0000000000000000000000000000000000000000..4e90289d5e1eafa19edb881b1256718356260d8b GIT binary patch literal 23 Zcmb2|=3oE;rvJ$a4GavK_mxsX0suJI1kL~e literal 0 HcmV?d00001 diff --git a/crates/nargo_cli/tests/test_data/keccak256/target/main.json b/crates/nargo_cli/tests/test_data/keccak256/target/main.json index e10a86357e2..daac0e499ec 100644 --- a/crates/nargo_cli/tests/test_data/keccak256/target/main.json +++ b/crates/nargo_cli/tests/test_data/keccak256/target/main.json @@ -1 +1 @@ -{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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\ No newline at end of file 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/sha256/target/main.json b/crates/nargo_cli/tests/test_data/sha256/target/main.json index 5fd48602f5b..5034bb8f814 100644 --- a/crates/nargo_cli/tests/test_data/sha256/target/main.json +++ b/crates/nargo_cli/tests/test_data/sha256/target/main.json @@ -1 +1 @@ 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\ No newline at end of file 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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result256","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result512","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result256":[4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"result512":[36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99],"x":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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\ No newline at end of file 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/simple_shield/target/main.json b/crates/nargo_cli/tests/test_data/simple_shield/target/main.json index 963e1ded6ad..08e53fc8eb8 100644 --- a/crates/nargo_cli/tests/test_data/simple_shield/target/main.json +++ b/crates/nargo_cli/tests/test_data/simple_shield/target/main.json @@ -1 +1 @@ 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\ No newline at end of file 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\ No newline at end of file diff --git a/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json index 96caf4b87da..384946facdb 100644 --- a/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json +++ b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json @@ -1 +1 @@ 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a1c7b8ec6e7..0b2d57ec3b3 100644 --- a/crates/nargo_cli/tests/test_data/strings/target/main.json +++ b/crates/nargo_cli/tests/test_data/strings/target/main.json @@ -1 +1 @@ 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\ No newline at end of file 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-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"struct","fields":[{"name":"foo","type":{"kind":"integer","sign":"unsigned","width":32}},{"name":"bar","type":{"kind":"field"}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"z","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"a","type":{"kind":"struct","fields":[{"name":"bar_struct","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]}},{"name":"baz","type":{"kind":"field"}}]},"visibility":"public"}],"param_witnesses":{"a":[17,18,19,20,21,22,23,24,25],"x":[1],"y":[2,3,4,5,6,7,8],"z":[9,10,11,12,13,14,15,16]},"return_type":{"kind":"field"},"return_witnesses":[19]},"bytecode":"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","proving_key":null,"verification_key":null} 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a/crates/nargo_cli/tests/test_data/type_aliases/target/witness.tr b/crates/nargo_cli/tests/test_data/type_aliases/target/witness.tr new file mode 100644 index 0000000000000000000000000000000000000000..6c2ad03aa2ee3b8095aaed865189ad143c39712b GIT binary patch literal 112 zcmV-$0FVD4iwFP!00002|EI7ySV$1_oyJV8ZZb ze0uZ^{}LxZi{_6-keF+Z6$wv>R#bqcBt=D0xuOzPWzAMBgCSGJCPuAei=(yreT2=? S+8wRnXW$a9~sC*0E!vmF9hf2lCB2 I^MnBa0CZw6-~a#s From 159d048fa1bd6cdb01f2e9dc701f2d0879015002 Mon Sep 17 00:00:00 2001 From: Maxim Vezenov Date: Thu, 3 Aug 2023 15:40:57 +0100 Subject: [PATCH 40/50] chore: Refreshed ACIR artifacts (#2148) * refreshed artifacts * remove main.json files * chore: update artifacts --------- Co-authored-by: Tom French --- .../target/{main.json => 1327_concrete_in_generic.json} | 0 .../tests/test_data/1_mul/target/{main.json => 1_mul.json} | 0 .../tests/test_data/2_div/target/{main.json => 2_div.json} | 0 .../tests/test_data/3_add/target/{main.json => 3_add.json} | 0 .../tests/test_data/4_sub/target/{main.json => 4_sub.json} | 0 .../tests/test_data/5_over/target/{main.json => 5_over.json} | 0 crates/nargo_cli/tests/test_data/6/target/{main.json => 6.json} | 0 .../tests/test_data/6_array/target/{main.json => 6_array.json} | 0 crates/nargo_cli/tests/test_data/7/target/{main.json => 7.json} | 0 .../test_data/7_function/target/{main.json => 7_function.json} | 0 .../8_integration/target/{main.json => 8_integration.json} | 0 .../9_conditional/target/{main.json => 9_conditional.json} | 0 .../target/{main.json => arithmetic_binary_operations.json} | 0 .../array_dynamic/target/{main.json => array_dynamic.json} | 0 .../test_data/array_len/target/{main.json => array_len.json} | 0 .../test_data/array_neq/target/{main.json => array_neq.json} | 0 .../test_data/array_sort/target/{main.json => array_sort.json} | 0 .../tests/test_data/assert/target/{main.json => assert.json} | 0 .../assert_statement/target/{main.json => assert_statement.json} | 0 .../test_data/assign_ex/target/{main.json => assign_ex.json} | 0 .../tests/test_data/bit_and/target/{main.json => bit_and.json} | 0 .../target/{main.json => bit_shifts_comptime.json} | 0 .../target/{main.json => bit_shifts_runtime.json} | 0 .../target/{main.json => blackbox_func_simple_call.json} | 0 .../tests/test_data/bool_not/target/{main.json => bool_not.json} | 0 .../tests/test_data/bool_or/target/{main.json 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.../tests/test_data/strings/target/{main.json => strings.json} | 0 .../tests/test_data/struct/target/{main.json => struct.json} | 0 .../target/{main.json => struct_array_inputs.json} | 0 .../target/{main.json => struct_fields_ordering.json} | 0 .../struct_inputs/target/{main.json => struct_inputs.json} | 0 .../test_data/submodules/target/{main.json => submodules.json} | 0 .../test_data/to_be_bytes/target/{main.json => to_be_bytes.json} | 0 .../tests/test_data/to_bits/target/{main.json => to_bits.json} | 0 .../target/{main.json => to_bytes_integration.json} | 0 .../test_data/to_le_bytes/target/{main.json => to_le_bytes.json} | 0 .../tests/test_data/tuples/target/{main.json => tuples.json} | 0 .../type_aliases/target/{main.json => type_aliases.json} | 0 .../target/{main.json => unconstrained_empty.json} | 0 .../tests/test_data/unit/target/{main.json => unit.json} | 0 .../tests/test_data/vectors/target/{main.json => vectors.json} | 0 .../workspace_default_member/target/{main.json => a.json} | 0 .../nargo_cli/tests/test_data/xor/target/{main.json => xor.json} | 0 137 files changed, 1 deletion(-) rename crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/{main.json => 1327_concrete_in_generic.json} (100%) rename crates/nargo_cli/tests/test_data/1_mul/target/{main.json => 1_mul.json} (100%) rename crates/nargo_cli/tests/test_data/2_div/target/{main.json => 2_div.json} (100%) rename crates/nargo_cli/tests/test_data/3_add/target/{main.json => 3_add.json} (100%) rename crates/nargo_cli/tests/test_data/4_sub/target/{main.json => 4_sub.json} (100%) rename crates/nargo_cli/tests/test_data/5_over/target/{main.json => 5_over.json} (100%) rename crates/nargo_cli/tests/test_data/6/target/{main.json => 6.json} (100%) rename crates/nargo_cli/tests/test_data/6_array/target/{main.json => 6_array.json} (100%) rename crates/nargo_cli/tests/test_data/7/target/{main.json => 7.json} (100%) rename crates/nargo_cli/tests/test_data/7_function/target/{main.json => 7_function.json} (100%) rename crates/nargo_cli/tests/test_data/8_integration/target/{main.json => 8_integration.json} (100%) rename crates/nargo_cli/tests/test_data/9_conditional/target/{main.json => 9_conditional.json} (100%) rename crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/{main.json => arithmetic_binary_operations.json} (100%) rename crates/nargo_cli/tests/test_data/array_dynamic/target/{main.json => array_dynamic.json} (100%) rename crates/nargo_cli/tests/test_data/array_len/target/{main.json => array_len.json} (100%) rename crates/nargo_cli/tests/test_data/array_neq/target/{main.json => array_neq.json} (100%) rename crates/nargo_cli/tests/test_data/array_sort/target/{main.json => array_sort.json} (100%) rename crates/nargo_cli/tests/test_data/assert/target/{main.json => assert.json} (100%) rename crates/nargo_cli/tests/test_data/assert_statement/target/{main.json => assert_statement.json} (100%) rename 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b/crates/nargo_cli/tests/test_data/if_else_chain/target/if_else_chain.json similarity index 100% rename from crates/nargo_cli/tests/test_data/if_else_chain/target/main.json rename to crates/nargo_cli/tests/test_data/if_else_chain/target/if_else_chain.json diff --git a/crates/nargo_cli/tests/test_data/inner_outer_cl/target/main.json b/crates/nargo_cli/tests/test_data/inner_outer_cl/target/inner_outer_cl.json similarity index 100% rename from crates/nargo_cli/tests/test_data/inner_outer_cl/target/main.json rename to crates/nargo_cli/tests/test_data/inner_outer_cl/target/inner_outer_cl.json diff --git a/crates/nargo_cli/tests/test_data/integer_array_indexing/target/main.json b/crates/nargo_cli/tests/test_data/integer_array_indexing/target/integer_array_indexing.json similarity index 100% rename from crates/nargo_cli/tests/test_data/integer_array_indexing/target/main.json rename to crates/nargo_cli/tests/test_data/integer_array_indexing/target/integer_array_indexing.json diff --git a/crates/nargo_cli/tests/test_data/keccak256/target/main.json b/crates/nargo_cli/tests/test_data/keccak256/target/keccak256.json similarity index 100% rename from crates/nargo_cli/tests/test_data/keccak256/target/main.json rename to crates/nargo_cli/tests/test_data/keccak256/target/keccak256.json diff --git a/crates/nargo_cli/tests/test_data/let_stmt/target/main.json b/crates/nargo_cli/tests/test_data/let_stmt/target/let_stmt.json similarity index 100% rename from crates/nargo_cli/tests/test_data/let_stmt/target/main.json rename to crates/nargo_cli/tests/test_data/let_stmt/target/let_stmt.json diff --git a/crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json b/crates/nargo_cli/tests/test_data/main_bool_arg/target/main_bool_arg.json similarity index 100% rename from crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json rename to crates/nargo_cli/tests/test_data/main_bool_arg/target/main_bool_arg.json diff --git a/crates/nargo_cli/tests/test_data/main_return/target/main.json b/crates/nargo_cli/tests/test_data/main_return/target/main_return.json similarity index 100% rename from crates/nargo_cli/tests/test_data/main_return/target/main.json rename to crates/nargo_cli/tests/test_data/main_return/target/main_return.json diff --git a/crates/nargo_cli/tests/test_data/merkle_insert/target/main.json b/crates/nargo_cli/tests/test_data/merkle_insert/target/merkle_insert.json similarity index 100% rename from crates/nargo_cli/tests/test_data/merkle_insert/target/main.json rename to crates/nargo_cli/tests/test_data/merkle_insert/target/merkle_insert.json diff --git a/crates/nargo_cli/tests/test_data/modules/target/main.json b/crates/nargo_cli/tests/test_data/modules/target/modules.json similarity index 100% rename from crates/nargo_cli/tests/test_data/modules/target/main.json rename to crates/nargo_cli/tests/test_data/modules/target/modules.json diff --git a/crates/nargo_cli/tests/test_data/modules_more/target/main.json b/crates/nargo_cli/tests/test_data/modules_more/target/modules_more.json similarity index 100% rename from crates/nargo_cli/tests/test_data/modules_more/target/main.json rename to crates/nargo_cli/tests/test_data/modules_more/target/modules_more.json diff --git a/crates/nargo_cli/tests/test_data/modulus/target/main.json b/crates/nargo_cli/tests/test_data/modulus/target/modulus.json similarity index 100% rename from crates/nargo_cli/tests/test_data/modulus/target/main.json rename to crates/nargo_cli/tests/test_data/modulus/target/modulus.json diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/main.json b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/nested_arrays_from_brillig.json similarity index 100% rename from crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/main.json rename to crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/nested_arrays_from_brillig.json diff --git a/crates/nargo_cli/tests/test_data/numeric_generics/target/main.json b/crates/nargo_cli/tests/test_data/numeric_generics/target/numeric_generics.json similarity index 100% rename from crates/nargo_cli/tests/test_data/numeric_generics/target/main.json rename to crates/nargo_cli/tests/test_data/numeric_generics/target/numeric_generics.json diff --git a/crates/nargo_cli/tests/test_data/option/target/main.json b/crates/nargo_cli/tests/test_data/option/target/option.json similarity index 100% rename from crates/nargo_cli/tests/test_data/option/target/main.json rename to crates/nargo_cli/tests/test_data/option/target/option.json diff --git a/crates/nargo_cli/tests/test_data/pedersen_check/target/main.json b/crates/nargo_cli/tests/test_data/pedersen_check/target/pedersen_check.json similarity index 100% rename from crates/nargo_cli/tests/test_data/pedersen_check/target/main.json rename to crates/nargo_cli/tests/test_data/pedersen_check/target/pedersen_check.json diff --git a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/poseidon_bn254_hash.json similarity index 100% rename from crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json rename to crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/poseidon_bn254_hash.json diff --git a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/poseidonsponge_x5_254.json similarity index 100% rename from crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json rename to crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/poseidonsponge_x5_254.json diff --git a/crates/nargo_cli/tests/test_data/pred_eq/target/main.json b/crates/nargo_cli/tests/test_data/pred_eq/target/pred_eq.json similarity index 100% rename from crates/nargo_cli/tests/test_data/pred_eq/target/main.json rename to crates/nargo_cli/tests/test_data/pred_eq/target/pred_eq.json diff --git a/crates/nargo_cli/tests/test_data/rebuild.sh b/crates/nargo_cli/tests/test_data/rebuild.sh index 8496e87e100..53d18e5cc93 100755 --- a/crates/nargo_cli/tests/test_data/rebuild.sh +++ b/crates/nargo_cli/tests/test_data/rebuild.sh @@ -25,7 +25,6 @@ for dir in ./*; do rm -r ./target/ fi nargo compile && nargo execute witness - mv ./target/*.json ./target/main.json cd .. fi done diff --git a/crates/nargo_cli/tests/test_data/references/target/main.json b/crates/nargo_cli/tests/test_data/references/target/references.json similarity index 100% rename from crates/nargo_cli/tests/test_data/references/target/main.json rename to crates/nargo_cli/tests/test_data/references/target/references.json diff --git a/crates/nargo_cli/tests/test_data/regression/target/main.json b/crates/nargo_cli/tests/test_data/regression/target/regression.json similarity index 100% rename from crates/nargo_cli/tests/test_data/regression/target/main.json rename to crates/nargo_cli/tests/test_data/regression/target/regression.json diff --git a/crates/nargo_cli/tests/test_data/regression_2099/target/main.json b/crates/nargo_cli/tests/test_data/regression_2099/target/regression_2099.json similarity index 100% rename from crates/nargo_cli/tests/test_data/regression_2099/target/main.json rename to crates/nargo_cli/tests/test_data/regression_2099/target/regression_2099.json diff --git a/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/main.json b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/regression_method_cannot_be_found.json similarity index 100% rename from crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/main.json rename to crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/regression_method_cannot_be_found.json diff --git a/crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/main.json b/crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/ret_fn_ret_cl.json similarity index 100% rename from crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/main.json rename to crates/nargo_cli/tests/test_data/ret_fn_ret_cl/target/ret_fn_ret_cl.json diff --git a/crates/nargo_cli/tests/test_data/scalar_mul/target/main.json b/crates/nargo_cli/tests/test_data/scalar_mul/target/scalar_mul.json similarity index 100% rename from crates/nargo_cli/tests/test_data/scalar_mul/target/main.json rename to crates/nargo_cli/tests/test_data/scalar_mul/target/scalar_mul.json diff --git a/crates/nargo_cli/tests/test_data/schnorr/target/main.json b/crates/nargo_cli/tests/test_data/schnorr/target/schnorr.json similarity index 100% rename from crates/nargo_cli/tests/test_data/schnorr/target/main.json rename to crates/nargo_cli/tests/test_data/schnorr/target/schnorr.json diff --git a/crates/nargo_cli/tests/test_data/sha256/target/main.json b/crates/nargo_cli/tests/test_data/sha256/target/sha256.json similarity index 100% rename from crates/nargo_cli/tests/test_data/sha256/target/main.json rename to crates/nargo_cli/tests/test_data/sha256/target/sha256.json diff --git a/crates/nargo_cli/tests/test_data/sha2_blocks/target/main.json b/crates/nargo_cli/tests/test_data/sha2_blocks/target/sha2_blocks.json similarity index 100% rename from crates/nargo_cli/tests/test_data/sha2_blocks/target/main.json rename to crates/nargo_cli/tests/test_data/sha2_blocks/target/sha2_blocks.json diff --git a/crates/nargo_cli/tests/test_data/sha2_byte/target/main.json b/crates/nargo_cli/tests/test_data/sha2_byte/target/sha2_byte.json similarity index 100% rename from crates/nargo_cli/tests/test_data/sha2_byte/target/main.json rename to crates/nargo_cli/tests/test_data/sha2_byte/target/sha2_byte.json diff --git a/crates/nargo_cli/tests/test_data/signed_division/target/main.json b/crates/nargo_cli/tests/test_data/signed_division/target/signed_division.json similarity index 100% rename from crates/nargo_cli/tests/test_data/signed_division/target/main.json rename to crates/nargo_cli/tests/test_data/signed_division/target/signed_division.json diff --git a/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/main.json b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/simple_add_and_ret_arr.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/main.json rename to crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/simple_add_and_ret_arr.json diff --git a/crates/nargo_cli/tests/test_data/simple_array_param/target/main.json b/crates/nargo_cli/tests/test_data/simple_array_param/target/simple_array_param.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_array_param/target/main.json rename to crates/nargo_cli/tests/test_data/simple_array_param/target/simple_array_param.json diff --git a/crates/nargo_cli/tests/test_data/simple_bitwise/target/main.json b/crates/nargo_cli/tests/test_data/simple_bitwise/target/simple_bitwise.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_bitwise/target/main.json rename to crates/nargo_cli/tests/test_data/simple_bitwise/target/simple_bitwise.json diff --git a/crates/nargo_cli/tests/test_data/simple_comparison/target/main.json b/crates/nargo_cli/tests/test_data/simple_comparison/target/simple_comparison.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_comparison/target/main.json rename to crates/nargo_cli/tests/test_data/simple_comparison/target/simple_comparison.json diff --git a/crates/nargo_cli/tests/test_data/simple_mut/target/main.json b/crates/nargo_cli/tests/test_data/simple_mut/target/simple_mut.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_mut/target/main.json rename to crates/nargo_cli/tests/test_data/simple_mut/target/simple_mut.json diff --git a/crates/nargo_cli/tests/test_data/simple_not/target/main.json b/crates/nargo_cli/tests/test_data/simple_not/target/simple_not.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_not/target/main.json rename to crates/nargo_cli/tests/test_data/simple_not/target/simple_not.json diff --git a/crates/nargo_cli/tests/test_data/simple_print/target/main.json b/crates/nargo_cli/tests/test_data/simple_print/target/simple_print.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_print/target/main.json rename to crates/nargo_cli/tests/test_data/simple_print/target/simple_print.json diff --git a/crates/nargo_cli/tests/test_data/simple_program_addition/target/main.json b/crates/nargo_cli/tests/test_data/simple_program_addition/target/simple_program_addition.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_program_addition/target/main.json rename to crates/nargo_cli/tests/test_data/simple_program_addition/target/simple_program_addition.json diff --git a/crates/nargo_cli/tests/test_data/simple_program_no_body/target/main.json b/crates/nargo_cli/tests/test_data/simple_program_no_body/target/simple_program_no_body.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_program_no_body/target/main.json rename to crates/nargo_cli/tests/test_data/simple_program_no_body/target/simple_program_no_body.json diff --git a/crates/nargo_cli/tests/test_data/simple_radix/target/main.json b/crates/nargo_cli/tests/test_data/simple_radix/target/simple_radix.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_radix/target/main.json rename to crates/nargo_cli/tests/test_data/simple_radix/target/simple_radix.json diff --git a/crates/nargo_cli/tests/test_data/simple_range/target/main.json b/crates/nargo_cli/tests/test_data/simple_range/target/simple_range.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_range/target/main.json rename to crates/nargo_cli/tests/test_data/simple_range/target/simple_range.json diff --git a/crates/nargo_cli/tests/test_data/simple_shield/target/main.json b/crates/nargo_cli/tests/test_data/simple_shield/target/simple_shield.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_shield/target/main.json rename to crates/nargo_cli/tests/test_data/simple_shield/target/simple_shield.json diff --git a/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/simple_shift_left_right.json similarity index 100% rename from crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json rename to crates/nargo_cli/tests/test_data/simple_shift_left_right/target/simple_shift_left_right.json diff --git a/crates/nargo_cli/tests/test_data/slices/target/main.json b/crates/nargo_cli/tests/test_data/slices/target/slices.json similarity index 100% rename from crates/nargo_cli/tests/test_data/slices/target/main.json rename to crates/nargo_cli/tests/test_data/slices/target/slices.json diff --git a/crates/nargo_cli/tests/test_data/strings/target/main.json b/crates/nargo_cli/tests/test_data/strings/target/strings.json similarity index 100% rename from crates/nargo_cli/tests/test_data/strings/target/main.json rename to crates/nargo_cli/tests/test_data/strings/target/strings.json diff --git a/crates/nargo_cli/tests/test_data/struct/target/main.json b/crates/nargo_cli/tests/test_data/struct/target/struct.json similarity index 100% rename from crates/nargo_cli/tests/test_data/struct/target/main.json rename to crates/nargo_cli/tests/test_data/struct/target/struct.json diff --git a/crates/nargo_cli/tests/test_data/struct_array_inputs/target/main.json b/crates/nargo_cli/tests/test_data/struct_array_inputs/target/struct_array_inputs.json similarity index 100% rename from crates/nargo_cli/tests/test_data/struct_array_inputs/target/main.json rename to crates/nargo_cli/tests/test_data/struct_array_inputs/target/struct_array_inputs.json diff --git a/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json b/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/struct_fields_ordering.json similarity index 100% rename from crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json rename to crates/nargo_cli/tests/test_data/struct_fields_ordering/target/struct_fields_ordering.json diff --git a/crates/nargo_cli/tests/test_data/struct_inputs/target/main.json b/crates/nargo_cli/tests/test_data/struct_inputs/target/struct_inputs.json similarity index 100% rename from crates/nargo_cli/tests/test_data/struct_inputs/target/main.json rename to crates/nargo_cli/tests/test_data/struct_inputs/target/struct_inputs.json diff --git a/crates/nargo_cli/tests/test_data/submodules/target/main.json b/crates/nargo_cli/tests/test_data/submodules/target/submodules.json similarity index 100% rename from crates/nargo_cli/tests/test_data/submodules/target/main.json rename to crates/nargo_cli/tests/test_data/submodules/target/submodules.json diff --git a/crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json b/crates/nargo_cli/tests/test_data/to_be_bytes/target/to_be_bytes.json similarity index 100% rename from crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json rename to crates/nargo_cli/tests/test_data/to_be_bytes/target/to_be_bytes.json diff --git a/crates/nargo_cli/tests/test_data/to_bits/target/main.json b/crates/nargo_cli/tests/test_data/to_bits/target/to_bits.json similarity index 100% rename from crates/nargo_cli/tests/test_data/to_bits/target/main.json rename to crates/nargo_cli/tests/test_data/to_bits/target/to_bits.json diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json b/crates/nargo_cli/tests/test_data/to_bytes_integration/target/to_bytes_integration.json similarity index 100% rename from crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json rename to crates/nargo_cli/tests/test_data/to_bytes_integration/target/to_bytes_integration.json diff --git a/crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json b/crates/nargo_cli/tests/test_data/to_le_bytes/target/to_le_bytes.json similarity index 100% rename from crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json rename to crates/nargo_cli/tests/test_data/to_le_bytes/target/to_le_bytes.json diff --git a/crates/nargo_cli/tests/test_data/tuples/target/main.json b/crates/nargo_cli/tests/test_data/tuples/target/tuples.json similarity index 100% rename from crates/nargo_cli/tests/test_data/tuples/target/main.json rename to crates/nargo_cli/tests/test_data/tuples/target/tuples.json diff --git a/crates/nargo_cli/tests/test_data/type_aliases/target/main.json b/crates/nargo_cli/tests/test_data/type_aliases/target/type_aliases.json similarity index 100% rename from crates/nargo_cli/tests/test_data/type_aliases/target/main.json rename to crates/nargo_cli/tests/test_data/type_aliases/target/type_aliases.json diff --git a/crates/nargo_cli/tests/test_data/unconstrained_empty/target/main.json b/crates/nargo_cli/tests/test_data/unconstrained_empty/target/unconstrained_empty.json similarity index 100% rename from crates/nargo_cli/tests/test_data/unconstrained_empty/target/main.json rename to crates/nargo_cli/tests/test_data/unconstrained_empty/target/unconstrained_empty.json diff --git a/crates/nargo_cli/tests/test_data/unit/target/main.json b/crates/nargo_cli/tests/test_data/unit/target/unit.json similarity index 100% rename from crates/nargo_cli/tests/test_data/unit/target/main.json rename to crates/nargo_cli/tests/test_data/unit/target/unit.json diff --git a/crates/nargo_cli/tests/test_data/vectors/target/main.json b/crates/nargo_cli/tests/test_data/vectors/target/vectors.json similarity index 100% rename from crates/nargo_cli/tests/test_data/vectors/target/main.json rename to crates/nargo_cli/tests/test_data/vectors/target/vectors.json diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/target/main.json b/crates/nargo_cli/tests/test_data/workspace_default_member/target/a.json similarity index 100% rename from crates/nargo_cli/tests/test_data/workspace_default_member/target/main.json rename to crates/nargo_cli/tests/test_data/workspace_default_member/target/a.json diff --git a/crates/nargo_cli/tests/test_data/xor/target/main.json b/crates/nargo_cli/tests/test_data/xor/target/xor.json similarity index 100% rename from crates/nargo_cli/tests/test_data/xor/target/main.json rename to crates/nargo_cli/tests/test_data/xor/target/xor.json From 6abcb792e510454896d032cea5017bd43ef8cfc3 Mon Sep 17 00:00:00 2001 From: jfecher Date: Thu, 3 Aug 2023 12:12:41 -0500 Subject: [PATCH 41/50] fix: Implement slices of structs (#2150) * Implement slices of structs * Add missed function call * Use element_size in element_size --- .../tests/test_data/slices/src/main.nr | 34 +++++++ crates/noirc_evaluator/src/ssa/ir/dfg.rs | 2 +- .../src/ssa/ir/instruction/call.rs | 96 +++++++++++++------ crates/noirc_evaluator/src/ssa/ir/types.rs | 11 +++ .../src/ssa/ssa_gen/context.rs | 6 +- 5 files changed, 113 insertions(+), 36 deletions(-) diff --git a/crates/nargo_cli/tests/test_data/slices/src/main.nr b/crates/nargo_cli/tests/test_data/slices/src/main.nr index f97078a2143..cda6657b4ff 100644 --- a/crates/nargo_cli/tests/test_data/slices/src/main.nr +++ b/crates/nargo_cli/tests/test_data/slices/src/main.nr @@ -42,5 +42,39 @@ fn main(x : Field, y : pub Field) { assert(removed_elem == 2); assert(remove_slice[3] == 3); assert(remove_slice.len() == 4); + + regression_2083(); } +// Ensure that slices of struct/tuple values work. +fn regression_2083() { + let y = [(1, 2)]; + let y = y.push_back((3, 4)); // [(1, 2), (3, 4)] + let y = y.push_back((5, 6)); // [(1, 2), (3, 4), (5, 6)] + assert(y[2].1 == 6); + + let y = y.push_front((10, 11)); // [(10, 11), (1, 2), (3, 4), (5, 6)] + let y = y.push_front((12, 13)); // [(12, 13), (10, 11), (1, 2), (3, 4), (5, 6)] + + assert(y[1].0 == 10); + + let y = y.insert(1, (55, 56)); // [(12, 13), (55, 56), (10, 11), (1, 2), (3, 4), (5, 6)] + assert(y[0].1 == 13); + assert(y[1].1 == 56); + assert(y[2].0 == 10); + + let (y, x) = y.remove(2); // [(12, 13), (55, 56), (1, 2), (3, 4), (5, 6)] + assert(y[2].0 == 1); + assert(x.0 == 10); + assert(x.1 == 11); + + let (x, y) = y.pop_front(); // [(55, 56), (1, 2), (3, 4), (5, 6)] + assert(y[0].0 == 55); + assert(x.0 == 12); + assert(x.1 == 13); + + let (y, x) = y.pop_back(); // [(55, 56), (1, 2), (3, 4)] + assert(y.len() == 3); + assert(x.0 == 5); + assert(x.1 == 6); +} diff --git a/crates/noirc_evaluator/src/ssa/ir/dfg.rs b/crates/noirc_evaluator/src/ssa/ir/dfg.rs index 29f5156a88c..1dd54499632 100644 --- a/crates/noirc_evaluator/src/ssa/ir/dfg.rs +++ b/crates/noirc_evaluator/src/ssa/ir/dfg.rs @@ -369,7 +369,7 @@ impl DataFlowGraph { /// Otherwise, this returns None. pub(crate) fn get_array_constant(&self, value: ValueId) -> Option<(im::Vector, Type)> { match &self.values[self.resolve(value)] { - // Vectors are shared, so cloning them is cheap + // Arrays are shared, so cloning them is cheap Value::Array { array, typ } => Some((array.clone(), typ.clone())), _ => None, } diff --git a/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs b/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs index 2f0c077a1a7..d5925080870 100644 --- a/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs +++ b/crates/noirc_evaluator/src/ssa/ir/instruction/call.rs @@ -1,4 +1,4 @@ -use std::rc::Rc; +use std::{collections::VecDeque, rc::Rc}; use acvm::{acir::BlackBoxFunc, BlackBoxResolutionError, FieldElement}; use iter_extended::vecmap; @@ -53,22 +53,22 @@ pub(super) fn simplify_call( } Intrinsic::ArrayLen => { let slice = dfg.get_array_constant(arguments[0]); - if let Some((slice, _)) = slice { - SimplifyResult::SimplifiedTo( - dfg.make_constant((slice.len() as u128).into(), Type::field()), - ) + if let Some((slice, typ)) = slice { + let length = FieldElement::from((slice.len() / typ.element_size()) as u128); + SimplifyResult::SimplifiedTo(dfg.make_constant(length, Type::field())) } else if let Some(length) = dfg.try_get_array_length(arguments[0]) { - SimplifyResult::SimplifiedTo( - dfg.make_constant((length as u128).into(), Type::field()), - ) + let length = FieldElement::from(length as u128); + SimplifyResult::SimplifiedTo(dfg.make_constant(length, Type::field())) } else { SimplifyResult::None } } Intrinsic::SlicePushBack => { let slice = dfg.get_array_constant(arguments[0]); - if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { - slice.push_back(elem); + if let Some((mut slice, element_type)) = slice { + for elem in &arguments[1..] { + slice.push_back(*elem); + } let new_slice = dfg.make_array(slice, element_type); SimplifyResult::SimplifiedTo(new_slice) } else { @@ -77,8 +77,10 @@ pub(super) fn simplify_call( } Intrinsic::SlicePushFront => { let slice = dfg.get_array_constant(arguments[0]); - if let (Some((mut slice, element_type)), elem) = (slice, arguments[1]) { - slice.push_front(elem); + if let Some((mut slice, element_type)) = slice { + for elem in arguments[1..].iter().rev() { + slice.push_front(*elem); + } let new_slice = dfg.make_array(slice, element_type); SimplifyResult::SimplifiedTo(new_slice) } else { @@ -87,22 +89,41 @@ pub(super) fn simplify_call( } Intrinsic::SlicePopBack => { let slice = dfg.get_array_constant(arguments[0]); - if let Some((mut slice, element_type)) = slice { - let elem = - slice.pop_back().expect("There are no elements in this slice to be removed"); - let new_slice = dfg.make_array(slice, element_type); - SimplifyResult::SimplifiedToMultiple(vec![new_slice, elem]) + if let Some((mut slice, typ)) = slice { + let element_count = typ.element_size(); + let mut results = VecDeque::with_capacity(element_count + 1); + + // We must pop multiple elements in the case of a slice of tuples + for _ in 0..element_count { + let elem = slice + .pop_back() + .expect("There are no elements in this slice to be removed"); + results.push_front(elem); + } + + let new_slice = dfg.make_array(slice, typ); + results.push_front(new_slice); + + SimplifyResult::SimplifiedToMultiple(results.into()) } else { SimplifyResult::None } } Intrinsic::SlicePopFront => { let slice = dfg.get_array_constant(arguments[0]); - if let Some((mut slice, element_type)) = slice { - let elem = - slice.pop_front().expect("There are no elements in this slice to be removed"); - let new_slice = dfg.make_array(slice, element_type); - SimplifyResult::SimplifiedToMultiple(vec![elem, new_slice]) + if let Some((mut slice, typ)) = slice { + let element_count = typ.element_size(); + + // We must pop multiple elements in the case of a slice of tuples + let mut results = vecmap(0..element_count, |_| { + slice.pop_front().expect("There are no elements in this slice to be removed") + }); + + let new_slice = dfg.make_array(slice, typ); + + // The slice is the last item returned for pop_front + results.push(new_slice); + SimplifyResult::SimplifiedToMultiple(results) } else { SimplifyResult::None } @@ -110,11 +131,16 @@ pub(super) fn simplify_call( Intrinsic::SliceInsert => { let slice = dfg.get_array_constant(arguments[0]); let index = dfg.get_numeric_constant(arguments[1]); - if let (Some((mut slice, element_type)), Some(index), value) = - (slice, index, arguments[2]) - { - slice.insert(index.to_u128() as usize, value); - let new_slice = dfg.make_array(slice, element_type); + if let (Some((mut slice, typ)), Some(index)) = (slice, index) { + let elements = &arguments[2..]; + let mut index = index.to_u128() as usize * elements.len(); + + for elem in &arguments[2..] { + slice.insert(index, *elem); + index += 1; + } + + let new_slice = dfg.make_array(slice, typ); SimplifyResult::SimplifiedTo(new_slice) } else { SimplifyResult::None @@ -123,10 +149,18 @@ pub(super) fn simplify_call( Intrinsic::SliceRemove => { let slice = dfg.get_array_constant(arguments[0]); let index = dfg.get_numeric_constant(arguments[1]); - if let (Some((mut slice, element_type)), Some(index)) = (slice, index) { - let removed_elem = slice.remove(index.to_u128() as usize); - let new_slice = dfg.make_array(slice, element_type); - SimplifyResult::SimplifiedToMultiple(vec![new_slice, removed_elem]) + if let (Some((mut slice, typ)), Some(index)) = (slice, index) { + let element_count = typ.element_size(); + let mut results = Vec::with_capacity(element_count + 1); + let index = index.to_u128() as usize * element_count; + + for _ in 0..element_count { + results.push(slice.remove(index)); + } + + let new_slice = dfg.make_array(slice, typ); + results.insert(0, new_slice); + SimplifyResult::SimplifiedToMultiple(results) } else { SimplifyResult::None } diff --git a/crates/noirc_evaluator/src/ssa/ir/types.rs b/crates/noirc_evaluator/src/ssa/ir/types.rs index 7e37a72ff83..38dd6125121 100644 --- a/crates/noirc_evaluator/src/ssa/ir/types.rs +++ b/crates/noirc_evaluator/src/ssa/ir/types.rs @@ -61,6 +61,17 @@ impl Type { pub(crate) fn field() -> Type { Type::Numeric(NumericType::NativeField) } + + /// Returns the size of the element type for this array/slice. + /// The size of a type is defined as representing how many Fields are needed + /// to represent the type. This is 1 for every primitive type, and is the number of fields + /// for any flattened tuple type. + pub(crate) fn element_size(&self) -> usize { + match self { + Type::Array(elements, _) | Type::Slice(elements) => elements.len(), + other => panic!("element_size: Expected array or slice, found {other}"), + } + } } /// Composite Types are essentially flattened struct or tuple types. diff --git a/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs index c3578e5ee7e..6de804a37b8 100644 --- a/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs +++ b/crates/noirc_evaluator/src/ssa/ssa_gen/context.rs @@ -641,10 +641,8 @@ impl<'a> FunctionContext<'a> { } fn element_size(&self, array: ValueId) -> FieldElement { - match self.builder.type_of_value(array) { - Type::Array(elements, _) | Type::Slice(elements) => (elements.len() as u128).into(), - t => panic!("Uncaught type error: tried to take element size of non-array type {t}"), - } + let size = self.builder.type_of_value(array).element_size(); + FieldElement::from(size as u128) } /// Given an lhs containing only references, create a store instruction to store each value of From 2232a387177f827d14f7c0b7ac1f3e5bb6d957d9 Mon Sep 17 00:00:00 2001 From: Blaine Bublitz Date: Thu, 3 Aug 2023 13:15:33 -0700 Subject: [PATCH 42/50] chore: Refactor `normalize_path` into an API on FileManager (#2156) chore: Refactor normalize_path into an API on FileManager --- crates/fm/src/lib.rs | 69 ++++++++++--------- .../src/hir/def_collector/dc_mod.rs | 2 +- 2 files changed, 38 insertions(+), 33 deletions(-) diff --git a/crates/fm/src/lib.rs b/crates/fm/src/lib.rs index dc78db87684..96ebba8c425 100644 --- a/crates/fm/src/lib.rs +++ b/crates/fm/src/lib.rs @@ -30,7 +30,7 @@ pub struct FileManager { impl FileManager { pub fn new(root: &Path) -> Self { Self { - root: normalize_path(root), + root: root.to_path_buf(), file_map: Default::default(), id_to_path: Default::default(), path_to_id: Default::default(), @@ -44,7 +44,7 @@ impl FileManager { // TODO: The stdlib path should probably be an absolute path rooted in something people would never create file_name.to_path_buf() } else { - normalize_path(&self.root.join(file_name)) + self.resolve_path(file_name) }; // Check that the resolved path already exists in the file map, if it is, we return it. @@ -80,7 +80,7 @@ impl FileManager { self.id_to_path.get(&file_id).unwrap().0.as_path() } - pub fn resolve_path(&mut self, anchor: FileId, mod_name: &str) -> Result { + pub fn find_module(&mut self, anchor: FileId, mod_name: &str) -> Result { let mut candidate_files = Vec::new(); let anchor_path = self.path(anchor).to_path_buf(); @@ -99,37 +99,42 @@ impl FileManager { Err(candidate_files.remove(0).as_os_str().to_str().unwrap().to_owned()) } -} -/// Replacement for `std::fs::canonicalize` that doesn't verify the path exists. -/// -/// Plucked from https://github.com/rust-lang/cargo/blob/fede83ccf973457de319ba6fa0e36ead454d2e20/src/cargo/util/paths.rs#L61 -/// Advice from https://www.reddit.com/r/rust/comments/hkkquy/comment/fwtw53s/ -fn normalize_path(path: &Path) -> PathBuf { - let mut components = path.components().peekable(); - let mut ret = if let Some(c @ Component::Prefix(..)) = components.peek().cloned() { - components.next(); - PathBuf::from(c.as_os_str()) - } else { - PathBuf::new() - }; - - for component in components { - match component { - Component::Prefix(..) => unreachable!(), - Component::RootDir => { - ret.push(component.as_os_str()); - } - Component::CurDir => {} - Component::ParentDir => { - ret.pop(); + /// Resolve a path within the FileManager, removing all `.` and `..` segments. + /// Additionally, relative paths will be resolved against the FileManager's root. + pub fn resolve_path(&self, path: &Path) -> PathBuf { + // This is a replacement for `std::fs::canonicalize` that doesn't verify the path exists. + // + // Plucked from https://github.com/rust-lang/cargo/blob/fede83ccf973457de319ba6fa0e36ead454d2e20/src/cargo/util/paths.rs#L61 + // Advice from https://www.reddit.com/r/rust/comments/hkkquy/comment/fwtw53s/ + let mut components = path.components().peekable(); + let mut ret = match components.peek().cloned() { + Some(c @ Component::Prefix(..)) => { + components.next(); + PathBuf::from(c.as_os_str()) } - Component::Normal(c) => { - ret.push(c); + Some(Component::RootDir) => PathBuf::new(), + // If the first component isn't a RootDir or a Prefix, we know it is relative and needs to be joined to root + _ => self.root.clone(), + }; + + for component in components { + match component { + Component::Prefix(..) => unreachable!(), + Component::RootDir => { + ret.push(component.as_os_str()); + } + Component::CurDir => {} + Component::ParentDir => { + ret.pop(); + } + Component::Normal(c) => { + ret.push(c); + } } } + ret } - ret } /// Takes a path to a noir file. This will panic on paths to directories @@ -165,7 +170,7 @@ mod tests { let dep_file_name = Path::new("foo.nr"); create_dummy_file(&dir, dep_file_name); - fm.resolve_path(file_id, "foo").unwrap(); + fm.find_module(file_id, "foo").unwrap(); } #[test] fn path_resolve_file_module_other_ext() { @@ -212,10 +217,10 @@ mod tests { create_dummy_file(&dir, Path::new(&format!("{}.nr", sub_dir_name))); // First check for the sub_dir.nr file and add it to the FileManager - let sub_dir_file_id = fm.resolve_path(file_id, sub_dir_name).unwrap(); + let sub_dir_file_id = fm.find_module(file_id, sub_dir_name).unwrap(); // Now check for files in it's subdirectory - fm.resolve_path(sub_dir_file_id, "foo").unwrap(); + fm.find_module(sub_dir_file_id, "foo").unwrap(); } /// Tests that two identical files that have different paths are treated as the same file diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs b/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs index 37c017ecb96..9d05539750c 100644 --- a/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs +++ b/crates/noirc_frontend/src/hir/def_collector/dc_mod.rs @@ -259,7 +259,7 @@ impl<'a> ModCollector<'a> { errors: &mut Vec, ) { let child_file_id = - match context.file_manager.resolve_path(self.file_id, &mod_name.0.contents) { + match context.file_manager.find_module(self.file_id, &mod_name.0.contents) { Ok(child_file_id) => child_file_id, Err(_) => { let err = From 4b7d4844327290c0babea88d4f7bc263b6f67dd4 Mon Sep 17 00:00:00 2001 From: Ethan-000 Date: Fri, 4 Aug 2023 11:11:11 +0100 Subject: [PATCH 43/50] chore: Move the long line of `nargo info` to `long_about` (#2151) * . * Update crates/nargo_cli/src/cli/mod.rs --------- Co-authored-by: Tom French <15848336+TomAFrench@users.noreply.github.com> --- crates/nargo_cli/src/cli/info_cmd.rs | 1 + 1 file changed, 1 insertion(+) diff --git a/crates/nargo_cli/src/cli/info_cmd.rs b/crates/nargo_cli/src/cli/info_cmd.rs index 12a70f7b13e..1a834bdd78e 100644 --- a/crates/nargo_cli/src/cli/info_cmd.rs +++ b/crates/nargo_cli/src/cli/info_cmd.rs @@ -12,6 +12,7 @@ use crate::{ use super::NargoConfig; /// Provides detailed information on a circuit +/// /// Current information provided: /// 1. The number of ACIR opcodes /// 2. Counts the final number gates in the circuit used by a backend From fc98b26153f3d0b82778c78aa31056c4f4a1002c Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 12:39:51 +0100 Subject: [PATCH 44/50] chore: bump `clap` to 4.3.19 (#2167) --- Cargo.lock | 8 ++++---- Cargo.toml | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index f513136caf3..e4978b441bf 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -663,9 +663,9 @@ dependencies = [ [[package]] name = "clap" -version = "4.3.16" +version = "4.3.19" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "74bb1b4028935821b2d6b439bba2e970bdcf740832732437ead910c632e30d7d" +checksum = "5fd304a20bff958a57f04c4e96a2e7594cc4490a0e809cbd48bb6437edaa452d" dependencies = [ "clap_builder", "clap_derive", @@ -674,9 +674,9 @@ dependencies = [ [[package]] name = "clap_builder" -version = "4.3.16" +version = "4.3.19" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "5ae467cbb0111869b765e13882a1dbbd6cb52f58203d8b80c44f667d4dd19843" +checksum = "01c6a3f08f1fe5662a35cfe393aec09c4df95f60ee93b7556505260f75eee9e1" dependencies = [ "anstream", "anstyle", diff --git a/Cargo.toml b/Cargo.toml index ca6fbf62299..0b05d783e11 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -38,7 +38,7 @@ noirc_evaluator = { path = "crates/noirc_evaluator" } noirc_frontend = { path = "crates/noirc_frontend" } noir_wasm = { path = "crates/wasm" } cfg-if = "1.0.0" -clap = { version = "4.1.4", features = ["derive"] } +clap = { version = "4.3.19", features = ["derive"] } codespan = { version = "0.11.1", features = ["serialization"] } codespan-lsp = "0.11.1" codespan-reporting = "0.11.1" From efec20a17e9749b4e9096cd320a4fb04a51bbd28 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 12:41:07 +0100 Subject: [PATCH 45/50] chore: Hide the `show_ssa` and `show_brillig` flags (#2171) chore: hide the `show_ssa` and `show_brillig` flags --- crates/noirc_driver/src/lib.rs | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs index 9a1cc8a534d..c624dda2fce 100644 --- a/crates/noirc_driver/src/lib.rs +++ b/crates/noirc_driver/src/lib.rs @@ -25,10 +25,10 @@ pub use program::CompiledProgram; #[derive(Args, Clone, Debug, Default, Serialize, Deserialize)] pub struct CompileOptions { /// Emit debug information for the intermediate SSA IR - #[arg(long)] + #[arg(long, hide = true)] pub show_ssa: bool, - #[arg(long)] + #[arg(long, hide = true)] pub show_brillig: bool, /// Display the ACIR for compiled circuit From ccba78e330463ea9eee00f745e0b489379059bd9 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 12:42:52 +0100 Subject: [PATCH 46/50] chore!: remove unused flags on LSP command (#2170) chore: remove unused flags on LSP command --- crates/nargo_cli/src/cli/lsp_cmd.rs | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/crates/nargo_cli/src/cli/lsp_cmd.rs b/crates/nargo_cli/src/cli/lsp_cmd.rs index afb824c5888..1a1028e2713 100644 --- a/crates/nargo_cli/src/cli/lsp_cmd.rs +++ b/crates/nargo_cli/src/cli/lsp_cmd.rs @@ -5,7 +5,6 @@ use async_lsp::{ }; use clap::Args; use noir_lsp::NargoLspService; -use noirc_driver::CompileOptions; use tokio::io::BufReader; use tower::ServiceBuilder; @@ -13,10 +12,7 @@ use super::NargoConfig; use crate::errors::CliError; #[derive(Debug, Clone, Args)] -pub(crate) struct LspCommand { - #[clap(flatten)] - compile_options: CompileOptions, -} +pub(crate) struct LspCommand; pub(crate) fn run( // Backend is currently unused, but we might want to use it to inform the lsp in the future From e932599b1187fbf426b73c364626d1b17348a55e Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 12:43:59 +0100 Subject: [PATCH 47/50] feat!: Allow specifying new package name with `--name` flag (#2144) * feat: Allow specifying new package name with `--name` flag * chore: update message for option default value * chore: update to match format used in `nargo prove` --- crates/nargo_cli/src/cli/init_cmd.rs | 17 ++++++++++++----- crates/nargo_cli/src/cli/new_cmd.rs | 14 +++++++++----- 2 files changed, 21 insertions(+), 10 deletions(-) diff --git a/crates/nargo_cli/src/cli/init_cmd.rs b/crates/nargo_cli/src/cli/init_cmd.rs index 576690b7fab..a1d4576758a 100644 --- a/crates/nargo_cli/src/cli/init_cmd.rs +++ b/crates/nargo_cli/src/cli/init_cmd.rs @@ -9,7 +9,11 @@ use std::path::PathBuf; /// Create a Noir project in the current directory. #[derive(Debug, Clone, Args)] -pub(crate) struct InitCommand; +pub(crate) struct InitCommand { + /// Name of the package [default: current directory name] + #[clap(long)] + name: Option, +} const EXAMPLE: &str = r#"fn main(x : Field, y : pub Field) { assert(x != y); @@ -27,17 +31,20 @@ fn test_main() { pub(crate) fn run( // Backend is currently unused, but we might want to use it to inform the "new" template in the future _backend: &B, - _args: InitCommand, + args: InitCommand, config: NargoConfig, ) -> Result<(), CliError> { - initialize_project(config.program_dir); + let package_name = args + .name + .unwrap_or_else(|| config.program_dir.file_name().unwrap().to_str().unwrap().to_owned()); + + initialize_project(config.program_dir, &package_name); Ok(()) } /// Initializes a new Noir project in `package_dir`. -pub(crate) fn initialize_project(package_dir: PathBuf) { +pub(crate) fn initialize_project(package_dir: PathBuf, package_name: &str) { // TODO: Should this reject if we have non-Unicode filepaths? - let package_name = package_dir.file_name().expect("Expected a filename").to_string_lossy(); let src_dir = package_dir.join(SRC_DIR); create_named_dir(&src_dir, "src"); diff --git a/crates/nargo_cli/src/cli/new_cmd.rs b/crates/nargo_cli/src/cli/new_cmd.rs index 66c29eb3292..a792e752a51 100644 --- a/crates/nargo_cli/src/cli/new_cmd.rs +++ b/crates/nargo_cli/src/cli/new_cmd.rs @@ -8,10 +8,12 @@ use std::path::PathBuf; /// Create a Noir project in a new directory. #[derive(Debug, Clone, Args)] pub(crate) struct NewCommand { - /// Name of the package - package_name: String, /// The path to save the new project - path: Option, + path: PathBuf, + + /// Name of the package [default: package directory name] + #[clap(long)] + name: Option, } pub(crate) fn run( @@ -20,12 +22,14 @@ pub(crate) fn run( args: NewCommand, config: NargoConfig, ) -> Result<(), CliError> { - let package_dir = config.program_dir.join(args.package_name); + let package_dir = config.program_dir.join(&args.path); if package_dir.exists() { return Err(CliError::DestinationAlreadyExists(package_dir)); } - initialize_project(package_dir); + let package_name = + args.name.unwrap_or_else(|| args.path.file_name().unwrap().to_str().unwrap().to_owned()); + initialize_project(package_dir, &package_name); Ok(()) } From 1e79f4a16ef9713913afbe0af47535dd5fd87827 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 12:44:03 +0100 Subject: [PATCH 48/50] chore: clippy fix (#2174) --- .../noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs index ded6be71bd5..5e66519e4ad 100644 --- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs +++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs @@ -776,7 +776,7 @@ impl<'block> BrilligBlock<'block> { fn convert_ssa_value(&mut self, value_id: ValueId, dfg: &DataFlowGraph) -> RegisterOrMemory { let value = &dfg[value_id]; - let variable = match value { + match value { Value::Param { .. } | Value::Instruction { .. } => { // All block parameters and instruction results should have already been // converted to registers so we fetch from the cache. @@ -843,8 +843,7 @@ impl<'block> BrilligBlock<'block> { _ => { todo!("ICE: Cannot convert value {value:?}") } - }; - variable + } } /// Converts an SSA `ValueId` into a `RegisterIndex`. Initializes if necessary. From a6549a27628d00e378a9a0636977729caf8d0c8d Mon Sep 17 00:00:00 2001 From: Blaine Bublitz Date: Fri, 4 Aug 2023 05:28:15 -0700 Subject: [PATCH 49/50] chore: Replace `resolve_path` function with a trait that impls normalize (#2157) * chore: Replace `resolve_path` function with a trait that impls normalize * chore: add smoketests for path normalization * chore: remove unnecessary raw string * chore: remove test for windows prefixes * chore: cspell --------- Co-authored-by: Tom French --- Cargo.lock | 1 + crates/fm/Cargo.toml | 1 + crates/fm/src/lib.rs | 107 ++++++++++++++++++++++++++++++------------- cspell.json | 3 +- 4 files changed, 78 insertions(+), 34 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index e4978b441bf..c4235b2c913 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1237,6 +1237,7 @@ version = "0.9.0" dependencies = [ "cfg-if", "codespan-reporting", + "iter-extended", "rust-embed", "serde", "tempfile", diff --git a/crates/fm/Cargo.toml b/crates/fm/Cargo.toml index 48f1932f9d6..2fc7eac6d8f 100644 --- a/crates/fm/Cargo.toml +++ b/crates/fm/Cargo.toml @@ -17,3 +17,4 @@ wasm-bindgen.workspace = true [dev-dependencies] tempfile = "3.2.0" +iter-extended.workspace = true diff --git a/crates/fm/src/lib.rs b/crates/fm/src/lib.rs index 96ebba8c425..4c2ce39dd40 100644 --- a/crates/fm/src/lib.rs +++ b/crates/fm/src/lib.rs @@ -30,7 +30,7 @@ pub struct FileManager { impl FileManager { pub fn new(root: &Path) -> Self { Self { - root: root.to_path_buf(), + root: root.normalize(), file_map: Default::default(), id_to_path: Default::default(), path_to_id: Default::default(), @@ -44,7 +44,7 @@ impl FileManager { // TODO: The stdlib path should probably be an absolute path rooted in something people would never create file_name.to_path_buf() } else { - self.resolve_path(file_name) + self.root.join(file_name).normalize() }; // Check that the resolved path already exists in the file map, if it is, we return it. @@ -99,41 +99,82 @@ impl FileManager { Err(candidate_files.remove(0).as_os_str().to_str().unwrap().to_owned()) } +} - /// Resolve a path within the FileManager, removing all `.` and `..` segments. - /// Additionally, relative paths will be resolved against the FileManager's root. - pub fn resolve_path(&self, path: &Path) -> PathBuf { - // This is a replacement for `std::fs::canonicalize` that doesn't verify the path exists. - // - // Plucked from https://github.com/rust-lang/cargo/blob/fede83ccf973457de319ba6fa0e36ead454d2e20/src/cargo/util/paths.rs#L61 - // Advice from https://www.reddit.com/r/rust/comments/hkkquy/comment/fwtw53s/ - let mut components = path.components().peekable(); - let mut ret = match components.peek().cloned() { - Some(c @ Component::Prefix(..)) => { - components.next(); - PathBuf::from(c.as_os_str()) - } - Some(Component::RootDir) => PathBuf::new(), - // If the first component isn't a RootDir or a Prefix, we know it is relative and needs to be joined to root - _ => self.root.clone(), - }; +pub trait NormalizePath { + /// Replacement for `std::fs::canonicalize` that doesn't verify the path exists. + /// + /// Plucked from https://github.com/rust-lang/cargo/blob/fede83ccf973457de319ba6fa0e36ead454d2e20/src/cargo/util/paths.rs#L61 + /// Advice from https://www.reddit.com/r/rust/comments/hkkquy/comment/fwtw53s/ + fn normalize(&self) -> PathBuf; +} + +impl NormalizePath for PathBuf { + fn normalize(&self) -> PathBuf { + let components = self.components(); + resolve_components(components) + } +} + +impl NormalizePath for &Path { + fn normalize(&self) -> PathBuf { + let components = self.components(); + resolve_components(components) + } +} - for component in components { - match component { - Component::Prefix(..) => unreachable!(), - Component::RootDir => { - ret.push(component.as_os_str()); - } - Component::CurDir => {} - Component::ParentDir => { - ret.pop(); - } - Component::Normal(c) => { - ret.push(c); - } +fn resolve_components<'a>(components: impl Iterator>) -> PathBuf { + let mut components = components.peekable(); + + // Preserve path prefix if one exists. + let mut normalized_path = if let Some(c @ Component::Prefix(..)) = components.peek().cloned() { + components.next(); + PathBuf::from(c.as_os_str()) + } else { + PathBuf::new() + }; + + for component in components { + match component { + Component::Prefix(..) => unreachable!("Path cannot contain multiple prefixes"), + Component::RootDir => { + normalized_path.push(component.as_os_str()); + } + Component::CurDir => {} + Component::ParentDir => { + normalized_path.pop(); + } + Component::Normal(c) => { + normalized_path.push(c); } } - ret + } + + normalized_path +} + +#[cfg(test)] +mod path_normalization { + use iter_extended::vecmap; + use std::path::PathBuf; + + use crate::NormalizePath; + + #[test] + fn normalizes_paths_correctly() { + // Note that tests are run on unix so prefix handling can't be tested (as these only exist on Windows) + let test_cases = vecmap( + [ + ("/", "/"), // Handles root + ("/foo/bar/../baz/../bar", "/foo/bar"), // Handles backtracking + ("/././././././././baz", "/baz"), // Removes no-ops + ], + |(unnormalized, normalized)| (PathBuf::from(unnormalized), PathBuf::from(normalized)), + ); + + for (path, expected_result) in test_cases { + assert_eq!(path.normalize(), expected_result); + } } } diff --git a/cspell.json b/cspell.json index 64413c3faf3..8da1d65fb56 100644 --- a/cspell.json +++ b/cspell.json @@ -63,6 +63,7 @@ "typevars", "udiv", "uninstantiated", + "unnormalized", "urem", "vecmap", "direnv", @@ -99,4 +100,4 @@ "termcolor", "thiserror" ] -} \ No newline at end of file +} From 186375b1c492ca4d84690860f0fa6a8d1a25bea2 Mon Sep 17 00:00:00 2001 From: Tom French <15848336+TomAFrench@users.noreply.github.com> Date: Fri, 4 Aug 2023 14:20:43 +0100 Subject: [PATCH 50/50] chore: update stale comment on `create_circuit` (#2173) --- crates/noirc_evaluator/src/ssa.rs | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/crates/noirc_evaluator/src/ssa.rs b/crates/noirc_evaluator/src/ssa.rs index c57bb330b09..2b7be935619 100644 --- a/crates/noirc_evaluator/src/ssa.rs +++ b/crates/noirc_evaluator/src/ssa.rs @@ -65,10 +65,9 @@ pub(crate) fn optimize_into_acir( ssa.into_acir(brillig, abi_distinctness) } -/// Compiles the Program into ACIR and applies optimizations to the arithmetic gates -/// This is analogous to `ssa:create_circuit` and this method is called when one wants -/// to use the new ssa module to process Noir code. -// TODO: This no longer needs to return a result, but it is kept to match the signature of `create_circuit` +/// Compiles the [`Program`] into [`ACIR`][acvm::acir::circuit::Circuit]. +/// +/// The output ACIR is is backend-agnostic and so must go through a transformation pass before usage in proof generation. pub fn create_circuit( program: Program, enable_ssa_logging: bool,