fix: instance order when using processed params (#829)

.github/workflows/rust.yml

@@ -260,6 +260,8 @@ jobs:
         run: cargo nextest run --release --verbose tests::mock_hashed_input_::t  --test-threads 32
       - name: hashed params
         run: cargo nextest run --release --verbose tests::mock_hashed_params_::t  --test-threads 32
+      - name: hashed params public inputs
+        run: cargo nextest run --release --verbose tests::mock_hashed_params_public_inputs_::t  --test-threads 32
       - name: hashed outputs
         run: cargo nextest run --release --verbose tests::mock_hashed_output_::t  --test-threads 32
       - name: hashed inputs + params + outputs

benches/relu.rs

@@ -2,6 +2,7 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::table::Range;
 use ezkl::circuit::{ops::lookup::LookupOp, BaseConfig as Config, CheckMode};
+use ezkl::fieldutils::IntegerRep;
 use ezkl::pfsys::create_proof_circuit;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
@@ -84,7 +85,7 @@ fn runrelu(c: &mut Criterion) {
         };
 
         let input: Tensor<Value<Fr>> =
-            Tensor::<i32>::from((0..len).map(|_| rng.gen_range(0..10))).into();
+            Tensor::<IntegerRep>::from((0..len).map(|_| rng.gen_range(0..10))).into();
 
         let circuit = NLCircuit {
             input: ValTensor::from(input.clone()),

examples/conv2d_mnist/main.rs

@@ -2,8 +2,7 @@ use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::{
     ops::lookup::LookupOp, ops::poly::PolyOp, BaseConfig as PolyConfig, CheckMode,
 };
-use ezkl::fieldutils;
-use ezkl::fieldutils::i32_to_felt;
+use ezkl::fieldutils::{self, integer_rep_to_felt, IntegerRep};
 use ezkl::tensor::*;
 use halo2_proofs::dev::MockProver;
 use halo2_proofs::poly::commitment::Params;
@@ -42,8 +41,8 @@ const NUM_INNER_COLS: usize = 1;
 struct Config<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened //not supported yet in rust stable
     const CLASSES: usize,
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
     // Convolution
     const KERNEL_HEIGHT: usize,
     const KERNEL_WIDTH: usize,
@@ -66,8 +65,8 @@ struct Config<
 struct MyCircuit<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened
     const CLASSES: usize,
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
     // Convolution
     const KERNEL_HEIGHT: usize,
     const KERNEL_WIDTH: usize,
@@ -90,8 +89,8 @@ struct MyCircuit<
 impl<
         const LEN: usize,
         const CLASSES: usize,
-        const LOOKUP_MIN: i64,
-        const LOOKUP_MAX: i64,
+        const LOOKUP_MIN: IntegerRep,
+        const LOOKUP_MAX: IntegerRep,
         // Convolution
         const KERNEL_HEIGHT: usize,
         const KERNEL_WIDTH: usize,
@@ -316,7 +315,11 @@ pub fn runconv() {
         .test_set_length(10_000)
         .finalize();
 
-    let mut train_data = Tensor::from(trn_img.iter().map(|x| i32_to_felt::<F>(*x as i32 / 16)));
+    let mut train_data = Tensor::from(
+        trn_img
+            .iter()
+            .map(|x| integer_rep_to_felt::<F>(*x as IntegerRep / 16)),
+    );
     train_data.reshape(&[50_000, 28, 28]).unwrap();
 
     let mut train_labels = Tensor::from(trn_lbl.iter().map(|x| *x as f32));
@@ -344,8 +347,8 @@ pub fn runconv() {
             .map(|fl| {
                 let dx = fl * 32_f32;
                 let rounded = dx.round();
-                let integral: i32 = unsafe { rounded.to_int_unchecked() };
-                fieldutils::i32_to_felt(integral)
+                let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+                fieldutils::integer_rep_to_felt(integral)
             }),
     );
 
@@ -356,16 +359,17 @@ pub fn runconv() {
 
     let l0_kernels = l0_kernels.try_into().unwrap();
 
-    let mut l0_bias = Tensor::<F>::from((0..OUT_CHANNELS).map(|_| fieldutils::i32_to_felt(0)));
+    let mut l0_bias =
+        Tensor::<F>::from((0..OUT_CHANNELS).map(|_| fieldutils::integer_rep_to_felt(0)));
     l0_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
     let l0_bias = l0_bias.try_into().unwrap();
 
     let mut l2_biases = Tensor::<F>::from(myparams.biases.into_iter().map(|fl| {
         let dx = fl * 32_f32;
         let rounded = dx.round();
-        let integral: i32 = unsafe { rounded.to_int_unchecked() };
-        fieldutils::i32_to_felt(integral)
+        let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+        fieldutils::integer_rep_to_felt(integral)
     }));
     l2_biases.set_visibility(&ezkl::graph::Visibility::Private);
     l2_biases.reshape(&[l2_biases.len(), 1]).unwrap();
@@ -375,8 +379,8 @@ pub fn runconv() {
     let mut l2_weights = Tensor::<F>::from(myparams.weights.into_iter().flatten().map(|fl| {
         let dx = fl * 32_f32;
         let rounded = dx.round();
-        let integral: i32 = unsafe { rounded.to_int_unchecked() };
-        fieldutils::i32_to_felt(integral)
+        let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+        fieldutils::integer_rep_to_felt(integral)
     }));
     l2_weights.set_visibility(&ezkl::graph::Visibility::Private);
     l2_weights.reshape(&[CLASSES, LEN]).unwrap();
@@ -402,13 +406,13 @@ pub fn runconv() {
         l2_params: [l2_weights, l2_biases],
     };
 
-    let public_input: Tensor<i32> = vec![
-        -25124i32, -19304, -16668, -4399, -6209, -4548, -2317, -8349, -6117, -23461,
+    let public_input: Tensor<IntegerRep> = vec![
+        -25124, -19304, -16668, -4399, -6209, -4548, -2317, -8349, -6117, -23461,
     ]
     .into_iter()
     .into();
 
-    let pi_inner: Tensor<F> = public_input.map(i32_to_felt::<F>);
+    let pi_inner: Tensor<F> = public_input.map(integer_rep_to_felt::<F>);
 
     println!("MOCK PROVING");
     let now = Instant::now();

examples/mlp_4d_einsum.rs

@@ -2,7 +2,7 @@ use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::{
     ops::lookup::LookupOp, ops::poly::PolyOp, BaseConfig as PolyConfig, CheckMode,
 };
-use ezkl::fieldutils::i32_to_felt;
+use ezkl::fieldutils::{integer_rep_to_felt, IntegerRep};
 use ezkl::tensor::*;
 use halo2_proofs::dev::MockProver;
 use halo2_proofs::{
@@ -23,8 +23,8 @@ struct MyConfig {
 #[derive(Clone)]
 struct MyCircuit<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
 > {
     // Given the stateless MyConfig type information, a DNN trace is determined by its input and the parameters of its layers.
     // Computing the trace still requires a forward pass. The intermediate activations are stored only by the layouter.
@@ -34,7 +34,7 @@ struct MyCircuit<
     _marker: PhantomData<F>,
 }
 
-impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
+impl<const LEN: usize, const LOOKUP_MIN: IntegerRep, const LOOKUP_MAX: IntegerRep> Circuit<F>
     for MyCircuit<LEN, LOOKUP_MIN, LOOKUP_MAX>
 {
     type Config = MyConfig;
@@ -215,33 +215,33 @@ pub fn runmlp() {
     #[cfg(not(target_arch = "wasm32"))]
     env_logger::init();
     // parameters
-    let mut l0_kernel: Tensor<F> = Tensor::<i32>::new(
+    let mut l0_kernel: Tensor<F> = Tensor::<IntegerRep>::new(
         Some(&[10, 0, 0, -1, 0, 10, 1, 0, 0, 1, 10, 0, 1, 0, 0, 10]),
         &[4, 4],
     )
     .unwrap()
-    .map(i32_to_felt);
+    .map(integer_rep_to_felt);
     l0_kernel.set_visibility(&ezkl::graph::Visibility::Private);
 
-    let mut l0_bias: Tensor<F> = Tensor::<i32>::new(Some(&[0, 0, 0, 1]), &[4, 1])
+    let mut l0_bias: Tensor<F> = Tensor::<IntegerRep>::new(Some(&[0, 0, 0, 1]), &[4, 1])
         .unwrap()
-        .map(i32_to_felt);
+        .map(integer_rep_to_felt);
     l0_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
-    let mut l2_kernel: Tensor<F> = Tensor::<i32>::new(
+    let mut l2_kernel: Tensor<F> = Tensor::<IntegerRep>::new(
         Some(&[0, 3, 10, -1, 0, 10, 1, 0, 0, 1, 0, 12, 1, -2, 32, 0]),
         &[4, 4],
     )
     .unwrap()
-    .map(i32_to_felt);
+    .map(integer_rep_to_felt);
     l2_kernel.set_visibility(&ezkl::graph::Visibility::Private);
     // input data, with 1 padding to allow for bias
-    let input: Tensor<Value<F>> = Tensor::<i32>::new(Some(&[-30, -21, 11, 40]), &[4, 1])
+    let input: Tensor<Value<F>> = Tensor::<IntegerRep>::new(Some(&[-30, -21, 11, 40]), &[4, 1])
         .unwrap()
         .into();
-    let mut l2_bias: Tensor<F> = Tensor::<i32>::new(Some(&[0, 0, 0, 1]), &[4, 1])
+    let mut l2_bias: Tensor<F> = Tensor::<IntegerRep>::new(Some(&[0, 0, 0, 1]), &[4, 1])
         .unwrap()
-        .map(i32_to_felt);
+        .map(integer_rep_to_felt);
     l2_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
     let circuit = MyCircuit::<4, -8192, 8192> {
@@ -251,12 +251,12 @@ pub fn runmlp() {
         _marker: PhantomData,
     };
 
-    let public_input: Vec<i32> = unsafe {
+    let public_input: Vec<IntegerRep> = unsafe {
         vec![
-            (531f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (103f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (4469f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (2849f32 / 128f32).to_int_unchecked::<i32>(),
+            (531f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (103f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (4469f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (2849f32 / 128f32).to_int_unchecked::<IntegerRep>(),
         ]
     };
 
@@ -265,7 +265,10 @@ pub fn runmlp() {
     let prover = MockProver::run(
         K as u32,
         &circuit,
-        vec![public_input.iter().map(|x| i32_to_felt::<F>(*x)).collect()],
+        vec![public_input
+            .iter()
+            .map(|x| integer_rep_to_felt::<F>(*x))
+            .collect()],
     )
     .unwrap();
     prover.assert_satisfied();

src/circuit/ops/chip.rs

@@ -22,7 +22,7 @@ use crate::{
         table::{Range, RangeCheck, Table},
         utils,
     },
-    tensor::{IntoI64, Tensor, TensorType, ValTensor, VarTensor},
+    tensor::{Tensor, TensorType, ValTensor, VarTensor},
 };
 use std::{collections::BTreeMap, marker::PhantomData};
 
@@ -327,7 +327,7 @@ pub struct BaseConfig<F: PrimeField + TensorType + PartialOrd> {
     _marker: PhantomData<F>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseConfig<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> BaseConfig<F> {
     /// Returns a new [BaseConfig] with no inputs, no selectors, and no tables.
     pub fn dummy(col_size: usize, num_inner_cols: usize) -> Self {
         Self {

src/circuit/ops/errors.rs

@@ -1,6 +1,6 @@
 use std::convert::Infallible;
 
-use crate::tensor::TensorError;
+use crate::{fieldutils::IntegerRep, tensor::TensorError};
 use halo2_proofs::plonk::Error as PlonkError;
 use thiserror::Error;
 
@@ -57,7 +57,7 @@ pub enum CircuitError {
     InvalidConversion(#[from] Infallible),
     /// Invalid min/max lookup range
     #[error("invalid min/max lookup range: min: {0}, max: {1}")]
-    InvalidMinMaxRange(i64, i64),
+    InvalidMinMaxRange(IntegerRep, IntegerRep),
     /// Missing product in einsum
     #[error("missing product in einsum")]
     MissingEinsumProduct,
@@ -81,7 +81,7 @@ pub enum CircuitError {
     MissingSelectors(String),
     /// Table lookup error
     #[error("value ({0}) out of range: ({1}, {2})")]
-    TableOOR(i64, i64, i64),
+    TableOOR(IntegerRep, IntegerRep, IntegerRep),
     /// Loookup not configured
     #[error("lookup not configured: {0}")]
     LookupNotConfigured(String),

src/circuit/ops/hybrid.rs

@@ -1,7 +1,7 @@
 use super::*;
 use crate::{
     circuit::{layouts, utils, Tolerance},
-    fieldutils::i64_to_felt,
+    fieldutils::integer_rep_to_felt,
     graph::multiplier_to_scale,
     tensor::{self, Tensor, TensorType, ValTensor},
 };
@@ -71,7 +71,7 @@ pub enum HybridOp {
     },
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F> for HybridOp {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash > Op<F> for HybridOp {
     ///
     fn requires_homogenous_input_scales(&self) -> Vec<usize> {
         match self {
@@ -184,8 +184,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
                         config,
                         region,
                         values[..].try_into()?,
-                        i64_to_felt(input_scale.0 as i64),
-                        i64_to_felt(output_scale.0 as i64),
+                        integer_rep_to_felt(input_scale.0 as i128),
+                        integer_rep_to_felt(output_scale.0 as i128),
                     )?
                 } else {
                     layouts::nonlinearity(
@@ -209,7 +209,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
                         config,
                         region,
                         values[..].try_into()?,
-                        i64_to_felt(denom.0 as i64),
+                        integer_rep_to_felt(denom.0 as i128),
                     )?
                 } else {
                     layouts::nonlinearity(