[PIR]Store Python data in Operation (#62750)

* store data in operation * delete lod * rename persistable * fix append_backward * fix lod * remove pir test for data feeder * fix amp * support return none * amend * perfect set property * fix descontruct bug
PaddlePaddle · Mar 26, 2024 · c3f5747 · c3f5747
1 parent 66a4faa
commit c3f5747
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Showing 19 changed files with 163 additions and 49 deletions.
diff --git a/paddle/fluid/pybind/pir.cc b/paddle/fluid/pybind/pir.cc
@@ -823,6 +823,40 @@ pir::Value apply(Value self, py::object func) {
   return out;
 }
 
+#define DEF_VALUE_BOOL_PROPERTY(name)                                         \
+  def_property(                                                               \
+      name,                                                                   \
+      [](Value self) {                                                        \
+        auto bool_data = self.attribute<BoolAttribute>(name);                 \
+        return !bool_data || bool_data.data();                                \
+      },                                                                      \
+      [](Value self, bool bool_data) {                                        \
+        self.set_attribute(                                                   \
+            name, BoolAttribute::get(pir::IrContext::Instance(), bool_data)); \
+      })
+
+#define DEF_VALUE_POINTER_PROPERTY(name)                                     \
+  def_property(                                                              \
+      name,                                                                  \
+      [](Value self) -> py::object {                                         \
+        auto prop_ptr = self.property(name);                                 \
+        if (!prop_ptr) {                                                     \
+          return py::cast<py::none>(Py_None);                                \
+        }                                                                    \
+        auto py_data = reinterpret_cast<PyObject *>(prop_ptr);               \
+        py::object obj = py::object(py::handle(py_data), true);              \
+        return obj;                                                          \
+      },                                                                     \
+      [](Value self, py::object obj) {                                       \
+        pir::PropertiesDeleter deleter = [](void *python_obj) {              \
+          Py_DECREF(python_obj);                                             \
+        };                                                                   \
+        PyObject *pointer_data = obj.release().ptr();                        \
+        pir::Property value_property(reinterpret_cast<void *>(pointer_data), \
+                                     deleter);                               \
+        self.set_property(name, value_property);                             \
+      })
+
 void BindValue(py::module *m) {
   py::class_<Value> value(*m,
                           "Value",
@@ -834,8 +868,7 @@ void BindValue(py::module *m) {
         The constructor of Value should not be invoked directly. Value can be automatically constructed
         when build network.
 
-  )DOC",
-                          pybind11::dynamic_attr());
+  )DOC");
   g_ir_value_pytype = reinterpret_cast<PyTypeObject *>(value.ptr());
   value.def(py::init<>())
       .def_property_readonly(
@@ -916,30 +949,15 @@ void BindValue(py::module *m) {
                return true;
              }
            })
-      .def_property(
-          "stop_gradient",
-          [](Value self) {
-            auto stop_gradient =
-                self.attribute<BoolAttribute>(kAttrStopGradients);
-            return !stop_gradient || stop_gradient.data();
-          },
-          [](Value self, bool stop_gradient) {
-            self.set_attribute(
-                kAttrStopGradients,
-                BoolAttribute::get(pir::IrContext::Instance(), stop_gradient));
-          })
-      .def_property(
-          "persistable",
-          [](Value self) {
-            auto persistable =
-                self.attribute<BoolAttribute>(kAttrIsPersistable);
-            return !persistable || persistable.data();
-          },
-          [](Value self, bool persistable) {
-            self.set_attribute(
-                kAttrIsPersistable,
-                BoolAttribute::get(pir::IrContext::Instance(), persistable));
-          })
+      .DEF_VALUE_BOOL_PROPERTY("stop_gradient")
+      .DEF_VALUE_BOOL_PROPERTY("trainable")
+      .DEF_VALUE_BOOL_PROPERTY("persistable")
+      .DEF_VALUE_BOOL_PROPERTY("need_clip")
+      .DEF_VALUE_BOOL_PROPERTY("is_distributed")
+      .DEF_VALUE_BOOL_PROPERTY("is_parameter")
+      .DEF_VALUE_POINTER_PROPERTY("optimize_attr")
+      .DEF_VALUE_POINTER_PROPERTY("regularizer")
+      .DEF_VALUE_POINTER_PROPERTY("do_model_average")
       .def("all_used_ops",
            [](Value &self) -> py::list {
              py::list op_list;

diff --git a/paddle/pir/include/core/attribute.h b/paddle/pir/include/core/attribute.h
@@ -19,7 +19,7 @@
 #include "paddle/pir/include/core/type_id.h"
 
 constexpr char kAttrStopGradients[] = "stop_gradient";
-constexpr char kAttrIsPersistable[] = "is_persistable";
+constexpr char kAttrIsPersistable[] = "persistable";
 constexpr char kAttrOpDistAttr[] = "op_dist_attr";
 
 namespace pir {

diff --git a/paddle/pir/include/core/op_result.h b/paddle/pir/include/core/op_result.h
@@ -38,6 +38,9 @@ class IR_API OpResult : public Value {
   Attribute attribute(const std::string &key) const;
   void set_attribute(const std::string &key, Attribute value);
 
+  void *property(const std::string &key) const;
+  void set_property(const std::string &key, const Property &value);
+
  private:
   friend Operation;
   OpResult(detail::OpResultImpl *impl);  // NOLINT

diff --git a/paddle/pir/include/core/operation.h b/paddle/pir/include/core/operation.h
@@ -117,6 +117,12 @@ class IR_API alignas(8) Operation final
     return attributes_.find(key) != attributes_.end();
   }
 
+  void set_value_property(const std::string &key,
+                          const Property &value,
+                          size_t index);
+
+  void *value_property(const std::string &key, size_t index) const;
+
   ///
   /// \brief op ouput related public interfaces
   ///
@@ -266,6 +272,9 @@ class IR_API alignas(8) Operation final
 
   AttributeMap attributes_;
 
+  // store data that user create by Python
+  std::vector<PropertyMap> value_properties_;
+
   OpInfo info_;
 
   static uint64_t GenerateId() {

diff --git a/paddle/pir/include/core/operation_utils.h b/paddle/pir/include/core/operation_utils.h
@@ -28,6 +28,7 @@
 namespace pir {
 class Block;
 using AttributeMap = std::unordered_map<std::string, Attribute>;
+using PropertyMap = std::unordered_map<std::string, Property>;
 
 //===----------------------------------------------------------------------===//
 // OperationArgument

diff --git a/paddle/pir/include/core/value.h b/paddle/pir/include/core/value.h
@@ -21,6 +21,8 @@
 
 namespace pir {
 class Operation;
+using PropertiesDeleter = void (*)(void *);
+using Property = std::pair<void *, PropertiesDeleter>;
 
 namespace detail {
 class ValueImpl;
@@ -116,6 +118,10 @@ class IR_API Value {
 
   void set_attribute(const std::string &key, Attribute value);
 
+  void set_property(const std::string &key, const Property &value);
+
+  void *property(const std::string &name) const;
+
  protected:
   detail::ValueImpl *impl_{nullptr};
 };

diff --git a/paddle/pir/src/core/op_result.cc b/paddle/pir/src/core/op_result.cc
@@ -57,6 +57,14 @@ void OpResult::set_attribute(const std::string &key, Attribute value) {
   return IMPL_->set_attribute(key, value);
 }
 
+void *OpResult::property(const std::string &key) const {
+  return impl_ ? IMPL_->property(key) : nullptr;
+}
+void OpResult::set_property(const std::string &key, const Property &value) {
+  CHECK_OPRESULT_NULL_IMPL(set_property);
+  return IMPL_->set_property(key, value);
+}
+
 OpResult::OpResult(detail::OpResultImpl *impl) : Value(impl) {}
 
 }  // namespace pir
diff --git a/paddle/pir/src/core/op_result_impl.cc b/paddle/pir/src/core/op_result_impl.cc
@@ -90,6 +90,15 @@ void OpResultImpl::set_attribute(const std::string &key, Attribute value) {
   owner->set_attribute(key, ArrayAttribute::get(owner->ir_context(), vec));
 }
 
+void *OpResultImpl::property(const std::string &key) const {
+  return owner()->value_property(key, index());
+}
+
+void OpResultImpl::set_property(const std::string &key, const Property &value) {
+  auto owner = this->owner();
+  owner->set_value_property(key, value, index());
+}
+
 OpInlineResultImpl::OpInlineResultImpl(Type type, uint32_t result_index)
     : OpResultImpl(type, result_index) {
   PADDLE_ENFORCE_LE(

diff --git a/paddle/pir/src/core/op_result_impl.h b/paddle/pir/src/core/op_result_impl.h
@@ -50,6 +50,9 @@ class OpResultImpl : public ValueImpl {
   Attribute attribute(const std::string &key) const;
   void set_attribute(const std::string &key, Attribute value);
 
+  void *property(const std::string &key) const;
+  void set_property(const std::string &key, const Property &value);
+
  private:
   int32_t ComputeOperationOffset() const;
 };

diff --git a/paddle/pir/src/core/operation.cc b/paddle/pir/src/core/operation.cc
@@ -199,26 +199,35 @@ void Operation::Destroy() {
     }
   }
 
-  // 3. Deconstruct Operation.
+  // 3. Deconstruct Properties.
+  for (auto &value_property : value_properties_) {
+    for (auto &property_map : value_property) {
+      if (property_map.second.second) {
+        property_map.second.second((property_map.second.first));
+      }
+    }
+  }
+
+  // 4. Deconstruct Operation.
   this->~Operation();
 
-  // 4. Deconstruct OpOperand.
+  // 5. Deconstruct OpOperand.
   for (size_t idx = 0; idx < num_operands_; idx++) {
     detail::OpOperandImpl *op_operand_impl = operand(idx).impl_;
     if (op_operand_impl) {
       op_operand_impl->~OpOperandImpl();
     }
   }
 
-  // 5. Deconstruct BlockOperand.
+  // 6. Deconstruct BlockOperand.
   for (size_t idx = 0; idx < num_successors_; idx++) {
     detail::BlockOperandImpl *block_operand_impl = block_operands_ + idx;
     if (block_operand_impl) {
       block_operand_impl->~BlockOperandImpl();
     }
   }
 
-  // 5. Free memory.
+  // 7. Free memory.
   size_t result_mem_size =
       num_results_ > OUTLINE_RESULT_IDX
           ? sizeof(detail::OpOutlineResultImpl) *
@@ -399,6 +408,28 @@ int32_t Operation::ComputeOpOperandOffset(uint32_t index) const {
                               sizeof(Operation));
 }
 
+void Operation::set_value_property(const std::string &key,
+                                   const Property &value,
+                                   size_t index) {
+  if (value_properties_.size() < index + 1) {
+    value_properties_.resize(index + 1);
+  }
+  auto &property_map = value_properties_[index];
+  if (property_map.count(key)) {
+    property_map[key].second(property_map[key].first);
+  }
+  property_map[key] = value;
+}
+
+void *Operation::value_property(const std::string &key, size_t index) const {
+  if (value_properties_.size() < (index + 1)) {
+    return nullptr;
+  }
+  auto &property_map = value_properties_[index];
+  auto iter = property_map.find(key);
+  return iter == property_map.end() ? nullptr : iter->second.first;
+}
+
 #define COMPONENT_IMPL(component_lower, component_upper)                   \
   component_upper##Impl *Operation::component_lower##_impl(uint32_t index) \
       const {                                                              \

diff --git a/paddle/pir/src/core/value.cc b/paddle/pir/src/core/value.cc
@@ -110,4 +110,22 @@ void Value::set_attribute(const std::string &key, Attribute value) {
   return dyn_cast<BlockArgument>().set_attribute(key, value);
 }
 
+void Value::set_property(const std::string &key, const Property &value) {
+  auto op_result = dyn_cast<OpResult>();
+  PADDLE_ENFORCE_NE(op_result,
+                    nullptr,
+                    common::errors::PreconditionNotMet(
+                        "The Value is not an OpResult, we can set property "
+                        "only for OpResult currently"));
+  return op_result.set_property(key, value);
+}
+
+void *Value::property(const std::string &key) const {
+  auto op_result = dyn_cast<OpResult>();
+  if (op_result) {
+    return op_result.property(key);
+  } else {
+    return nullptr;
+  }
+}
 }  // namespace pir
diff --git a/python/paddle/amp/auto_cast.py b/python/paddle/amp/auto_cast.py
@@ -260,8 +260,15 @@ def _pir_transform(t, dtype):
         paddle.pir.reset_insertion_point_to_start()
         block = main.global_block()
         cast_param = paddle._pir_ops.parameter(t.name)
+        cast_param.trainable = t.trainable
         cast_param.stop_gradient = t.stop_gradient
         cast_param.persistable = t.persistable
+        cast_param.optimize_attr = t.optimize_attr
+        cast_param.regularizer = t.regularizer
+        cast_param.do_model_average = t.do_model_average
+        cast_param.need_clip = t.need_clip
+        cast_param.is_distributed = t.is_distributed
+        cast_param.is_parameter = t.is_parameter
         op = t.get_defining_op()
         t.replace_all_uses_with(cast_param)
         block.remove_op(op)

diff --git a/python/paddle/autograd/ir_backward.py b/python/paddle/autograd/ir_backward.py
@@ -1167,7 +1167,7 @@ def append_backward(loss, parameter_list=None, no_grad_set=None):
         ops = loss.get_defining_op().get_parent_block().ops
         parameter_list = []
         for op in ops:
-            if not op.has_attr("is_persistable"):
+            if not op.has_attr("persistable"):
                 continue
             persist_value = [
                 result for result in op.results() if result.persistable

diff --git a/python/paddle/base/data_feeder.py b/python/paddle/base/data_feeder.py
@@ -440,7 +440,7 @@ def __init__(self, feed_list, place, program=None):
                     raise TypeError("Feed list should contain a list of Value")
                 self.feed_dtypes.append(each_var.dtype)
                 self.feed_names.append(each_var.name)
-                self.feed_lod_level.append(each_var.lod_level)
+                self.feed_lod_level.append(0)
                 self.feed_shapes.append(each_var.shape)
         else:
             if program is None:

diff --git a/python/paddle/pir/core.py b/python/paddle/pir/core.py
@@ -288,16 +288,10 @@ def create_parameter(
     name=None,
     **kwargs,
 ):
-    regularizer = None
-    need_clip = None
     if 'initializer' not in kwargs:
         raise ValueError(
             "initializer is None, if you want to create parameter, please pass its initializer."
         )
-    if 'regularizer' in kwargs:
-        regularizer = kwargs['regularizer']
-    if 'need_clip' in kwargs:
-        need_clip = kwargs['need_clip']
     if dtype is not None:
         if not isinstance(dtype, DataType):
             dtype = convert_np_dtype_to_dtype_(dtype)
@@ -320,12 +314,16 @@ def create_parameter(
     with program_guard(default_main_program()):
         reset_insertion_point_to_start()
         param = parameter(value_name)
-        trainable = kwargs.get('trainable', True)
-        param.stop_gradient = not trainable
         param.persistable = True
 
-    param.regularizer = regularizer
-    param.need_clip = need_clip
+    param.trainable = kwargs.get('trainable', True)
+    param.stop_gradient = not param.trainable
+    param.optimize_attr = kwargs.get('optimize_attr', {'learning_rate': 1.0})
+    param.regularizer = kwargs.get('regularizer', None)
+    param.do_model_average = kwargs.get('do_model_average', None)
+    param.need_clip = kwargs.get('need_clip', True)
+    param.is_distributed = False
+    param.is_parameter = True
     return param
 
 

diff --git a/python/paddle/static/input.py b/python/paddle/static/input.py
@@ -139,7 +139,6 @@ def _reset_data_op_insertion_point():
         prev_insertion_point = get_current_insertion_point()
         _reset_data_op_insertion_point()
         out = paddle._pir_ops.data(name, shape, ir_dtype, core.Place())
-        out.lod_level = lod_level
         set_insertion_point(prev_insertion_point)
         return out
 

diff --git a/test/dygraph_to_static/test_tensor_attr_consistency.py b/test/dygraph_to_static/test_tensor_attr_consistency.py
@@ -109,6 +109,13 @@
         'dist_attr',
         'value_assign',
         'replace_grad_users_with',
+        'do_model_average',
+        'is_distributed',
+        'is_parameter',
+        'need_clip',
+        'optimize_attr',
+        'regularizer',
+        'trainable',
     ]
 )