Integrate static code gen info (#49858)

* polish static grad op maker gen

* fix some bugs

* fix static code gen

* solve conflict

* modify composite grad maker name

* integrate phi and fluid info in static code gen

* rename some composite maker

* modify static code gen format

paddle/fluid/framework/details/op_registry.h

@@ -63,7 +63,7 @@ using OpRegistryClasses = std::tuple<                                // NOLINT
     TypePair<OpProtoAndCheckerMaker, kOpProtoAndCheckerMaker>,       // NOLINT
     TypePair<GradOpDescMakerBase, kGradOpDescMaker>,                 // NOLINT
     TypePair<imperative::GradOpBaseMakerBase, kGradOpBaseMaker>,     // NOLINT
-    TypePair<prim::GradCompositeOpMakerBase, kGradCompOpDescMaker>,  // NOLINT
+    TypePair<prim::CompositeGradOpMakerBase, kGradCompOpDescMaker>,  // NOLINT
     TypePair<VarTypeInference, kVarTypeInference>,                   // NOLINT
     TypePair<InferShapeBase, kShapeInference>,                       // NOLINT
     TypePair<InplaceOpInference, kInplaceOpInference>,               // NOLINT
@@ -262,7 +262,7 @@ struct OpInfoFiller<T, kGradCompOpDescMaker> {
         info->grad_comp_op_maker_,
         nullptr,
         platform::errors::AlreadyExists(
-            "GradCompositeOpMakerBase of %s has been registered", op_type));
+            "CompositeGradOpMakerBase of %s has been registered", op_type));
 
     info->grad_comp_op_maker_ =
         [](const OpDesc& fwd_op,

paddle/fluid/framework/op_info.h

@@ -43,7 +43,7 @@ class OpInfo {
  public:
   OpCreator creator_;
   GradOpMakerFN grad_op_maker_;
-  GradCompositeOpMakerFN grad_comp_op_maker_;
+  CompositeGradOpMakerFN grad_comp_op_maker_;
   proto::OpProto* proto_{nullptr};
   OpAttrChecker* checker_{nullptr};
   InferVarTypeFN infer_var_type_;
@@ -84,7 +84,7 @@ class OpInfo {
 
   const GradOpMakerFN& GradOpMaker() const { return grad_op_maker_; }
 
-  const GradCompositeOpMakerFN& GradCompOpMaker() const {
+  const CompositeGradOpMakerFN& CompGradOpMaker() const {
     return grad_comp_op_maker_;
   }
 

paddle/fluid/framework/type_defs.h

@@ -96,7 +96,7 @@ using GradOpMakerFN = std::function<std::vector<std::unique_ptr<OpDesc>>(
     std::unordered_map<std::string, std::string>* /*grad_to_var*/,
     const std::vector<BlockDesc*>& grad_block)>;
 
-using GradCompositeOpMakerFN =
+using CompositeGradOpMakerFN =
     std::function<std::vector<std::unique_ptr<OpDesc>>(
         const OpDesc&,
         const std::unordered_set<std::string>& /*no_grad_set*/,

paddle/fluid/operators/elementwise/elementwise_add_op.cc

@@ -51,9 +51,9 @@ class ElementwiseAddOpMaker : public ElementwiseOpMaker {
   }
 };
 
-class ElementwiseAddGradCompositeOpMaker
-    : public prim::GradCompositeOpMakerBase {
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+class ElementwiseAddCompositeGradOpMaker
+    : public prim::CompositeGradOpMakerBase {
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
 
  public:
   void Apply() override {
@@ -122,7 +122,7 @@ REGISTER_OPERATOR(elementwise_add,
                   ::paddle::operators::ElementwiseOpInferVarType,
                   elementwise_addGradMaker<::paddle::framework::OpDesc>,
                   elementwise_addGradMaker<::paddle::imperative::OpBase>,
-                  ::paddle::operators::ElementwiseAddGradCompositeOpMaker,
+                  ::paddle::operators::ElementwiseAddCompositeGradOpMaker,
                   ::paddle::operators::ElementwiseOpInplaceInferer);
 
 namespace ops = paddle::operators;

paddle/fluid/operators/elementwise/elementwise_div_op.cc

@@ -67,9 +67,9 @@ class ElementwiseDivGradOpMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
-class ElementwiseDivGradCompositeOpMaker
-    : public prim::GradCompositeOpMakerBase {
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+class ElementwiseDivCompositeGradOpMaker
+    : public prim::CompositeGradOpMakerBase {
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
 
  public:
   void Apply() override {
@@ -123,7 +123,7 @@ REGISTER_OPERATOR(elementwise_div,
                   ops::ElementwiseOp,
                   ops::ElementwiseDivOpMaker,
                   ops::ElementwiseOpInferVarType,
-                  ops::ElementwiseDivGradCompositeOpMaker,
+                  ops::ElementwiseDivCompositeGradOpMaker,
                   ops::ElementwiseDivGradOpMaker<paddle::framework::OpDesc>,
                   ops::ElementwiseDivGradOpMaker<paddle::imperative::OpBase>);
 

paddle/fluid/operators/elementwise/elementwise_mul_op.cc

@@ -66,9 +66,9 @@ class ElementwiseMulOpGradMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
-class ElementwiseMulGradCompositeOpMaker
-    : public prim::GradCompositeOpMakerBase {
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+class ElementwiseMulCompositeGradOpMaker
+    : public prim::CompositeGradOpMakerBase {
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
 
  public:
   void Apply() override {
@@ -155,7 +155,7 @@ REGISTER_OPERATOR(elementwise_mul,
                   ops::ElementwiseOpInferVarType,
                   ops::ElementwiseMulOpGradMaker<paddle::framework::OpDesc>,
                   ops::ElementwiseMulOpGradMaker<paddle::imperative::OpBase>,
-                  ops::ElementwiseMulGradCompositeOpMaker);
+                  ops::ElementwiseMulCompositeGradOpMaker);
 REGISTER_OPERATOR(
     elementwise_mul_grad,
     ops::ElementwiseOpGrad,

paddle/fluid/operators/elementwise/elementwise_sub_op.cc

@@ -54,9 +54,9 @@ class ElementwiseSubOpMaker : public ElementwiseOpMaker {
   }
 };
 
-class ElementwiseSubGradCompositeOpMaker
-    : public prim::GradCompositeOpMakerBase {
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+class ElementwiseSubCompositeGradOpMaker
+    : public prim::CompositeGradOpMakerBase {
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
 
  public:
   void Apply() override {
@@ -109,7 +109,7 @@ REGISTER_OPERATOR(elementwise_sub,
                   ::paddle::operators::ElementwiseOpInferVarType,
                   elementwise_subGradMaker<::paddle::framework::OpDesc>,
                   elementwise_subGradMaker<::paddle::imperative::OpBase>,
-                  ::paddle::operators::ElementwiseSubGradCompositeOpMaker,
+                  ::paddle::operators::ElementwiseSubCompositeGradOpMaker,
                   ::paddle::operators::ElementwiseOpInplaceInferer);
 
 REGISTER_OPERATOR(

paddle/fluid/operators/expand_v2_op.cc

@@ -193,8 +193,8 @@ class ExpandV2GradOpMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
-class ExpandV2GradCompositeOpMaker : public prim::GradCompositeOpMakerBase {
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+class ExpandV2CompositeGradOpMaker : public prim::CompositeGradOpMakerBase {
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
 
  public:
   void Apply() override {
@@ -244,7 +244,7 @@ namespace ops = paddle::operators;
 REGISTER_OPERATOR(expand_v2,
                   ops::ExpandV2Op,
                   ops::ExpandV2OpMaker,
-                  ops::ExpandV2GradCompositeOpMaker,
+                  ops::ExpandV2CompositeGradOpMaker,
                   ops::ExpandV2GradOpMaker<paddle::framework::OpDesc>,
                   ops::ExpandV2GradOpMaker<paddle::imperative::OpBase>,
                   ExpandInferShapeFunctor);

paddle/fluid/operators/generator/filters.py

@@ -14,6 +14,7 @@
 
 import itertools
 import re
+from typing import Dict, List
 
 from type_mapping import (
     attr_types_map,
@@ -137,17 +138,23 @@ def to_composite_grad_opmaker_name(backward_op_name):
     for i in range(len(words)):
         words[i] = words[i].strip()
         words[i] = words[i].capitalize()
-    composite_grad_opmaker_name = words[0] + "Composite"
-    composite_grad_opmaker_name += "".join(word for word in words[1:])
-    composite_grad_opmaker_name += "OpMaker"
+    composite_grad_opmaker_name = "".join(word for word in words[:-1])
+    composite_grad_opmaker_name += "CompositeGradOpMaker"
     return composite_grad_opmaker_name
 
 
+def to_variable_names(dict_list: List[Dict], key: str) -> List[str]:
+    names = []
+    for var in dict_list:
+        names.append(var[key])
+    return names
+
+
 def cartesian_prod_attrs(attrs):
     items = []
     for attr in attrs:
         type_name = attr["typename"]
-        name = attr["name"]
+        name = attr["fluid_name"]
         if type_name == "Scalar":
             items.append((name, to_scalar_tensor_name(attr)))
         elif type_name == "IntArray":
@@ -176,11 +183,15 @@ def cartesian_prod_attrs(attrs):
 def cartesian_prod_mapping(op):
     kernels = op["kernel"]["func"]
     inputs = [
-        x["name"] for x in op["inputs"] if x["name"] in op["kernel"]["param"]
+        x["fluid_name"]
+        for x in op["inputs"]
+        if x["fluid_name"] in op["kernel"]["param"]
     ]
     inputs = [to_opmaker_name_cstr(input) for input in inputs]
     attrs = cartesian_prod_attrs(op["attrs"])
-    outputs = [to_opmaker_name_cstr(output["name"]) for output in op["outputs"]]
+    outputs = [
+        to_opmaker_name_cstr(output["fluid_name"]) for output in op["outputs"]
+    ]
 
     def vec(items):
         return "{" + ', '.join(items) + "}"

paddle/fluid/operators/generator/generate_op.py

@@ -28,6 +28,7 @@ from filters import (
     to_opmaker_name_cstr,
     to_pascal_case,
     to_scalar_tensor_name,
+    to_variable_names,
 )
 from jinja2 import Environment, FileSystemLoader, StrictUndefined
 from parse_utils import to_named_dict
@@ -60,6 +61,7 @@ env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
 env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
+env.filters["to_variable_names"] = to_variable_names
 env.tests["base_op"] = is_base_op
 env.tests["composite_op"] = is_composite_op
 env.tests["vec"] = is_vec
@@ -157,29 +159,26 @@ def process_int_array(op_item, int_array_configs):
                         ]
 
 
-def parse_composite_info(ops, backward_ops, backward_op_dict):
-    for op in ops:
-        if "backward" in op:
-            op["phi_backward"] = op["backward"]
-    for backward_op in backward_ops:
-        if "backward" in backward_op:
-            backward_op["phi_backward"] = backward_op["backward"]
-    for backward_op_name, op_dict in backward_op_dict.items():
-        if "composite" not in op_dict:
-            continue
-        op_dict["composite"]["phi_inputs"] = []
-        op_dict["composite"]["phi_attrs"] = []
-        op_dict["composite"]["phi_outputs"] = []
-        for input in op_dict["inputs"]:
-            op_dict["composite"]["phi_inputs"].append(input['name'])
-        for attr in op_dict["attrs"]:
-            op_dict["composite"]["phi_attrs"].append(attr['name'])
-        for output in op_dict["outputs"]:
-            op_dict["composite"]["phi_outputs"].append(output['name'])
-
-
-# replace name of op and params for OpMaker
-def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
+def add_composite_info(ops, backward_ops, backward_op_dict):
+    # add backward composite name in forward
+    for op in ops + backward_ops:
+        if (
+            op["backward"] in backward_op_dict
+            and "composite" in backward_op_dict[op["backward"]]
+        ):
+            op["backward_composite"] = op["backward"]
+        else:
+            op["backward_composite"] = None
+
+
+# add fluid name in ops and backward ops info
+def add_fluid_name(dict_list):
+    for item in dict_list:
+        item["fluid_name"] = item["name"]
+
+
+# add fluid name of op and params for OpMaker
+def add_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
     def get_phi_and_fluid_op_name(op_item):
         names = op_item.split('(')
         if len(names) == 1:
@@ -187,12 +186,14 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
         else:
             return names[0].strip(), names[1].split(')')[0].strip()
 
-    def update_op_param_name(op_args, args_alias_map):
+    def add_op_param_name(op_args, args_alias_map):
         for item in op_args:
             if item['name'] in args_alias_map:
-                item['name'] = args_alias_map[item['name']]
+                item['fluid_name'] = args_alias_map[item['name']]
+            else:
+                item['fluid_name'] = item['name']
 
-    def update_grad_args_name(op_args, args_alias_map):
+    def add_grad_args_name(op_args, args_alias_map):
         for item in op_args:
             if (
                 item['name'].endswith('_grad')
@@ -201,38 +202,12 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                 args_alias_map[item['name']] = (
                     args_alias_map[item['name'][:-5]] + '_grad'
                 )
-                item['name'] = args_alias_map[item['name'][:-5]] + '_grad'
-
-    def add_fluid_info_in_composite(composite_map, args_alias_map):
-        fluid_input_list = []
-        fluid_attr_list = []
-        fluid_output_list = []
-        # add fluid op inputs
-        for input in composite_map["phi_inputs"]:
-            if input in args_alias_map:
-                fluid_input_list.append(args_alias_map[input])
-            else:
-                fluid_input_list.append(input)
-        # add fluid op attrs
-        for attr in composite_map["phi_attrs"]:
-            if attr in args_alias_map:
-                fluid_attr_list.append(args_alias_map[attr])
-            else:
-                fluid_attr_list.append(attr)
-        # add fluid op outputs
-        for output in composite_map["phi_outputs"]:
-            if output in args_alias_map:
-                fluid_output_list.append(args_alias_map[output])
-            else:
-                fluid_output_list.append(output)
-
-        composite_map.update(
-            {
-                "fluid_inputs": fluid_input_list,
-                "fluid_attrs": fluid_attr_list,
-                "fluid_outputs": fluid_output_list,
-            }
-        )
+                item['fluid_name'] = args_alias_map[item['name'][:-5]] + '_grad'
+            elif (
+                item['name'].endswith('_grad')
+                and item['name'][:-5] not in args_alias_map
+            ):
+                item['fluid_name'] = item['name']
 
     def get_param_list_alias(param_list, args_map):
         return [
@@ -297,15 +272,15 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                 op_item['kernel']['layout']['candidates'], args_name_map
             )
 
-    def update_grad_op_compat_name(grad_op_item, args_name_map):
-        update_op_param_name(grad_op_item['inputs'], args_name_map)
-        update_op_param_name(grad_op_item['outputs'], args_name_map)
-        update_op_param_name(grad_op_item['attrs'], args_name_map)
-        update_op_param_name(grad_op_item['forward']['inputs'], args_name_map)
-        update_op_param_name(grad_op_item['forward']['outputs'], args_name_map)
-        update_op_param_name(grad_op_item['forward']['attrs'], args_name_map)
-        update_grad_args_name(grad_op_item['inputs'], args_map)
-        update_grad_args_name(grad_op_item['outputs'], args_map)
+    def add_grad_op_compat_name(grad_op_item, args_name_map):
+        add_op_param_name(grad_op_item['inputs'], args_name_map)
+        add_op_param_name(grad_op_item['outputs'], args_name_map)
+        add_op_param_name(grad_op_item['attrs'], args_name_map)
+        add_op_param_name(grad_op_item['forward']['inputs'], args_name_map)
+        add_op_param_name(grad_op_item['forward']['outputs'], args_name_map)
+        add_op_param_name(grad_op_item['forward']['attrs'], args_name_map)
+        add_grad_args_name(grad_op_item['inputs'], args_map)
+        add_grad_args_name(grad_op_item['outputs'], args_map)
 
     for op_args in op_fluid_map_list:
         new_op_name, op_name = get_phi_and_fluid_op_name(op_args['op'])
@@ -350,39 +325,32 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                             int_array_configs[
                                 op_args[key][args_item['name']]
                             ] = int_array_configs[args_item['name']]
-                        args_item['name'] = op_args[key][args_item['name']]
-                if has_backward:
-                    for args_item in backward_op_item['forward'][key]:
-                        if args_item['name'] in op_args[key]:
-                            args_item['name'] = op_args[key][args_item['name']]
-        forward_op_item["attr_dict"] = to_named_dict(forward_op_item["attrs"])
+                        args_item['fluid_name'] = op_args[key][
+                            args_item['name']
+                        ]
         update_common_params_name(
             forward_op_item, args_map, scalar_configs, int_array_configs
         )
 
         if has_backward:
-            update_grad_op_compat_name(backward_op_item, args_map)
+            # update fluid info in backward
+            add_grad_op_compat_name(backward_op_item, args_map)
             update_common_params_name(
                 backward_op_item, args_map, scalar_configs, int_array_configs
             )
-            backward_op_item["attr_dict"] = to_named_dict(
-                backward_op_item["attrs"]
-            )
 
             if 'backward' not in op_args:
                 continue
 
             backward_op_list = op_args['backward'].split(',')
-            # add fluid args name in composite map
-            for backward_op in backward_op_list:
-                if (
-                    "composite"
-                    in backward_op_dict[backward_op.split('(')[0].strip()]
-                ):
-                    add_fluid_info_in_composite(
-                        backward_op_dict[backward_op]["composite"], args_map
-                    )
-            _, bw_op_name = get_phi_and_fluid_op_name(backward_op_list[0])
+            phi_bw_op_name, bw_op_name = get_phi_and_fluid_op_name(
+                backward_op_list[0]
+            )
+            if (
+                forward_op_item["backward_composite"] is not None
+                and phi_bw_op_name != bw_op_name
+            ):
+                forward_op_item["backward_composite"] = bw_op_name
             forward_op_item['backward'] = bw_op_name
             backward_op_item['op_name'] = bw_op_name
 
@@ -393,18 +361,20 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                     double_grad_op_name,
                 ) = get_phi_and_fluid_op_name(backward_op_list[1])
                 double_grad_item = backward_op_dict[phi_double_grad_op_name]
+                if (
+                    backward_op_item["backward_composite"] is not None
+                    and phi_double_grad_op_name != double_grad_op_name
+                ):
+                    backward_op_item["backward_composite"] = double_grad_op_name
                 backward_op_item['backward'] = double_grad_op_name
                 double_grad_item['op_name'] = double_grad_op_name
-                update_grad_op_compat_name(double_grad_item, args_map)
+                add_grad_op_compat_name(double_grad_item, args_map)
                 update_common_params_name(
                     double_grad_item,
                     args_map,
                     scalar_configs,
                     int_array_configs,
                 )
-                double_grad_item["attr_dict"] = to_named_dict(
-                    double_grad_item["attrs"]
-                )
 
                 # for triple grad
                 if len(backward_op_list) > 2:
@@ -413,18 +383,22 @@ def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                         triple_grad_op_name,
                     ) = get_phi_and_fluid_op_name(backward_op_list[2])
                     triple_grad_item = backward_op_dict[phi_triple_grad_op_name]
+                    if (
+                        double_grad_item["backward_composite"] is not None
+                        and phi_triple_grad_op_name != triple_grad_op_name
+                    ):
+                        double_grad_item[
+                            "backward_composite"
+                        ] = triple_grad_op_name
                     double_grad_item['backward'] = triple_grad_op_name
                     triple_grad_item['op_name'] = triple_grad_op_name
-                    update_grad_op_compat_name(triple_grad_item, args_map)
+                    add_grad_op_compat_name(triple_grad_item, args_map)
                     update_common_params_name(
                         triple_grad_item,
                         args_map,
                         scalar_configs,
                         int_array_configs,
                     )
-                    triple_grad_item["attr_dict"] = to_named_dict(
-                        triple_grad_item["attrs"]
-                    )
 
 
 def process_invoke_op(forward_op_dict, backward_op_dict):
@@ -442,20 +416,28 @@ def process_invoke_op(forward_op_dict, backward_op_dict):
                 for input_item in reuse_op['inputs']:
                     bw_op['invoke']['inputs'].append(
                         {
+                            'fluid_name': input_item['fluid_name'],
                             'name': input_item['name'],
                             'value': args_list[args_index],
                         }
                     )
                     args_index = args_index + 1
+                bw_fluid_attrs_set = [
+                    item['fluid_name'] for item in bw_op['attrs']
+                ]
                 for attr in reuse_op['attrs']:
                     if args_index < len(args_list):
                         attr_value = (
                             f"this->GetAttr(\"{args_list[args_index]}\")"
-                            if args_list[args_index] in bw_op['attr_dict']
+                            if args_list[args_index] in bw_fluid_attrs_set
                             else args_list[args_index]
                         )
                         bw_op['invoke']['attrs'].append(
-                            {'name': attr['name'], 'value': attr_value}
+                            {
+                                'name': attr['name'],
+                                'fluid_name': attr['fluid_name'],
+                                'value': attr_value,
+                            }
                         )
                         args_index = args_index + 1
                     else:
@@ -464,7 +446,8 @@ def process_invoke_op(forward_op_dict, backward_op_dict):
                     bw_op['invoke']['outputs'].append(
                         {
                             'name': output_item['name'],
-                            'value': bw_op['outputs'][idx]['name'],
+                            'fluid_name': output_item['fluid_name'],
+                            'value': bw_op['outputs'][idx]['fluid_name'],
                         }
                     )
 
@@ -517,17 +500,26 @@ def main(
 
     for op in ops:
         op['op_name'] = op['name']
+        add_fluid_name(op['inputs'])
+        add_fluid_name(op['attrs'])
+        add_fluid_name(op['outputs'])
     for bw_op in backward_ops:
         bw_op['op_name'] = bw_op['name']
+        add_fluid_name(bw_op['inputs'])
+        add_fluid_name(bw_op['attrs'])
+        add_fluid_name(bw_op['outputs'])
+        add_fluid_name(bw_op['forward']['inputs'])
+        add_fluid_name(bw_op['forward']['attrs'])
+        add_fluid_name(bw_op['forward']['outputs'])
         for bw_output in bw_op['outputs']:
             bw_output['drop_empty_grad'] = True
 
     # deal the drop_empty_grad of bw_op by op_compat.yaml
     parse_drop_empty_grad(op_fluid_map_list, backward_op_dict)
 
-    parse_composite_info(ops, backward_ops, backward_op_dict)
+    add_composite_info(ops, backward_ops, backward_op_dict)
 
-    replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict)
+    add_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict)
 
     # prepare for invoke case
     process_invoke_op(forward_op_dict, backward_op_dict)
@@ -555,7 +547,6 @@ def main(
             ops=ops,
             backward_ops=backward_ops,
             op_dict=op_dict,
-            composite_gen_flag=True,
         )
         f.write(msg)
     ks_template = env.get_template('ks.c.j2')

paddle/fluid/operators/generator/generate_sparse_op.py

@@ -28,12 +28,14 @@ from filters import (
     to_opmaker_name_cstr,
     to_pascal_case,
     to_scalar_tensor_name,
+    to_variable_names,
 )
-from generate_op import process_invoke_op
+from generate_op import add_fluid_name, process_invoke_op
 from jinja2 import Environment, FileSystemLoader, StrictUndefined
 from parse_utils import to_named_dict
 from tests import (
     is_base_op,
+    is_composite_op,
     is_initializer_list,
     is_scalar,
     is_vec,
@@ -60,7 +62,9 @@ env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
 env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
+env.filters["to_variable_names"] = to_variable_names
 env.tests["base_op"] = is_base_op
+env.tests["composite_op"] = is_composite_op
 env.tests["vec"] = is_vec
 env.tests["scalar"] = is_scalar
 env.tests["initializer_list"] = is_initializer_list
@@ -96,9 +100,18 @@ def main(op_yaml_path, backward_yaml_path, output_op_path, output_arg_map_path):
         op['name'] = op['op_name']
         if op["backward"] is not None:
             op["backward"] = SPARSE_OP_PREFIX + op["backward"]
+        add_fluid_name(op["inputs"])
+        add_fluid_name(op["attrs"])
+        add_fluid_name(op["outputs"])
     for bw_op in backward_ops:
         bw_op['op_name'] = SPARSE_OP_PREFIX + bw_op['name']
         bw_op['name'] = bw_op['op_name']
+        add_fluid_name(bw_op["inputs"])
+        add_fluid_name(bw_op["attrs"])
+        add_fluid_name(bw_op["outputs"])
+        add_fluid_name(bw_op["forward"]["inputs"])
+        add_fluid_name(bw_op["forward"]["attrs"])
+        add_fluid_name(bw_op["forward"]["outputs"])
         if 'invoke' in bw_op:
             bw_op['invoke']['args'] = [
                 param.strip() for param in bw_op['invoke']['args'].split(',')
@@ -139,7 +152,6 @@ def main(op_yaml_path, backward_yaml_path, output_op_path, output_arg_map_path):
             ops=ops,
             backward_ops=backward_ops,
             op_dict=op_dict,
-            composite_gen_flag=False,
         )
         f.write(msg)
 

paddle/fluid/operators/generator/generate_static_op.py

@@ -28,12 +28,14 @@ from filters import (
     to_opmaker_name_cstr,
     to_pascal_case,
     to_scalar_tensor_name,
+    to_variable_names,
 )
-from generate_op import replace_compat_name
+from generate_op import add_compat_name, add_fluid_name
 from jinja2 import Environment, FileSystemLoader, StrictUndefined
 from parse_utils import to_named_dict
 from tests import (
     is_base_op,
+    is_composite_op,
     is_initializer_list,
     is_scalar,
     is_vec,
@@ -60,7 +62,9 @@ env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
 env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
+env.filters["to_variable_names"] = to_variable_names
 env.tests["base_op"] = is_base_op
+env.tests["composite_op"] = is_composite_op
 env.tests["vec"] = is_vec
 env.tests["scalar"] = is_scalar
 env.tests["initializer_list"] = is_initializer_list
@@ -100,8 +104,11 @@ def main(
 
     for op in ops:
         op['op_name'] = op['name']
+        add_fluid_name(op["inputs"])
+        add_fluid_name(op["attrs"])
+        add_fluid_name(op["outputs"])
 
-    replace_compat_name(op_op_map, forward_op_dict, {})
+    add_compat_name(op_op_map, forward_op_dict, {})
 
     if len(ops) == 0:
         if os.path.isfile(output_op_path):
@@ -116,7 +123,6 @@ def main(
             ops=ops,
             backward_ops=[],
             op_dict=forward_op_dict,
-            composite_gen_flag=False,
         )
         f.write(msg)
 

paddle/fluid/operators/generator/parse_utils.py

@@ -294,14 +294,13 @@ def parse_composite(
     composite_config: str,
 ) -> Dict[str, Any]:
     # composite_config: func(args1, args2,.....)
-    fname = r'(.*?)'
-    wspace = r'\s*'
-    fargs = r'(.*?)'
-    pattern = fr'{fname}{wspace}\({wspace}{fargs}{wspace}\)'
-
-    m = re.search(pattern, composite_config)
-    func_name = m.group(1)
-    func_args = m.group(2)
+    result = re.search(
+        r"(?P<func_name>[a-z][a-z0-9_]+)\s*\((?P<func_args>[^\)]+)\)",
+        composite_config,
+    )
+
+    func_name = result.group("func_name")
+    func_args = result.group("func_args")
 
     composite_dict = {}
     composite_dict["func_name"] = func_name

paddle/fluid/operators/generator/templates/op.c.j2

@@ -39,11 +39,9 @@ using paddle::framework::GradVarName;
   {% else %}
 {{backward_op_reused_maker(op, op_dict[op["forward"]["name"]], op["invoke"])}}
   {% endif %}
-  {% if composite_gen_flag == True %}
-    {% if op is composite_op %}
+  {% if op is composite_op %}
 {{composite_grad_op_maker(op_dict[op["name"]])}}
-    {% endif %}
-  {% endif %}  
+  {% endif %}
 {% endfor %}
 }  // namespace operators
 }  // namespace paddle
@@ -51,7 +49,7 @@ using paddle::framework::GradVarName;
 namespace ops = paddle::operators;
 {% for op in ops + backward_ops %}
 {% if op is base_op %}
-{{register_op_with_components(op, op_dict)}}
+{{register_op_with_components(op)}}
 {{register_op_version(op)}}
 {% endif %}
 {% endfor %}

paddle/fluid/operators/reduce_ops/reduce_sum_op.cc

@@ -64,9 +64,9 @@ class ReduceSumOpGradMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
-class ReduceSumCompositeGradOpMaker : public prim::GradCompositeOpMakerBase {
+class ReduceSumCompositeGradOpMaker : public prim::CompositeGradOpMakerBase {
  public:
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
   void Apply() override {
     // get inputs
     paddle::experimental::Tensor x = this->GetSingleForwardInput("X");

paddle/fluid/prim/tests/test_static_prim.cc

@@ -135,9 +135,9 @@ struct TestBaseProgram {
   int idx_{0};
 };
 
-class TestGradCompositeGradMaker : public GradCompositeOpMakerBase {
+class TestCompositeGradMaker : public CompositeGradOpMakerBase {
  public:
-  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
+  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
   void Apply() override {}
 };
 
@@ -177,7 +177,7 @@ TEST(StaticPrim, TanhBackwardComposite) {
   std::vector<std::unique_ptr<framework::OpDesc>> grad_ops =
       std::move(framework::OpInfoMap::Instance()
                     .Get(forward_opdesc->Type())
-                    .GradCompOpMaker()(*forward_opdesc,
+                    .CompGradOpMaker()(*forward_opdesc,
                                        std::unordered_set<std::string>(),
                                        &grad_to_var,
                                        target_block,
@@ -250,11 +250,11 @@ TEST(StaticCompositeGradMaker, TestMutiInputMethod) {
   auto* forward_opdesc = target_block->AllOps()[0];
   std::unordered_map<std::string, std::string> grad_to_var;
   std::vector<framework::BlockDesc*> grad_sub_block;
-  auto test = TestGradCompositeGradMaker(*forward_opdesc,
-                                         std::unordered_set<std::string>(),
-                                         &grad_to_var,
-                                         target_block,
-                                         grad_sub_block);
+  auto test = TestCompositeGradMaker(*forward_opdesc,
+                                     std::unordered_set<std::string>(),
+                                     &grad_to_var,
+                                     target_block,
+                                     grad_sub_block);
   test();
   std::vector<paddle::experimental::Tensor> muti_fw_input =
       test.GetMultiForwardInput("X");
@@ -312,11 +312,11 @@ TEST(StaticCompositeGradMaker, TestMutiOutputMethod) {
   auto* forward_opdesc = target_block->AllOps()[0];
   std::unordered_map<std::string, std::string> grad_to_var;
   std::vector<framework::BlockDesc*> grad_sub_block;
-  auto test = TestGradCompositeGradMaker(*forward_opdesc,
-                                         std::unordered_set<std::string>(),
-                                         &grad_to_var,
-                                         target_block,
-                                         grad_sub_block);
+  auto test = TestCompositeGradMaker(*forward_opdesc,
+                                     std::unordered_set<std::string>(),
+                                     &grad_to_var,
+                                     target_block,
+                                     grad_sub_block);
   test();
   paddle::experimental::Tensor fw_input = test.GetSingleForwardInput("X");
   paddle::optional<paddle::experimental::Tensor> opt_fw_input =

paddle/fluid/prim/utils/static/composite_grad_desc_maker.h

@@ -41,9 +41,9 @@ namespace prim {
   argument DropEmptyIG in the derived classes.
  */
 
-class GradCompositeOpMakerBase {
+class CompositeGradOpMakerBase {
  public:
-  explicit GradCompositeOpMakerBase(
+  explicit CompositeGradOpMakerBase(
       const framework::OpDesc& fwd_op,
       const std::unordered_set<std::string>& no_grad_set,
       std::unordered_map<std::string, std::string>* grad_to_var,
@@ -61,7 +61,7 @@ class GradCompositeOpMakerBase {
         acting_program_.MutableBlock(0));
   }
 
-  virtual ~GradCompositeOpMakerBase() = default;
+  virtual ~CompositeGradOpMakerBase() = default;
 
   virtual std::vector<std::unique_ptr<framework::OpDesc>> operator()() {
     this->Apply();

paddle/fluid/pybind/pybind.cc

@@ -1251,7 +1251,7 @@ All parameter, weight, gradient are variables in Paddle.
 
           auto op_info = framework::OpInfoMap::Instance().Get(op_desc.Type());
           auto grad_op_maker = op_info.GradOpMaker();
-          auto grad_comp_op_maker = op_info.GradCompOpMaker();
+          auto grad_comp_op_maker = op_info.CompGradOpMaker();
 
           if ((grad_op_maker == nullptr) && (grad_comp_op_maker == nullptr)) {
             // Normally, proto_ should not be null, except some special
@@ -1259,7 +1259,7 @@ All parameter, weight, gradient are variables in Paddle.
             std::string type =
                 op_info.proto_ ? op_info.proto_->type() : "unknown";
             PADDLE_THROW(platform::errors::NotFound(
-                "Neither operator %s's GradOpMaker nor GradCompOpMaker has "
+                "Neither operator %s's GradOpMaker nor CompGradOpMaker has "
                 "been registered.\nPlease check whether (%s) operator has "
                 "gradient operator.\nIf not, please set stop_gradient to be "
                 "True for its input and output variables using "
@@ -1268,10 +1268,10 @@ All parameter, weight, gradient are variables in Paddle.
                 type.c_str()));
           }
 
-          // In PrimEnabled mode, the priority of GradCompOpMaker is greater
+          // In PrimEnabled mode, the priority of CompGradOpMaker is greater
           // than GradCompMaker as we need split first-order grad operator into
           // primitive operators for compiler. In PrimDisabled mode, the
-          // priority of GradCompOpMaker is less than GradCompMaker for better
+          // priority of CompGradOpMaker is less than GradCompMaker for better
           // performance.
           std::vector<std::unique_ptr<OpDesc>> grad_op_descs;
           if (paddle::prim::PrimCommonUtils::IsBwdPrimEnabled()) {