Revert "[static code gen]Add phi and fluid info in static code gen (#49763)"

This reverts commit 4d5265b8.

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::CompositeGradOpMakerBase, kGradCompOpDescMaker>,  // NOLINT
+    TypePair<prim::GradCompositeOpMakerBase, 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(
-            "CompositeGradOpMakerBase of %s has been registered", op_type));
+            "GradCompositeOpMakerBase of %s has been registered", op_type));
 
     info->grad_comp_op_maker_ =
         [](const OpDesc& fwd_op,

paddle/fluid/operators/elementwise/elementwise_add_op.cc

@@ -52,8 +52,8 @@ class ElementwiseAddOpMaker : public ElementwiseOpMaker {
 };
 
 class ElementwiseAddGradCompositeOpMaker
-    : public prim::CompositeGradOpMakerBase {
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
+    : public prim::GradCompositeOpMakerBase {
+  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
 
  public:
   void Apply() override {

paddle/fluid/operators/elementwise/elementwise_div_op.cc

@@ -68,8 +68,8 @@ class ElementwiseDivGradOpMaker : public framework::SingleGradOpMaker<T> {
 };
 
 class ElementwiseDivGradCompositeOpMaker
-    : public prim::CompositeGradOpMakerBase {
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
+    : public prim::GradCompositeOpMakerBase {
+  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
 
  public:
   void Apply() override {

paddle/fluid/operators/elementwise/elementwise_sub_op.cc

@@ -55,8 +55,8 @@ class ElementwiseSubOpMaker : public ElementwiseOpMaker {
 };
 
 class ElementwiseSubGradCompositeOpMaker
-    : public prim::CompositeGradOpMakerBase {
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
+    : public prim::GradCompositeOpMakerBase {
+  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
 
  public:
   void Apply() override {

paddle/fluid/operators/generator/filters.py

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

paddle/fluid/operators/generator/generate_op.py

@@ -28,7 +28,6 @@ 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
@@ -61,7 +60,6 @@ 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
@@ -159,26 +157,29 @@ def process_int_array(op_item, int_array_configs):
                         ]
 
 
-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 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 get_phi_and_fluid_op_name(op_item):
         names = op_item.split('(')
         if len(names) == 1:
@@ -186,14 +187,12 @@ def add_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
         else:
             return names[0].strip(), names[1].split(')')[0].strip()
 
-    def add_op_param_name(op_args, args_alias_map):
+    def update_op_param_name(op_args, args_alias_map):
         for item in op_args:
             if item['name'] in args_alias_map:
-                item['fluid_name'] = args_alias_map[item['name']]
-            else:
-                item['fluid_name'] = item['name']
+                item['name'] = args_alias_map[item['name']]
 
-    def add_grad_args_name(op_args, args_alias_map):
+    def update_grad_args_name(op_args, args_alias_map):
         for item in op_args:
             if (
                 item['name'].endswith('_grad')
@@ -202,12 +201,38 @@ def add_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['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']
+                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,
+            }
+        )
 
     def get_param_list_alias(param_list, args_map):
         return [
@@ -262,15 +287,15 @@ def add_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
                 op_item['kernel']['layout']['candidates'], args_name_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)
+    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)
 
     for op_args in op_fluid_map_list:
         new_op_name, op_name = get_phi_and_fluid_op_name(op_args['op'])
@@ -315,32 +340,39 @@ def add_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['fluid_name'] = op_args[key][
-                            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"])
         update_common_params_name(
             forward_op_item, args_map, scalar_configs, int_array_configs
         )
 
         if has_backward:
-            # update fluid info in backward
-            add_grad_op_compat_name(backward_op_item, args_map)
+            update_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(',')
-            phi_bw_op_name, bw_op_name = get_phi_and_fluid_op_name(
-                backward_op_list[0]
-            )
+            # add fluid args name in composite map
+            for backward_op in backward_op_list:
                 if (
-                forward_op_item["backward_composite"] is not None
-                and phi_bw_op_name != bw_op_name
+                    "composite"
+                    in backward_op_dict[backward_op.split('(')[0].strip()]
                 ):
-                forward_op_item["backward_composite"] = bw_op_name
+                    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])
             forward_op_item['backward'] = bw_op_name
             backward_op_item['op_name'] = bw_op_name
 
@@ -351,20 +383,18 @@ def add_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
-                add_grad_op_compat_name(double_grad_item, args_map)
+                update_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:
@@ -373,22 +403,18 @@ def add_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
-                    add_grad_op_compat_name(triple_grad_item, args_map)
+                    update_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):
@@ -406,28 +432,20 @@ 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_fluid_attrs_set
+                            if args_list[args_index] in bw_op['attr_dict']
                             else args_list[args_index]
                         )
                         bw_op['invoke']['attrs'].append(
-                            {
-                                'name': attr['name'],
-                                'fluid_name': attr['fluid_name'],
-                                'value': attr_value,
-                            }
+                            {'name': attr['name'], 'value': attr_value}
                         )
                         args_index = args_index + 1
                     else:
@@ -436,8 +454,7 @@ def process_invoke_op(forward_op_dict, backward_op_dict):
                     bw_op['invoke']['outputs'].append(
                         {
                             'name': output_item['name'],
-                            'fluid_name': output_item['fluid_name'],
-                            'value': bw_op['outputs'][idx]['fluid_name'],
+                            'value': bw_op['outputs'][idx]['name'],
                         }
                     )
 
@@ -490,26 +507,17 @@ 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)
 
-    add_composite_info(ops, backward_ops, backward_op_dict)
+    parse_composite_info(ops, backward_ops, backward_op_dict)
 
-    add_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict)
+    replace_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)
@@ -537,6 +545,7 @@ 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

@@ -28,14 +28,12 @@ from filters import (
     to_opmaker_name_cstr,
     to_pascal_case,
     to_scalar_tensor_name,
-    to_variable_names,
 )
-from generate_op import add_fluid_name, process_invoke_op
+from generate_op import 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,
@@ -62,9 +60,7 @@ 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
 env.tests["scalar"] = is_scalar
 env.tests["initializer_list"] = is_initializer_list
@@ -100,18 +96,9 @@ 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(',')
@@ -152,6 +139,7 @@ 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

@@ -28,14 +28,12 @@ from filters import (
     to_opmaker_name_cstr,
     to_pascal_case,
     to_scalar_tensor_name,
-    to_variable_names,
 )
-from generate_op import add_compat_name, add_fluid_name
+from generate_op import replace_compat_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,
@@ -62,9 +60,7 @@ 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
 env.tests["scalar"] = is_scalar
 env.tests["initializer_list"] = is_initializer_list
@@ -104,11 +100,8 @@ 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"])
 
-    add_compat_name(op_op_map, forward_op_dict, {})
+    replace_compat_name(op_op_map, forward_op_dict, {})
 
     if len(ops) == 0:
         if os.path.isfile(output_op_path):
@@ -123,6 +116,7 @@ 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

@@ -294,13 +294,14 @@ def parse_composite(
     composite_config: str,
 ) -> Dict[str, Any]:
     # composite_config: func(args1, args2,.....)
-    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")
+    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)
 
     composite_dict = {}
     composite_dict["func_name"] = func_name

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

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

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

@@ -12,7 +12,7 @@ class {{op_name | to_pascal_case}}OpMaker : public framework::OpProtoAndCheckerM
 {{add_output(loop.index0, output, op_name)}};
     {% endfor %}
     {% for attr in op["attrs"] %}
-      {% if attr["fluid_name"] in op["kernel"]["param"] %}
+      {% if attr["name"] in op["kernel"]["param"] %}
 {{add_attr(loop.index0, attr, op_name)}};
       {% endif %}
     {% endfor %}
@@ -27,7 +27,7 @@ TODO: Documentation of {{op_name}} op.
 
 {# add input, it could be duplicable or dispensable #}
 {% macro add_input(i, input, op_name) %}{# inline #}
-  {% set name = input["fluid_name"] %}
+  {% set name = input["name"] %}
   {% set typename = input["typename"] %}
 AddInput({{name| to_opmaker_name}}, "({{typename}}), input {{i}} of {{op_name}} op.")
   {%- if typename is vec %}
@@ -42,7 +42,7 @@ AddInput({{name| to_opmaker_name}}, "({{typename}}), input {{i}} of {{op_name}}
 
 {# add output, it could be duplicable or intermediate, however, optional output is not supported #}
 {% macro add_output(i, output, op_name) %}{# inline #}
-  {% set name = output["fluid_name"] %}
+  {% set name = output["name"] %}
   {% set typename = output["typename"] %}
   {% set is_intermediate = output["intermediate"] %}
 AddOutput({{name | to_opmaker_name}}, "({{typename}}), output {{i}} of {{op_name}} op.")
@@ -66,7 +66,7 @@ AddOutput({{name | to_opmaker_name}}, "({{typename}}), output {{i}} of {{op_name
 
 {# add attribute, and process default value if needed #}
 {% macro add_attr(i, attr, op_name) %}{# inline #}
-  {% set name = attr["fluid_name"] %}
+  {% set name = attr["name"] %}
   {% set typename = attr["typename"] %}
   {% if typename is scalar %}
 AddInput("{{attr | to_scalar_tensor_name}}", "attribute {{i}} for {{op_name}} op from 0D Tensor.")
@@ -153,15 +153,15 @@ All possible KernelSignatures returned by {{op["name"] | to_pascal_case }}OpArgu
   {% set kernel_in_type_list = kernel_config["dispatch"][kernel_func][0] %}
 
   if ( {%- for input in inputs %}
-    {%- if input["fluid_name"] in kernel_config["param"] %}
+    {%- if input["name"] in kernel_config["param"] %}
       {%- if kernel_in_type_list[input_idx.idx] == "dense" %}
-ctx.IsDenseTensorInput("{{input["fluid_name"]}}"){{" && " if not loop.last}}
+ctx.IsDenseTensorInput("{{input["name"]}}"){{" && " if not loop.last}}
       {%- elif kernel_in_type_list[input_idx.idx] == "selected_rows" %}
-ctx.IsSelectedRowsInput("{{input["fluid_name"]}}"){{" && " if not loop.last}}
+ctx.IsSelectedRowsInput("{{input["name"]}}"){{" && " if not loop.last}}
       {%- elif kernel_in_type_list[input_idx.idx] == "sparse_coo" %}
-ctx.IsSparseCooTensorInput("{{input["fluid_name"]}}"){{" && " if not loop.last}}
+ctx.IsSparseCooTensorInput("{{input["name"]}}"){{" && " if not loop.last}}
       {%- elif kernel_in_type_list[input_idx.idx] == "sparse_csr" %}
-ctx.IsSparseCsrTensorInput("{{input["fluid_name"]}}"){{" && " if not loop.last}}
+ctx.IsSparseCsrTensorInput("{{input["name"]}}"){{" && " if not loop.last}}
       {%- endif %}
       {% set input_idx.idx = input_idx.idx + 1 %}
     {%- endif %}
@@ -210,8 +210,8 @@ PD_REGISTER_ARG_MAPPING_FN({{op["op_name"]}}, phi::{{op["op_name"] | to_pascal_c
 {% macro get_input_list(inputs, kernel_args) %}{# inline #}
 paddle::small_vector<const char*> inputs {
 {%- for input in inputs %}
-{%- if input["fluid_name"] in kernel_args %}
-{{input["fluid_name"] | to_opmaker_name_cstr}}{{", " if not loop.last}}
+{%- if input["name"] in kernel_args %}
+{{input["name"] | to_opmaker_name_cstr}}{{", " if not loop.last}}
 {%- endif %}
 {%- endfor %}
 }
@@ -219,8 +219,8 @@ paddle::small_vector<const char*> inputs {
 
 {% macro get_an_attr(attr, kernel_args) %}{# inline #}
 {% set typename = attr["typename"] %}
-{%- if attr["fluid_name"] in kernel_args %}
-{% set name = attr["fluid_name"] %}
+{%- if attr["name"] in kernel_args %}
+{% set name = attr["name"] %}
 {% if typename is scalar %}{# scalar correspond to a dispensable input and an attr in opmaker #}
 attrs.emplace_back(ctx.HasInput("{{attr | to_scalar_tensor_name}}") ? "{{attr | to_scalar_tensor_name}}" : "{{name}}");
 {%- elif typename == "IntArray" %}
@@ -251,7 +251,7 @@ attrs.emplace_back("{{name}}");
 {% macro get_output_list(outputs, kernel_args) %}{# inline #}
 paddle::small_vector<const char*> outputs {
 {%- for output in outputs %}
-{{output["fluid_name"] | to_opmaker_name_cstr}}{{", " if not loop.last}}
+{{output["name"] | to_opmaker_name_cstr}}{{", " if not loop.last}}
 {%- endfor %}
 }
 {%- endmacro %}
@@ -263,7 +263,7 @@ phi::KernelKey GetExpectedKernelType(
 {%if kernel["data_type"] is not none %}{# data type ---------------------------------#}
   {% if kernel["data_type"]["candidates"] | length == 1 %}
     {% set data_type_arg = kernel["data_type"]["candidates"][0] %}
-    {% set inputs = op["inputs"] | map(attribute="fluid_name") | list %}
+    {% set inputs = op["inputs"] | map(attribute="name") | list %}
     {% if data_type_arg in inputs %}
   auto data_type = framework::OperatorWithKernel::IndicateVarDataType(ctx, {{data_type_arg | to_opmaker_name}});
       {% if kernel["data_type"]["to_complex_flag"][0] %}
@@ -319,8 +319,9 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERER({{op["op_name"] | to_pascal_case}}NoNeedBuff
 {% endif %}
 {% endmacro%}
 
-{% macro register_op_with_components(op) %}
+{% macro register_op_with_components(op, op_dict) %}
 {% set name = op["op_name"] %}
+{% set phi_name = op["name"] %}
 REGISTER_OPERATOR({{name}}, ops::{{name | to_pascal_case}}Op,
 {% if not "forward" in op %}{# it is a forward op #}
                   ops::{{name | to_pascal_case}}OpMaker,
@@ -336,8 +337,8 @@ REGISTER_OPERATOR({{name}}, ops::{{name | to_pascal_case}}Op,
 {% if op is supports_inplace %}{# inplace#}
                   ops::{{name | to_pascal_case}}InplaceInferer,
 {% endif %}
-{% if "backward_composite" in op and op["backward_composite"] is not none %}
-                  ops::{{op["backward_composite"] | to_composite_grad_opmaker_name}},
+{% if "phi_backward" in op and  op["phi_backward"] is not none and "composite" in op_dict[op["phi_backward"]] %}
+                  ops::{{op["phi_backward"] | to_composite_grad_opmaker_name}},
 {% endif %}
 {% if op is supports_no_need_buffer %}{# no_need_buffer #}
                   ops::{{name | to_pascal_case}}NoNeedBufferVarInferer,
@@ -390,12 +391,12 @@ REGISTER_OP_VERSION({{name}})
 {# --------------------------------------- backward op maker ---------------------------------------------- #}
 {% macro backward_op_maker(op, forward_op ) %}
   {% set name = op["op_name"] %}
-  {% set forward_input_names = op["forward"]["inputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_output_names = op["forward"]["outputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_attr_names = op["forward"]["attrs"] | map(attribute="fluid_name") | list %}
-  {% set forward_input_orig_names = forward_op["inputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_output_orig_names = forward_op["outputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_attr_orig_names = forward_op["attrs"] | map(attribute="fluid_name") | list %}
+  {% set forward_input_names = op["forward"]["inputs"] | map(attribute="name") | list %}
+  {% set forward_output_names = op["forward"]["outputs"] | map(attribute="name") | list %}
+  {% set forward_attr_names = op["forward"]["attrs"] | map(attribute="name") | list %}
+  {% set forward_input_orig_names = forward_op["inputs"] | map(attribute="name") | list %}
+  {% set forward_output_orig_names = forward_op["outputs"] | map(attribute="name") | list %}
+  {% set forward_attr_orig_names = forward_op["attrs"] | map(attribute="name") | list %}
 template <typename T>
 class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T> {
  public:
@@ -406,8 +407,8 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
     grad_op->SetType("{{name}}");
 
   {% for input in op["inputs"] %}
-    grad_op->SetInput({{input["fluid_name"] | to_opmaker_name}}, this->{{extract_input_from_forward(
-      input["fluid_name"],
+    grad_op->SetInput({{input["name"] | to_opmaker_name}}, this->{{extract_input_from_forward(
+      input["name"],
       forward_input_names,
       forward_output_names,
       forward_input_orig_names,
@@ -415,8 +416,8 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
   {% endfor %}
 
   {% for output in op["outputs"] %}
-    grad_op->SetOutput({{output["fluid_name"] | to_opmaker_name}}, this->{{extract_output_from_forward(
-      output["fluid_name"],
+    grad_op->SetOutput({{output["name"] | to_opmaker_name}}, this->{{extract_output_from_forward(
+      output["name"],
       forward_input_names,
       forward_output_names,
       forward_input_orig_names,
@@ -426,7 +427,7 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
 
     grad_op->SetAttrMap(this->Attrs());
   {% for attr in op["attrs"] %}
-    {% set attr_name = attr["fluid_name"] %}
+    {% set attr_name = attr["name"] %}
     {% if attr_name in forward_attr_names %}
       {% if attr["typename"] == "IntArray" %}
         {% if 'tensor_name' in attr or 'manual_flag' not in attr %}
@@ -454,12 +455,12 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
 
 {% macro backward_op_reused_maker(bw_op, forward_op, invoke_op) %}
   {% set name = bw_op["op_name"] %}
-  {% set forward_input_names = bw_op["forward"]["inputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_output_names = bw_op["forward"]["outputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_attr_names = bw_op["forward"]["attrs"] | map(attribute="fluid_name") | list %}
-  {% set forward_input_orig_names = forward_op["inputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_output_orig_names = forward_op["outputs"] | map(attribute="fluid_name") | list %}
-  {% set forward_attr_orig_names = forward_op["attrs"] | map(attribute="fluid_name") | list %}
+  {% set forward_input_names = bw_op["forward"]["inputs"] | map(attribute="name") | list %}
+  {% set forward_output_names = bw_op["forward"]["outputs"] | map(attribute="name") | list %}
+  {% set forward_attr_names = bw_op["forward"]["attrs"] | map(attribute="name") | list %}
+  {% set forward_input_orig_names = forward_op["inputs"] | map(attribute="name") | list %}
+  {% set forward_output_orig_names = forward_op["outputs"] | map(attribute="name") | list %}
+  {% set forward_attr_orig_names = forward_op["attrs"] | map(attribute="name") | list %}
 template <typename T>
 class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T> {
  public:
@@ -470,7 +471,7 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
     grad_op->SetType("{{invoke_op["func"]}}");
 
   {% for input in invoke_op["inputs"] %}
-    grad_op->SetInput({{input["fluid_name"] | to_opmaker_name}}, this->{{extract_input_from_forward(
+    grad_op->SetInput({{input["name"] | to_opmaker_name}}, this->{{extract_input_from_forward(
       input["value"],
       forward_input_names,
       forward_output_names,
@@ -479,7 +480,7 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
   {% endfor %}
 
   {% for output in invoke_op["outputs"] %}
-    grad_op->SetOutput({{output["fluid_name"] | to_opmaker_name}}, this->{{extract_output_from_forward(
+    grad_op->SetOutput({{output["name"] | to_opmaker_name}}, this->{{extract_output_from_forward(
       output["value"],
       forward_input_names,
       forward_output_names,
@@ -489,49 +490,42 @@ class {{name | to_pascal_case}}OpMaker : public framework::SingleGradOpMaker<T>
   {% endfor %}
 
   {% for attr in invoke_op["attrs"] %}
-    grad_op->SetAttr("{{attr["fluid_name"]}}", {{attr["value"]}});
+    grad_op->SetAttr("{{attr["name"]}}", {{attr["value"]}});
   {% endfor %}
   }
 };
 {% endmacro %}
 
-{% macro composite_grad_op_maker(backward_op) %}
-  {% set op_name = backward_op["op_name"] %}
-  {% set inputs = backward_op["inputs"] | to_variable_names("name")%}
-  {% set input_dict = backward_op["input_dict"] %}
-  {% set fluid_inputs = backward_op["inputs"] | to_variable_names("fluid_name")%}
-  {% set forward_fluid_inputs = backward_op["forward"]["inputs"] | to_variable_names("fluid_name")%}
-  {% set forward_fluid_outputs = backward_op["forward"]["outputs"] | to_variable_names("fluid_name")%}
-  {% set attrs = backward_op["attrs"] | to_variable_names("name") %}
-  {% set fluid_attrs = backward_op["attrs"] | to_variable_names("fluid_name") %}
-  {% set attr_dict = backward_op["attr_dict"] %}
-  {% set outputs = backward_op["outputs"] | to_variable_names("name")%}
-  {% set output_dict = backward_op["output_dict"] %}
-  {% set fluid_outputs = backward_op["outputs"] | to_variable_names("fluid_name")%}
-  {% set composite_func_info = backward_op["composite"] %}
-class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradOpMakerBase {
+{% macro composite_grad_op_maker(composite_op_dict) %}
+  {% set op_name = composite_op_dict["name"] %}
+class {{op_name | to_composite_grad_opmaker_name}} : public prim::GradCompositeOpMakerBase {
  public:
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
+  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
   void Apply() override {
     //get inputs
-{{construct_composite_input(inputs, fluid_inputs, forward_fluid_inputs, forward_fluid_outputs, input_dict)}}
+{{construct_composite_input(composite_op_dict)}}
     //get attr
-{{construct_composite_attr(attrs, fluid_attrs, attr_dict)}}
+{{construct_composite_attr(composite_op_dict)}}
     //get output
-{{construct_composite_output(outputs, fluid_outputs, output_dict)}}
+{{construct_composite_output(composite_op_dict)}}
     //get output ptr
-{{construct_composite_output_ptr(outputs, output_dict)}}
+{{construct_composite_output_ptr(composite_op_dict)}}
     //get output orginal name
-{{get_composite_output_orginal_name(outputs, output_dict)}}
+{{get_composite_output_orginal_name(composite_op_dict)}}
     //call composite backward func
-{{call_composite_backward_api(composite_func_info)}}
+{{call_composite_backward_api(composite_op_dict)}}
     //recover output name
-{{recover_composite_output_name(outputs)}}
+{{recover_composite_output_name(composite_op_dict)}}
   }
 };
 {%- endmacro %}
 
-{% macro construct_composite_input(inputs, fluid_inputs, forward_fluid_inputs, forward_fluid_outputs, input_dict) %}
+{% macro construct_composite_input(composite_op_dict) %}
+  {% set inputs = composite_op_dict["composite"]["phi_inputs"] %}
+  {% set input_dict = composite_op_dict["input_dict"] %}
+  {% set fluid_inputs = composite_op_dict["composite"]["fluid_inputs"] %}
+  {% set forward_fluid_inputs = composite_op_dict["forward"]["inputs"] | map(attribute="name") | list %}
+  {% set forward_fluid_outputs = composite_op_dict["forward"]["outputs"] | map(attribute="name") | list %}
   {% set inputs_length = inputs | length %}
   {% for i in range(inputs_length) %}
     {% set input_typename = input_dict[inputs[i]]["typename"] %}
@@ -540,13 +534,13 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
       {% if input_typename == "Tensor" %}
         {% if input_optional_flag == True %}
     paddle::optional<paddle::experimental::Tensor> {{inputs[i]}} = this->GetOptionalSingleForwardInput("{{fluid_inputs[i]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     paddle::experimental::Tensor {{inputs[i]}} = this->GetSingleForwardInput("{{fluid_inputs[i]}}");
         {% endif %}
       {% elif input_typename == "Tensor[]" %}
         {% if input_optional_flag == True %}
     std::vector<paddle::optional<paddle::experimental::Tensor>> {{inputs[i]}} = this->GetOptionalMultiForwardInput("{{fluid_inputs[i]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     std::vector<paddle::experimental::Tensor> {{inputs[i]}} = this->GetMultiForwardInput("{{fluid_inputs[i]}}");
         {% endif %}
       {% endif %}
@@ -554,13 +548,13 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
       {% if input_typename == "Tensor" %}
         {% if input_optional_flag == True %}
     paddle::optional<paddle::experimental::Tensor> {{inputs[i]}} = this->GetOptionalSingleForwardOutput("{{fluid_inputs[i]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     paddle::experimental::Tensor {{inputs[i]}} = this->GetSingleForwardOutput("{{fluid_inputs[i]}}");
         {% endif %}
       {% elif input_typename == "Tensor[]" %}
         {% if input_optional_flag == True %}
     std::vector<paddle::optional<paddle::experimental::Tensor>> {{inputs[i]}} = this->GetOptionalMultiForwardOutput("{{fluid_inputs[i]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     std::vector<paddle::experimental::Tensor> {{inputs[i]}} = this->GetMultiForwardOutput("{{fluid_inputs[i]}}");
         {% endif %}
       {% endif %}
@@ -568,13 +562,13 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
       {% if input_typename == "Tensor" %}
         {% if input_optional_flag == True %}
     paddle::optional<paddle::experimental::Tensor> {{inputs[i]}} = this->GetOptionalSingleOutputGrad("{{fluid_inputs[i][:-5]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     paddle::experimental::Tensor {{inputs[i]}} = this->GetSingleOutputGrad("{{fluid_inputs[i][:-5]}}");
         {% endif %}
       {% elif input_typename == "Tensor[]" %}
         {% if input_optional_flag == True %}
     std::vector<paddle::optional<paddle::experimental::Tensor>> {{inputs[i]}} = this->GetOptionalMultiOutputGrad("{{fluid_inputs[i][:-5]}}");
-        {% else %}
+        {% elif input_optional_flag == False %}
     std::vector<paddle::experimental::Tensor> {{inputs[i]}} = this->GetMultiOutputGrad("{{fluid_inputs[i][:-5]}}");
         {%- endif %}
       {%- endif %}
@@ -582,18 +576,24 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
   {%- endfor %}
 {%- endmacro %}
 
-{% macro construct_composite_attr(attrs, fluid_attrs, attr_dict) %}
+{% macro construct_composite_attr(composite_op_dict) %}
+  {% set attrs = composite_op_dict["composite"]["phi_attrs"] %}
+  {% set fluid_attrs = composite_op_dict["composite"]["fluid_attrs"] %}
+  {% set fluid_attrs_dict = composite_op_dict["attr_dict"] %}
   {% set attrs_length = attrs | length %}
   {% for i in range(attrs_length) %}
-    {% set attrs_data_type = attr_dict[attrs[i]]["typename"] | to_op_attr_type %}
-    const {{attrs_data_type}} {{attrs[i]}} = this->Attr<{{attrs_data_type}}>("{{fluid_attrs[i]}}");
+    {% set attrs_data_type = fluid_attrs_dict[fluid_attrs[i]]["typename"] | to_op_attr_type %}
+    {{attrs_data_type}} {{attrs[i]}} = this->Attr<{{attrs_data_type}}>("{{fluid_attrs[i]}}");
   {% endfor %}
 {%- endmacro %}
 
-{% macro construct_composite_output(outputs, fluid_outputs, output_dict) %}
+{% macro construct_composite_output(composite_op_dict) %}
+  {% set outputs = composite_op_dict["composite"]["phi_outputs"] %}
+  {% set fluid_outputs = composite_op_dict["composite"]["fluid_outputs"] %}
+  {% set outputs_dict = composite_op_dict["output_dict"] %}
   {% set outputs_length = outputs | length %}
   {% for i in range(outputs_length) %}
-    {% set output_typename = output_dict[outputs[i]]["typename"] %}
+    {% set output_typename = outputs_dict[outputs[i]]["typename"] %}
     {% if output_typename == "Tensor" %}
     paddle::experimental::Tensor {{outputs[i] + "_t"}} = this->GetSingleInputGrad("{{fluid_outputs[i][:-5]}}");
     {% elif output_typename == "Tensor[]" %}
@@ -602,10 +602,12 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
   {%- endfor %}
 {%- endmacro %}
 
-{% macro construct_composite_output_ptr(outputs, output_dict) %}
+{% macro construct_composite_output_ptr(composite_op_dict) %}
+  {% set outputs = composite_op_dict["composite"]["phi_outputs"] %}
+  {% set outputs_dict = composite_op_dict["output_dict"] %}
   {% set outputs_length = outputs | length %}
   {% for i in range(outputs_length) %}
-    {% set output_typename = output_dict[outputs[i]]["typename"] %}
+    {% set output_typename = outputs_dict[outputs[i]]["typename"] %}
     {% if output_typename == "Tensor" %}
     paddle::experimental::Tensor* {{outputs[i]}} = this->GetOutputPtr(&{{outputs[i]+ "_t"}});
     {% elif output_typename == "Tensor[]" %}
@@ -618,10 +620,12 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
   {%- endfor %}
 {%- endmacro %}
 
-{% macro get_composite_output_orginal_name(outputs, output_dict) %}
+{% macro get_composite_output_orginal_name(composite_op_dict) %}
+  {% set outputs = composite_op_dict["composite"]["phi_outputs"] %}
+  {% set outputs_dict = composite_op_dict["output_dict"] %}
   {% set outputs_length = outputs | length %}
   {% for i in range(outputs_length) %}
-    {% set output_typename = output_dict[outputs[i]]["typename"] %}
+    {% set output_typename = outputs_dict[outputs[i]]["typename"] %}
     {% if output_typename == "Tensor" %}
     std::string {{outputs[i] + "_name"}} = this->GetOutputName({{outputs[i] + "_t"}});
     {% elif output_typename == "Tensor[]" %}
@@ -630,12 +634,13 @@ class {{op_name | to_composite_grad_opmaker_name}} : public prim::CompositeGradO
   {%- endfor %}
 {%- endmacro %}
 
-{% macro call_composite_backward_api(composite_func_info) %}
-    VLOG(3) << "Runing {{composite_func_info["func_name"]}} composite func";
-    prim::{{composite_func_info["func_name"]}}<prim::DescTensor>({{composite_func_info["func_args"]}});
+{% macro call_composite_backward_api(composite_op_dict) %}
+    VLOG(3) << "Runing {{composite_op_dict["composite"]["func_name"]}} composite func";
+    prim::{{composite_op_dict["composite"]["func_name"]}}<prim::DescTensor>({{composite_op_dict["composite"]["func_args"]}});
 {%- endmacro %}
 
-{% macro recover_composite_output_name(outputs) %}
+{% macro recover_composite_output_name(composite_op_dict) %}
+  {% set outputs = composite_op_dict["composite"]["phi_outputs"] %}
   {% set outputs_length = outputs | length %}
   {% for i in range(outputs_length) %}
     this->RecoverOutputName({{outputs[i] + "_t"}}, {{outputs[i] + "_name"}});

paddle/fluid/prim/tests/test_static_prim.cc

@@ -135,9 +135,9 @@ struct TestBaseProgram {
   int idx_{0};
 };
 
-class TestGradCompositeGradMaker : public CompositeGradOpMakerBase {
+class TestGradCompositeGradMaker : public GradCompositeOpMakerBase {
  public:
-  using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
+  using prim::GradCompositeOpMakerBase::GradCompositeOpMakerBase;
   void Apply() override {}
 };
 

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

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