Revert "Prim api gen (#49654)"

This reverts commit 813e27c9.

paddle/fluid/prim/api/.gitignore

-generated/prim_api/eager_prim_api.cc
-generated/prim_api/tmp_eager_prim_api.cc
-generated/prim_api/*.h

paddle/fluid/prim/api/CMakeLists.txt

-add_subdirectory(auto_code_generated)
 add_subdirectory(manual)
-add_subdirectory(generated)
-
 if(NOT (NOT WITH_PYTHON AND ON_INFER))
   cc_library(
     prim_api

paddle/fluid/prim/api/all.h

@@ -13,6 +13,6 @@
 // limitations under the License.
 
 #pragma once
-#include "paddle/fluid/prim/api/generated/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/backward/composite_backward_api.h"
+#include "paddle/fluid/prim/api/manual/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/utils/utils.h"

paddle/fluid/prim/api/auto_code_generated/CMakeLists.txt

-set(api_yaml_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/operators/generator/parsed_ops/ops.parsed.yaml"
-)
-set(legacy_api_yaml_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/operators/generator/parsed_ops/legacy_ops.parsed.yaml"
-)
-set(tmp_eager_prim_api_cc_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/prim/api/generated/prim_api/tmp_eager_prim_api.cc"
-)
-set(tmp_prim_api_h_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/prim/api/generated/prim_api/tmp_prim_api.h"
-)
-set(eager_prim_api_cc_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/prim/api/generated/prim_api/eager_prim_api.cc"
-)
-set(prim_api_h_path
-    "${PADDLE_SOURCE_DIR}/paddle/fluid/prim/api/generated/prim_api/prim_api.h")
-set(prim_api_gen_file
-    ${PADDLE_SOURCE_DIR}/paddle/fluid/prim/api/auto_code_generated/prim_gen.py)
-
-message("prim api Code gen")
-execute_process(
-  WORKING_DIRECTORY
-    ${CMAKE_SOURCE_DIR}/paddle/fluid/prim/api/auto_code_generated
-  COMMAND
-    ${PYTHON_EXECUTABLE} ${prim_api_gen_file} --api_yaml_path
-    ${legacy_api_yaml_path} ${api_yaml_path} --prim_api_header_path
-    ${tmp_prim_api_h_path} --eager_prim_api_source_path
-    ${tmp_eager_prim_api_cc_path}
-  RESULT_VARIABLE _result)
-if(${_result})
-  message(FATAL_ERROR "prim api genrate failed, exiting.")
-endif()
-execute_process(COMMAND ${CMAKE_COMMAND} -E copy_if_different
-                        ${tmp_prim_api_h_path} ${prim_api_h_path})
-execute_process(COMMAND ${CMAKE_COMMAND} -E copy_if_different
-                        ${tmp_eager_prim_api_cc_path} ${eager_prim_api_cc_path})
-message("copy tmp_xxx_prim_api to xxx_prim_api")

paddle/fluid/prim/api/auto_code_generated/prim_base.py

-# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-
-# prim api list
-white_ops_list = [
-    "pow",
-    "scale",
-    "multiply",
-    "unsqueeze",
-    "expand",
-    "full",
-    "reshape",
-    "divide",
-    "sum",
-    "exp",
-]
-
-inplace_out_type_map = {
-    "Tensor": "Tensor&",
-    "std::vector<Tensor>": "std::vector<Tensor>&",
-}
-
-inplace_optional_out_type_map = {
-    "Tensor": "paddle::optional<Tensor>&",
-    "std::vector<Tensor>": "paddle::optional<std::vector<Tensor>>&",
-}
-
-
-class BaseAPI:
-    def __init__(self, api_item_yaml):
-        # self.api = api_item_yaml['op']
-        self.api = api_item_yaml['name']
-
-        self.is_prim_api = False
-        if api_item_yaml['name'] in white_ops_list:
-            self.is_prim_api = True
-
-        #######################################
-        # inputs:
-        #     names : [], list of input names
-        #     input_info : {input_name : type}
-        # attrs:
-        #     names : [], list of attribute names
-        #     attr_info : { attr_name : (type, default_values)}
-        # outputs:
-        #     names : [], list of output names
-        #     types : [], list of output types
-        #     out_size_expr : [], expression for getting size of vector<Tensor>
-        ########################################
-        if self.is_prim_api:
-            (
-                self.inputs,
-                self.attrs,
-                self.outputs,
-                self.optional_vars,
-            ) = self.parse_args(self.api, api_item_yaml)
-
-            self.inplace_map = api_item_yaml['inplace']
-
-    def get_api_func_name(self):
-        return self.api
-
-    # def is_inplace(self):
-    #     if self.inplace_map
-    #         return True
-    #     return False
-
-    def get_input_tensor_args(self, inplace_flag=False):
-        input_args = []
-        inplace_type_map = {
-            "const Tensor&": "Tensor&",
-            "const paddle::optional<Tensor>&": "paddle::optional<Tensor>&",
-            "const std::vector<Tensor>&": "std::vector<Tensor>&",
-            "const paddle::optional<std::vector<Tensor>>&": "paddle::optional<std::vector<Tensor>>&",
-        }
-        for name in self.inputs['names']:
-            name = name.split('@')[0]
-            if inplace_flag and name in self.inplace_map.values():
-                input_args.append(
-                    inplace_type_map[self.inputs['input_info'][name]]
-                    + ' '
-                    + name
-                )
-            else:
-                input_args.append(self.inputs['input_info'][name] + ' ' + name)
-        return input_args
-
-    def get_declare_args(self, inplace_flag=False):
-        declare_args = self.get_input_tensor_args(inplace_flag)
-        for name in self.attrs['names']:
-            default_value = ''
-            if self.attrs['attr_info'][name][1] is not None:
-                default_value = ' = ' + self.attrs['attr_info'][name][1]
-            declare_args.append(
-                self.attrs['attr_info'][name][0] + ' ' + name + default_value
-            )
-
-        return ", ".join(declare_args)
-
-    def get_declare_args_nodefault(self, inplace_flag=False):
-        declare_args = self.get_input_tensor_args(inplace_flag)
-        for name in self.attrs['names']:
-            declare_args.append(self.attrs['attr_info'][name][0] + ' ' + name)
-
-        return ", ".join(declare_args)
-
-    def get_return_type(self, inplace_flag=False):
-        out_type_list = []
-        for i, out_type in enumerate(self.outputs['types']):
-            out_name = self.outputs['names'][i].split('@')[0]
-            if inplace_flag and out_name in self.inplace_map:
-                if self.inplace_map[out_name] in self.optional_vars:
-                    out_type_list.append(
-                        inplace_optional_out_type_map[out_type]
-                    )
-                else:
-                    out_type_list.append(inplace_out_type_map[out_type])
-            else:
-                out_type_list.append(out_type)
-        if len(out_type_list) == 1:
-            return out_type_list[0]
-        else:
-            return "std::tuple<" + ", ".join(out_type_list) + ">"
-
-    def parse_args(self, api_name, api_item_yaml):
-        optional_vars = []
-        for input_dict in api_item_yaml['inputs']:
-            if input_dict['optional']:
-                optional_vars.append(input_dict['name'])
-
-        inputs, attrs = self.parse_input_and_attr(
-            api_item_yaml['inputs'], api_item_yaml['attrs']
-        )
-
-        output_type_list, output_names, out_size_expr = self.parse_output(
-            api_item_yaml['outputs']
-        )
-        return (
-            inputs,
-            attrs,
-            {
-                'names': output_names,
-                'types': output_type_list,
-                'out_size_expr': out_size_expr,
-            },
-            optional_vars,
-        )
-
-    def parse_input_and_attr(self, inputs_list, attrs_list):
-        input_types_map = {
-            'Tensor': 'const Tensor&',
-            'Tensor[]': 'const std::vector<Tensor>&',
-        }
-        attr_types_map = {
-            'IntArray': 'const IntArray&',
-            'Scalar': 'const Scalar&',
-            'Scalar(int)': 'const Scalar&',
-            'Scalar(int64_t)': 'const Scalar&',
-            'Scalar(float)': 'const Scalar&',
-            'Scalar(dobule)': 'const Scalar&',
-            'Scalar[]': 'const std::vector<phi::Scalar>&',
-            'int': 'int',
-            'int32_t': 'int32_t',
-            'int64_t': 'int64_t',
-            'long': 'long',
-            'size_t': 'size_t',
-            'float': 'float',
-            'float[]': 'const std::vector<float>&',
-            'double': 'double',
-            'bool': 'bool',
-            'bool[]': 'const std::vector<bool>&',
-            'str': 'const std::string&',
-            'str[]': 'const std::vector<std::string>&',
-            'Place': 'const Place&',
-            'DataLayout': 'DataLayout',
-            'DataType': 'DataType',
-            'int64_t[]': 'const std::vector<int64_t>&',
-            'int[]': 'const std::vector<int>&',
-        }
-        optional_types_trans = {
-            'Tensor': 'const paddle::optional<Tensor>&',
-            'Tensor[]': 'const paddle::optional<std::vector<Tensor>>&',
-            'int': 'paddle::optional<int>',
-            'int32_t': 'paddle::optional<int32_t>',
-            'int64_t': 'paddle::optional<int64_t>',
-            'float': 'paddle::optional<float>',
-            'double': 'paddle::optional<double>',
-            'bool': 'paddle::optional<bool>',
-            'Place': 'paddle::optional<const Place&>',
-            'DataLayout': 'paddle::optional<DataLayout>',
-            'DataType': 'paddle::optional<DataType>',
-        }
-
-        inputs = {'names': [], 'input_info': {}}
-        for input_dict in inputs_list:
-            inputs['names'].append(input_dict['name'])
-            if input_dict['optional']:
-                inputs['input_info'][input_dict['name']] = optional_types_trans[
-                    input_dict['typename']
-                ]
-            else:
-                inputs['input_info'][input_dict['name']] = input_types_map[
-                    input_dict['typename']
-                ]
-
-        attrs = {'names': [], 'attr_info': {}}
-        for attr_dict in attrs_list:
-            attrs['names'].append(attr_dict['name'])
-            if 'default_value' in attr_dict.keys():
-                default_value = attr_dict['default_value']
-            else:
-                default_value = None
-
-            if 'optional' in attr_dict.keys():
-                attrs['attr_info'][attr_dict['name']] = (
-                    optional_types_trans[attr_dict['typename']],
-                    default_value,
-                )
-            else:
-                attrs['attr_info'][attr_dict['name']] = (
-                    attr_types_map[attr_dict['typename']],
-                    default_value,
-                )
-        return inputs, attrs
-
-    def parse_output(self, outputs_list):
-
-        out_type_list = []
-        out_name_list = []
-        out_size_expr_list = []
-        for output_dict in outputs_list:
-            if output_dict['intermediate']:
-                continue
-            out_type_list.append(output_dict['typename'])
-            out_name_list.append(output_dict['name'])
-            if 'size' in output_dict.keys():
-                out_size_expr_list.append(output_dict['size'])
-            else:
-                out_size_expr_list.append(None)
-        return out_type_list, out_name_list, out_size_expr_list
-
-
-class EagerPrimAPI(BaseAPI):
-    def __init__(self, api_item_yaml):
-        super().__init__(api_item_yaml)
-
-    def get_api__func_name(self):
-        api_func_name = self.api
-        # if self.is_inplace:
-        #     if api_func_name[-1] != '_':
-        #         api_func_name += '_'
-        # print("after api name", api_func_name)
-        return api_func_name
-
-    def gene_prim_api_declaration(self):
-        api_declaration = ""
-        api_func_name = self.get_api__func_name()
-        if api_func_name[-1] != '_':
-            api_declaration = f"""
-template <typename T>
-{self.get_return_type()} {api_func_name}({self.get_declare_args()});
-"""
-        else:
-            api_declaration = (
-                api_declaration
-                + f"""
-template <typename T>
-{self.get_return_type(inplace_flag=True)} {api_func_name}({self.get_declare_args(inplace_flag=True)});
-"""
-            )
-
-        return api_declaration
-
-    def get_ad_func_input_args(self, inplace_flag=False):
-        input_args = []
-        for name in self.inputs['names']:
-            name = name.split('@')[0]
-            if inplace_flag and name in self.inplace_map.values():
-                input_args.append(name)
-            else:
-                input_args.append(name)
-        return input_args
-
-    def get_ad_func_args(self, inplace_flag=False):
-        ad_func_args = self.get_ad_func_input_args(inplace_flag)
-        for name in self.attrs['names']:
-            default_value = ''
-            if self.attrs['attr_info'][name][1] is not None:
-                default_value = ' = ' + self.attrs['attr_info'][name][1]
-            ad_func_args.append(name)
-
-        ad_func_args_str = ", ".join(ad_func_args)
-        return ad_func_args_str
-
-    def gene_ad_func_call(self):
-        api_func_name = self.get_api__func_name()
-
-        dygraph_ad_func_name = '::' + api_func_name + '_ad_func'
-        dygraph_ad_func_parameters = self.get_ad_func_args()
-
-        ad_func_call_str = f"""
-VLOG(4) << "Eager Prim API {api_func_name}_ad_func call";
-return {dygraph_ad_func_name}({dygraph_ad_func_parameters});
-"""
-        # print("ad_func_call_str: ", ad_func_call_str)
-        return ad_func_call_str
-
-    def gene_eager_prim_api_code(self):
-        api_code = ""
-        indent = "  "
-        api_func_name = self.get_api__func_name()
-        template = '<Tensor>'
-        # func decalaration
-        if api_func_name[-1] != '_':
-            api_code = f"""
-template <>
-{self.get_return_type()} {api_func_name}{template}({self.get_declare_args_nodefault()})
-"""
-        else:
-            api_code = f"""
-template <>
-{self.get_return_type(inplace_flag=True)} {api_func_name}{template}({self.get_declare_args_nodefault(inplace_flag=True)})
-"""
-        # func code
-
-        api_code = api_code + '{'
-        api_code += f"""{self.gene_ad_func_call()}"""
-        api_code += '}' + '\n'
-
-        return api_code

paddle/fluid/prim/api/auto_code_generated/prim_gen.py

-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import argparse
-
-import yaml
-from prim_base import EagerPrimAPI
-
-
-def header_include():
-    return """
-#include "paddle/phi/common/int_array.h"
-#include "paddle/phi/common/data_type.h"
-#include "paddle/phi/common/scalar.h"
-#include "paddle/phi/common/place.h"
-#include "paddle/utils/optional.h"
-"""
-
-
-def eager_source_include(header_file_path):
-    return """
-#include "paddle/fluid/eager/api/all.h"
-#include "paddle/fluid/eager/api/generated/eager_generated/forwards/dygraph_functions.h"
-#include "paddle/fluid/prim/api/generated/prim_api/prim_api.h"
-"""
-
-
-def api_namespace():
-    return (
-        """
-namespace paddle {
-namespace prim {
-""",
-        """
-using Tensor = paddle::experimental::Tensor;
-using Scalar = paddle::experimental::Scalar;
-using IntArray = paddle::experimental::IntArray;
-using DataType = paddle::experimental::DataType;
-""",
-        """
-}  // namespace prim
-}  // namespace paddle
-""",
-    )
-
-
-def generate_api(api_yaml_path, header_file_path, eager_prim_source_file_path):
-    apis = []
-
-    for each_api_yaml in api_yaml_path:
-        with open(each_api_yaml, 'r') as f:
-            api_list = yaml.load(f, Loader=yaml.FullLoader)
-            if api_list:
-                apis.extend(api_list)
-
-    header_file = open(header_file_path, 'w')
-    eager_prim_source_file = open(eager_prim_source_file_path, 'w')
-
-    namespace = api_namespace()
-
-    header_file.write("#pragma once\n")
-    header_file.write(header_include())
-    header_file.write(namespace[0])
-    header_file.write(namespace[1])
-    include_header_file = (
-        "#include paddle/fluid/prim/api/generated/prim_api/prim_api.h"
-    )
-    eager_prim_source_file.write(eager_source_include(include_header_file))
-    eager_prim_source_file.write(namespace[0])
-
-    for api in apis:
-        prim_api = EagerPrimAPI(api)
-        if prim_api.is_prim_api:
-            header_file.write(prim_api.gene_prim_api_declaration())
-            eager_prim_source_file.write(prim_api.gene_eager_prim_api_code())
-
-    header_file.write(namespace[2])
-    eager_prim_source_file.write(namespace[2])
-
-    header_file.close()
-    eager_prim_source_file.close()
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        description='Generate PaddlePaddle C++ API files'
-    )
-    parser.add_argument(
-        '--api_yaml_path',
-        help='path to api yaml file',
-        nargs='+',
-        default=['paddle/phi/api/yaml/ops.yaml'],
-    )
-
-    parser.add_argument(
-        '--prim_api_header_path',
-        help='output of generated prim_api header code file',
-        default='paddle/fluid/prim/api/generated/prim_api/prim_api.h',
-    )
-
-    parser.add_argument(
-        '--eager_prim_api_source_path',
-        help='output of generated eager_prim_api source code file',
-        default='paddle/fluid/prim/api/generated/prim_api/eager_prim_api.cc',
-    )
-
-    options = parser.parse_args()
-
-    api_yaml_path = options.api_yaml_path
-    prim_api_header_file_path = options.prim_api_header_path
-    eager_prim_api_source_file_path = options.eager_prim_api_source_path
-
-    generate_api(
-        api_yaml_path,
-        prim_api_header_file_path,
-        eager_prim_api_source_file_path,
-    )
-
-
-if __name__ == '__main__':
-    main()

paddle/fluid/prim/api/generated/CMakeLists.txt

-add_subdirectory(prim_api)

paddle/fluid/prim/api/manual/CMakeLists.txt

+add_subdirectory(prim_api)
 add_subdirectory(utils)

paddle/fluid/prim/api/manual/backward/composite_backward_api.h

@@ -13,7 +13,6 @@
 // limitations under the License.
 
 #pragma once
-#include "paddle/fluid/prim/api/generated/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/utils/utils.h"
 #include "paddle/phi/common/int_array.h"

paddle/fluid/prim/api/manual/prim_api/eager_prim_api.cc

+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/eager/api/all.h"
+#include "paddle/fluid/eager/api/generated/eager_generated/forwards/dygraph_functions.h"
+#include "paddle/fluid/prim/api/manual/prim_api/prim_api.h"
+#include "paddle/phi/capi/include/wrapper_base.h"
+namespace paddle {
+namespace prim {
+template <>
+Tensor pow<Tensor>(const Tensor& x, const paddle::experimental::Scalar& y) {
+  return ::pow_ad_func(x, y);
+}
+
+template <>
+Tensor scale<Tensor>(const Tensor& x,
+                     const paddle::experimental::Scalar& scale,
+                     float bias,
+                     bool bias_after_scale) {
+  return ::scale_ad_func(x, scale, bias, bias_after_scale);
+}
+
+template <>
+Tensor multiply<Tensor>(const Tensor& x, const Tensor& y) {
+  return ::multiply_ad_func(x, y);
+}
+
+template <>
+Tensor expand<Tensor>(const Tensor& x, const IntArray& shape) {
+  return ::expand_ad_func(x, shape);
+}
+
+template <>
+Tensor unsqueeze<Tensor>(const Tensor& x, const IntArray& axis) {
+  return ::unsqueeze_ad_func(x, axis);
+}
+
+template <>
+Tensor divide<Tensor>(const Tensor& x, const Tensor& y) {
+  return ::divide_ad_func(x, y);
+}
+
+template <>
+Tensor full<Tensor>(paddle::experimental::IntArray shape,
+                    paddle::experimental::Scalar value,
+                    paddle::experimental::DataType dtype,
+                    paddle::platform::Place place) {
+  return ::full_ad_func(shape, value, dtype, place);
+}
+template <>
+Tensor sum<Tensor>(Tensor x, IntArray axis, DataType dtype, bool keepdim) {
+  return ::sum_ad_func(x, axis, dtype, keepdim);
+}
+
+template <>
+Tensor reshape<Tensor>(Tensor x, IntArray shape) {
+  return ::reshape_ad_func(x, shape);
+}
+
+template <>
+Tensor exp<Tensor>(const Tensor& x) {
+  return ::exp_ad_func(x);
+}
+
+template <typename T>
+Tensor expand(const Tensor& x, const IntArray& shape) {
+  return ::expand_ad_func(x, shape);
+}
+}  // namespace prim
+}  // namespace paddle

paddle/fluid/prim/api/manual/prim_api/prim_api.h

@@ -12,15 +12,56 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-// prim api which can't be generated
 #pragma once
-
-#include "paddle/phi/common/data_type.h"
 #include "paddle/phi/common/int_array.h"
-#include "paddle/phi/common/place.h"
 #include "paddle/phi/common/scalar.h"
 #include "paddle/utils/optional.h"
-
 namespace paddle {
-namespace prim {}  // namespace prim
+namespace prim {
+using Tensor = paddle::experimental::Tensor;
+using IntArray = paddle::experimental::IntArray;
+using Scalar = paddle::experimental::Scalar;
+
+template <typename T>
+Tensor pow(const Tensor& x, const Scalar& y);
+
+template <typename T>
+Tensor scale(const Tensor& X,
+             const Scalar& scale,
+             float bias,
+             bool bias_after_scale);
+
+template <typename T>
+Tensor multiply(const Tensor& x, const Tensor& y);
+
+template <typename T>
+Tensor expand(const Tensor& x, const IntArray& shape);
+
+template <typename T>
+Tensor unsqueeze(const Tensor& x, const IntArray& axis);
+
+template <typename T>
+Tensor divide(const Tensor& x, const Tensor& y);
+
+template <typename T>
+Tensor full(IntArray shape,
+            Scalar value,
+            DataType dtype = DataType::FLOAT32,
+            Place place = CPUPlace());
+
+template <typename T>
+Tensor sum(Tensor x,
+           IntArray axis = {},
+           DataType dtype = DataType::UNDEFINED,
+           bool keepdim = false);
+
+template <typename T>
+Tensor reshape(Tensor x, IntArray shape);
+
+template <typename T>
+Tensor expand(const Tensor& x, const IntArray& shape);
+
+template <typename T>
+Tensor exp(const Tensor& x);
+}  // namespace prim
 }  // namespace paddle

paddle/fluid/prim/api/generated/prim_api/static_prim_api.cc → paddle/fluid/prim/api/manual/prim_api/static_prim_api.cc

@@ -25,7 +25,6 @@
 #include "paddle/fluid/framework/program_desc.h"
 
 #include "paddle/fluid/framework/convert_utils.h"
-#include "paddle/fluid/prim/api/generated/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/prim_api/prim_api.h"
 #include "paddle/fluid/prim/api/manual/utils/utils.h"
 #include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
@@ -38,7 +37,7 @@ namespace paddle {
 namespace prim {
 
 template <>
-Tensor pow<DescTensor>(const Tensor& x, const Scalar& y) {
+Tensor pow<DescTensor>(const Tensor& x, const paddle::experimental::Scalar& y) {
   Tensor out = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
   framework::OpDesc* op = block->AppendOp();
@@ -56,7 +55,7 @@ Tensor pow<DescTensor>(const Tensor& x, const Scalar& y) {
 
 template <>
 Tensor scale<DescTensor>(const Tensor& x,
-                         const Scalar& scale,
+                         const paddle::experimental::Scalar& scale,
                          float bias,
                          bool bias_after_scale) {
   Tensor out = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
@@ -96,63 +95,63 @@ Tensor multiply<DescTensor>(const Tensor& x, const Tensor& y) {
 }
 
 template <>
-Tensor unsqueeze<DescTensor>(const Tensor& x, const IntArray& axis) {
+Tensor expand<DescTensor>(const Tensor& x, const IntArray& shape) {
   Tensor out = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
   framework::OpDesc* op = block->AppendOp();
-  op->SetType("unsqueeze2");
+  op->SetType("expand_v2");
   op->SetInput("X",
                {std::static_pointer_cast<prim::DescTensor>(x.impl())->Name()});
   op->SetOutput(
       "Out", {std::static_pointer_cast<prim::DescTensor>(out.impl())->Name()});
-  std::vector<int> new_shape(axis.GetData().begin(), axis.GetData().end());
-  op->SetAttr("axes", new_shape);
+  std::vector<int> new_shape(shape.GetData().begin(), shape.GetData().end());
+  op->SetAttr("shape", new_shape);
   op->CheckAttrs();
   op->InferVarType(block);
   return out;
 }
 
 template <>
-Tensor expand<DescTensor>(const Tensor& x, const IntArray& shape) {
+Tensor divide<DescTensor>(const Tensor& x, const Tensor& y) {
+  // Grad infershape
   Tensor out = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
   framework::OpDesc* op = block->AppendOp();
-  op->SetType("expand_v2");
+  op->SetType("elementwise_div");
   op->SetInput("X",
                {std::static_pointer_cast<prim::DescTensor>(x.impl())->Name()});
+  op->SetInput("Y",
+               {std::static_pointer_cast<prim::DescTensor>(y.impl())->Name()});
   op->SetOutput(
       "Out", {std::static_pointer_cast<prim::DescTensor>(out.impl())->Name()});
-  std::vector<int> new_shape(shape.GetData().begin(), shape.GetData().end());
-  op->SetAttr("shape", new_shape);
   op->CheckAttrs();
   op->InferVarType(block);
+  op->InferShape(*block);
   return out;
 }
 
 template <>
-Tensor divide<DescTensor>(const Tensor& x, const Tensor& y) {
-  // Grad infershape
+Tensor unsqueeze<DescTensor>(const Tensor& x, const IntArray& axis) {
   Tensor out = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
   framework::OpDesc* op = block->AppendOp();
-  op->SetType("elementwise_div");
+  op->SetType("unsqueeze2");
   op->SetInput("X",
                {std::static_pointer_cast<prim::DescTensor>(x.impl())->Name()});
-  op->SetInput("Y",
-               {std::static_pointer_cast<prim::DescTensor>(y.impl())->Name()});
   op->SetOutput(
       "Out", {std::static_pointer_cast<prim::DescTensor>(out.impl())->Name()});
+  std::vector<int> new_shape(axis.GetData().begin(), axis.GetData().end());
+  op->SetAttr("axes", new_shape);
   op->CheckAttrs();
   op->InferVarType(block);
-  op->InferShape(*block);
   return out;
 }
 
 template <>
-Tensor full<DescTensor>(const IntArray& shape,
-                        const Scalar& value,
-                        DataType dtype,
-                        const Place& place) {
+Tensor full<DescTensor>(paddle::experimental::IntArray shape,
+                        paddle::experimental::Scalar value,
+                        paddle::experimental::DataType dtype,
+                        paddle::platform::Place place) {
   // Grad infershape
   Tensor out = empty<DescTensor>({}, dtype, place);
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
@@ -160,8 +159,9 @@ Tensor full<DescTensor>(const IntArray& shape,
   op->SetType("fill_constant");
   op->SetAttr("shape", shape.GetData());
   PADDLE_ENFORCE_EQ(
-      ((dtype == DataType::FLOAT32) || (dtype == DataType::FLOAT64) ||
-       (dtype == DataType::FLOAT16)),
+      ((dtype == paddle::experimental::DataType::FLOAT32) ||
+       (dtype == paddle::experimental::DataType::FLOAT64) ||
+       (dtype == paddle::experimental::DataType::FLOAT16)),
       true,
       phi::errors::InvalidArgument(
           "We only support float32/float16 for full, but we got data type: %s",
@@ -177,9 +177,9 @@ Tensor full<DescTensor>(const IntArray& shape,
 }
 
 template <>
-Tensor sum<DescTensor>(const Tensor& x,
-                       const IntArray& axis,
-                       DataType dtype,
+Tensor sum<DescTensor>(Tensor x,
+                       paddle::experimental::IntArray axis,
+                       paddle::experimental::DataType dtype,
                        bool keepdim) {
   // Grad infershape
   Tensor out = empty<DescTensor>({}, dtype, paddle::Place());
@@ -204,7 +204,7 @@ Tensor sum<DescTensor>(const Tensor& x,
 }
 
 template <>
-Tensor reshape<DescTensor>(const Tensor& x, const IntArray& shape) {
+Tensor reshape<DescTensor>(Tensor x, paddle::experimental::IntArray shape) {
   // Grad infershape
   Tensor out = empty<DescTensor>({}, x.dtype(), paddle::Place());
   framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();