# 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 yaml import argparse from api_gen import ForwardAPI kernel_func_set = set() def get_wrapped_infermeta_name(api_name): return api_name.capitalize() + 'InferMeta' def gene_wrapped_infermeta_and_register(api): if api.is_base_api and not api.is_dygraph_api: register_code = f""" PD_REGISTER_INFER_META_FN({api.kernel['func'][0]}, phi::{api.infer_meta['func']});""" if api.infer_meta['param'] is not None: if api.kernel['func'][0] in kernel_func_set: return '', '', '' kernel_params = api.kernel['param'] if kernel_params is None: kernel_params = api.inputs['names'] + api.attrs['names'] if kernel_params == api.infer_meta['param']: return '', '', register_code assert len(api.infer_meta['param']) <= len(kernel_params), \ f"{api.api} api: Parameters error. The params of infer_meta should be a subset of kernel params." tensor_type_map = { 'const Tensor&': 'const MetaTensor&', 'const std::vector&': 'const std::vector&', 'Tensor': 'MetaTensor*', 'std::vector': 'std::vector', 'const paddle::optional&': 'const MetaTensor&' } wrapped_infermeta_name = get_wrapped_infermeta_name( api.kernel['func'][0]) args = [] for input_name in api.inputs['names']: if input_name in kernel_params: args.append( tensor_type_map[api.inputs['input_info'][input_name]] + ' ' + input_name) for attr_name in api.attrs['names']: if attr_name in kernel_params: args.append(api.attrs['attr_info'][attr_name][0] + ' ' + attr_name) for i, out_type in enumerate(api.outputs['types']): args.append(tensor_type_map[out_type] + ' ' + api.outputs['names'][i]) invoke_param = api.infer_meta['param'] invoke_param.extend(api.outputs['names']) declare_code = f""" void {wrapped_infermeta_name}({", ".join(args)}); """ defind_code = f""" void {wrapped_infermeta_name}({", ".join(args)}) {{ {api.infer_meta['func']}({", ".join(invoke_param)}); }} """ register_code = f""" PD_REGISTER_INFER_META_FN({api.kernel['func'][0]}, phi::{get_wrapped_infermeta_name(api.kernel['func'][0])});""" kernel_func_set.add(api.kernel['func'][0]) return declare_code, defind_code, register_code else: return '', '', register_code else: return '', '', '' def header_include(): return """ #include "paddle/phi/core/meta_tensor.h" #include "paddle/phi/common/scalar.h" #include "paddle/phi/common/int_array.h" """ def source_include(header_file_path): return f""" #include "{header_file_path}" #include "paddle/phi/core/infermeta_utils.h" #include "paddle/phi/infermeta/binary.h" #include "paddle/phi/infermeta/multiary.h" #include "paddle/phi/infermeta/nullary.h" #include "paddle/phi/infermeta/unary.h" #include "paddle/phi/infermeta/ternary.h" """ def api_namespace(): return (""" namespace phi { """, """ } // namespace phi """) def generate_wrapped_infermeta_and_register(api_yaml_path, header_file_path, 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') source_file = open(source_file_path, 'w') namespace = api_namespace() header_file.write("#pragma once\n") header_file.write(header_include()) header_file.write(namespace[0]) include_header_file = "paddle/phi/infermeta/generated.h" source_file.write(source_include(include_header_file)) source_file.write(namespace[0]) infermeta_register_code = '' for api in apis: api_item = ForwardAPI(api) declare_code, defind_code, register_code = gene_wrapped_infermeta_and_register( api_item) header_file.write(declare_code) source_file.write(defind_code) if infermeta_register_code.find(register_code) == -1: infermeta_register_code = infermeta_register_code + register_code header_file.write(namespace[1]) source_file.write(namespace[1]) source_file.write(infermeta_register_code) header_file.close() 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( '--wrapped_infermeta_header_path', help='output of generated wrapped_infermeta header code file', default='paddle/phi/infermeta/generated.h') parser.add_argument( '--wrapped_infermeta_source_path', help='output of generated wrapped_infermeta source code file', default='paddle/phi/infermeta/generated.cc') options = parser.parse_args() api_yaml_path = options.api_yaml_path header_file_path = options.wrapped_infermeta_header_path source_file_path = options.wrapped_infermeta_source_path generate_wrapped_infermeta_and_register(api_yaml_path, header_file_path, source_file_path) if __name__ == '__main__': main()