# 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. import os import yaml import argparse import re from api_base import BaseAPI, PREFIX_TENSOR_NAME class ForwardAPI(BaseAPI): def __init__(self, api_item_yaml): super(ForwardAPI, self).__init__(api_item_yaml) self.is_dygraph_api, self.intermediate_outs = self.parse_intermediate( api_item_yaml) def get_api_func_name(self): if self.is_dygraph_api: return self.api + '_intermediate' else: return self.api def parse_intermediate(self, api_item_yaml): if 'intermediate' in api_item_yaml: intermediate_outs = [ item.strip() for item in api_item_yaml['intermediate'].split(',') ] return True, intermediate_outs else: return False, [] def get_return_type(self, out_type_list): return out_type_list[0] if len( out_type_list) == 1 else "std::tuple<" + ",".join( out_type_list) + ">" def gene_return_type_code(self): if self.is_dygraph_api or len(self.intermediate_outs) == 0: return self.outputs['return_type'] else: return_out_list = [] for i, name in enumerate(self.outputs['names']): if name not in self.intermediate_outs: return_out_list.append(self.outputs['types'][i]) return return_out_list[0] if len( return_out_list) == 1 else "std::tuple<" + ",".join( return_out_list) + ">" def gene_return_code(self): if self.is_dygraph_api or len(self.intermediate_outs) == 0: return "api_output" else: return_out_list = [] for i, name in enumerate(self.outputs['names']): if name not in self.intermediate_outs: return_out_list.append(i) if len(return_out_list) == 1: return f"std::get<{return_out_list[0]}>(api_output)" else: selected_code = [ f"std::get<{i}>(api_output)" for i in return_out_list ] return '{' + ", ".join(selected_code) + '}' def gene_output(self, output_type_list, set_out_func, code_indent, inplace_flag=False): kernel_output = "" output_names = [] output_create = "" if len(output_type_list) == 1: kernel_output = 'kernel_out' output_names.append('kernel_out') inplace_assign = " = " + self.inplace_map[self.outputs['names'][ 0]] if inplace_flag and self.inplace_map is not None and self.outputs[ 'names'][0] in self.inplace_map else "" output_create = f""" {code_indent} {self.outputs['return_type']} api_output{inplace_assign}; {code_indent} auto kernel_out = {set_out_func}(kernel_backend, &api_output);""" if not inplace_flag and self.view_map is not None and self.outputs[ 'names'][0] in self.view_map: output_create = output_create + f""" {code_indent} kernel_out->ShareBufferWith(*{PREFIX_TENSOR_NAME}{self.view_map[self.outputs['names'][0]]}); {code_indent} kernel_out->ShareInplaceVersionCounterWith(*{PREFIX_TENSOR_NAME}{self.view_map[self.outputs['names'][0]]}); {code_indent} VLOG(3) << "Perform View between Output and Input Tensor, share allocation and inplace version.";""" elif len(output_type_list) > 1: output_create = f""" {code_indent} {self.outputs['return_type']} api_output;""" for i in range(len(output_type_list)): kernel_output = kernel_output + f'kernel_out_{i}, ' output_names.append(f'kernel_out_{i}') if inplace_flag and self.inplace_map is not None and self.outputs[ 'names'][i] in self.inplace_map: output_create = output_create + f""" {code_indent} std::get<{i}>(api_output) = {self.inplace_map[self.outputs['names'][i]]};""" output_create = output_create + f""" {code_indent} auto kernel_out_{i} = {set_out_func}(kernel_backend, &std::get<{i}>(api_output));""" if not inplace_flag and self.view_map is not None and self.outputs[ 'names'][i] in self.view_map: output_create = output_create + f""" {code_indent} kernel_out_{i}->ShareBufferWith(*{PREFIX_TENSOR_NAME}{self.view_map[self.outputs['names'][i]]}); {code_indent} kernel_out_{i}->ShareInplaceVersionCounterWith(*{PREFIX_TENSOR_NAME}{self.view_map[self.outputs['names'][i]]}); {code_indent} VLOG(3) << "Perform View between Output and Input Tensor, share allocation and inplace version.";""" kernel_output = kernel_output[:-2] else: raise ValueError( "{} : Output error: the output should not be empty.".format( self.api)) return kernel_output, output_names, output_create def header_include(): return """ #include #include "paddle/phi/api/include/tensor.h" #include "paddle/phi/common/scalar.h" #include "paddle/phi/common/int_array.h" #include "paddle/utils/optional.h" """ def source_include(header_file_path): return f""" #include "{header_file_path}" #include #include "glog/logging.h" #include "paddle/phi/api/lib/api_custom_impl.h" #include "paddle/phi/api/lib/api_gen_utils.h" #include "paddle/phi/api/lib/data_transform.h" #include "paddle/phi/api/lib/kernel_dispatch.h" #include "paddle/phi/api/lib/utils/storage.h" #include "paddle/phi/core/kernel_registry.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" #include "paddle/fluid/platform/profiler/event_tracing.h" DECLARE_bool(conv2d_disable_cudnn); """ def api_namespace(): return (""" namespace paddle { namespace experimental { """, """ } // namespace experimental } // namespace paddle """) def generate_api(api_yaml_path, header_file_path, source_file_path): with open(api_yaml_path, 'r') as f: apis = yaml.load(f, Loader=yaml.FullLoader) 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/api/include/api.h" source_file.write(source_include(include_header_file)) source_file.write(namespace[0]) for api in apis: foward_api = ForwardAPI(api) if foward_api.is_dygraph_api: foward_api.is_dygraph_api = False header_file.write(foward_api.gene_api_declaration()) source_file.write(foward_api.gene_api_code()) header_file.write(namespace[1]) source_file.write(namespace[1]) 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', default='python/paddle/utils/code_gen/api.yaml') parser.add_argument( '--api_header_path', help='output of generated api header code file', default='paddle/phi/api/include/api.h') parser.add_argument( '--api_source_path', help='output of generated api source code file', default='paddle/phi/api/lib/api.cc') options = parser.parse_args() api_yaml_path = options.api_yaml_path header_file_path = options.api_header_path source_file_path = options.api_source_path generate_api(api_yaml_path, header_file_path, source_file_path) if __name__ == '__main__': main()