211 lines
6.4 KiB
Python
211 lines
6.4 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import yaml
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from api_gen import ForwardAPI
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kernel_func_set = set()
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def get_wrapped_infermeta_name(api_name):
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return api_name.capitalize() + 'InferMeta'
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def gene_wrapped_infermeta_and_register(api):
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if api.is_base_api and not api.is_dygraph_api:
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register_code = f"""
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PD_REGISTER_INFER_META_FN({api.kernel['func'][0]}, phi::{api.infer_meta['func']});"""
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if api.infer_meta['param'] is not None:
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if api.kernel['func'][0] in kernel_func_set:
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return '', '', ''
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kernel_params = api.kernel['param']
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if kernel_params is None:
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kernel_params = api.inputs['names'] + api.attrs['names']
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if kernel_params == api.infer_meta['param']:
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return '', '', register_code
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assert len(api.infer_meta['param']) <= len(kernel_params), (
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f"{api.api} api: Parameters error. The params of infer_meta should be a subset of kernel params."
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)
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tensor_type_map = {
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'const Tensor&': 'const MetaTensor&',
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'const std::vector<Tensor>&': 'const std::vector<const MetaTensor*>&',
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'Tensor': 'MetaTensor*',
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'std::vector<Tensor>': 'std::vector<MetaTensor*>',
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'const paddle::optional<Tensor>&': 'const MetaTensor&',
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}
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wrapped_infermeta_name = get_wrapped_infermeta_name(
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api.kernel['func'][0]
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)
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args = []
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for input_name in api.inputs['names']:
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if input_name in kernel_params:
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args.append(
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tensor_type_map[api.inputs['input_info'][input_name]]
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+ ' '
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+ input_name
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)
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for attr_name in api.attrs['names']:
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if attr_name in kernel_params:
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args.append(
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api.attrs['attr_info'][attr_name][0] + ' ' + attr_name
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)
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for i, out_type in enumerate(api.outputs['types']):
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args.append(
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tensor_type_map[out_type] + ' ' + api.outputs['names'][i]
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)
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invoke_param = api.infer_meta['param']
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invoke_param.extend(api.outputs['names'])
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declare_code = f"""
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void {wrapped_infermeta_name}({", ".join(args)});
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"""
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defined_code = f"""
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void {wrapped_infermeta_name}({", ".join(args)}) {{
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{api.infer_meta['func']}({", ".join(invoke_param)});
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}}
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"""
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register_code = f"""
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PD_REGISTER_INFER_META_FN({api.kernel['func'][0]}, phi::{get_wrapped_infermeta_name(api.kernel['func'][0])});"""
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kernel_func_set.add(api.kernel['func'][0])
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return declare_code, defined_code, register_code
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else:
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return '', '', register_code
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else:
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return '', '', ''
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def header_include():
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return """
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#include "paddle/phi/core/meta_tensor.h"
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#include "paddle/phi/common/scalar.h"
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#include "paddle/phi/common/int_array.h"
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"""
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def source_include(header_file_path):
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return f"""
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#include "{header_file_path}"
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#include "paddle/phi/core/infermeta_utils.h"
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#include "paddle/phi/infermeta/binary.h"
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#include "paddle/phi/infermeta/multiary.h"
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#include "paddle/phi/infermeta/nullary.h"
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#include "paddle/phi/infermeta/unary.h"
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#include "paddle/phi/infermeta/ternary.h"
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"""
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def api_namespace():
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return (
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"""
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namespace phi {
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""",
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"""
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} // namespace phi
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""",
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)
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def generate_wrapped_infermeta_and_register(
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api_yaml_path, header_file_path, source_file_path
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):
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apis = []
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for each_api_yaml in api_yaml_path:
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with open(each_api_yaml, 'r') as f:
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api_list = yaml.load(f, Loader=yaml.FullLoader)
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if api_list:
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apis.extend(api_list)
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header_file = open(header_file_path, 'w')
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source_file = open(source_file_path, 'w')
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namespace = api_namespace()
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header_file.write("#pragma once\n")
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header_file.write(header_include())
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header_file.write(namespace[0])
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include_header_file = "paddle/phi/infermeta/generated.h"
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source_file.write(source_include(include_header_file))
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source_file.write(namespace[0])
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infermeta_register_code = ''
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for api in apis:
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api_item = ForwardAPI(api)
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(
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declare_code,
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defined_code,
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register_code,
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) = gene_wrapped_infermeta_and_register(api_item)
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header_file.write(declare_code)
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source_file.write(defined_code)
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if infermeta_register_code.find(register_code) == -1:
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infermeta_register_code = infermeta_register_code + register_code
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header_file.write(namespace[1])
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source_file.write(namespace[1])
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source_file.write(infermeta_register_code)
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header_file.close()
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source_file.close()
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def main():
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parser = argparse.ArgumentParser(
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description='Generate PaddlePaddle C++ API files'
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)
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parser.add_argument(
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'--api_yaml_path',
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help='path to api yaml file',
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nargs='+',
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default=['paddle/phi/ops/yaml/ops.yaml'],
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)
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parser.add_argument(
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'--wrapped_infermeta_header_path',
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help='output of generated wrapped_infermeta header code file',
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default='paddle/phi/infermeta/generated.h',
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)
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parser.add_argument(
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'--wrapped_infermeta_source_path',
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help='output of generated wrapped_infermeta source code file',
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default='paddle/phi/infermeta/generated.cc',
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)
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options = parser.parse_args()
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api_yaml_path = options.api_yaml_path
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header_file_path = options.wrapped_infermeta_header_path
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source_file_path = options.wrapped_infermeta_source_path
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generate_wrapped_infermeta_and_register(
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api_yaml_path, header_file_path, source_file_path
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)
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if __name__ == '__main__':
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main()
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