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69 lines
2.7 KiB
69 lines
2.7 KiB
// Copyright (c) 2018 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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#include "paddle/fluid/inference/anakin/convert/sum.h"
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#include <algorithm>
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#include <string>
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#include <vector>
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using anakin::PTuple;
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namespace paddle {
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namespace inference {
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namespace anakin {
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template <typename TargetT, ::anakin::Precision PrecisionT>
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void SumOpConverter<TargetT, PrecisionT>::operator()(
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const framework::proto::OpDesc &op, const framework::BlockDesc &block_desc,
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const framework::Scope &scope, bool test_mode) {
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framework::OpDesc op_desc(op, nullptr);
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PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 2);
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PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
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auto input_names = op_desc.Input("X");
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auto out_name = op_desc.Output("Out").front();
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auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
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std::vector<float> coeff = {1, 1};
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std::string elementwise_type = "Add";
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this->engine_->AddOp(op_name, "Eltwise", input_names, {out_name});
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this->engine_->template AddOpAttr<PTuple<float>>(op_name, "coeff", coeff);
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this->engine_->template AddOpAttr<std::string>(op_name, "type",
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elementwise_type);
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}
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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#ifdef PADDLE_WITH_CUDA
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using sum_nv_fp32 =
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::paddle::inference::anakin::SumOpConverter<::anakin::saber::NV,
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::anakin::Precision::FP32>;
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using sum_nv_int8 =
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::paddle::inference::anakin::SumOpConverter<::anakin::saber::NV,
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::anakin::Precision::INT8>;
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REGISTER_CUDA_ANAKIN_OP_CONVERTER(sum, sum_nv_fp32);
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REGISTER_CUDA_INT8_ANAKIN_OP_CONVERTER(sum, sum_nv_int8);
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#endif
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using sum_cpu_fp32 =
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::paddle::inference::anakin::SumOpConverter<::anakin::saber::X86,
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::anakin::Precision::FP32>;
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using sum_cpu_int8 =
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::paddle::inference::anakin::SumOpConverter<::anakin::saber::X86,
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::anakin::Precision::INT8>;
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REGISTER_CPU_ANAKIN_OP_CONVERTER(sum, sum_cpu_fp32);
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REGISTER_CPU_INT8_ANAKIN_OP_CONVERTER(sum, sum_cpu_int8);
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