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71 lines
2.0 KiB
71 lines
2.0 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <iostream>
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#include <string>
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#include <unordered_map>
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#include <vector>
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namespace paddle {
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namespace framework {
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namespace ir {
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static std::unordered_map<std::string, std::string> operator_cuda_table = {
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{"elementwise_add", "var$ + var$"},
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{"elementwise_sub", "var$ - var$"},
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{"elementwise_mul", "var$ * var$"},
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{"elementwise_div", "var$ / var$"},
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{"elementwise_min", "real_min(var$, var$)"},
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{"elementwise_max", "real_max(var$, var$)"},
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{"relu", "real_max(var$, 0)"},
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{"sigmoid", "1.0 / (1.0 + real_exp(-var$))"}};
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// op computation is composed by single or many operation
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class OperationExpression {
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public:
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OperationExpression(std::vector<int> input_ids, int output_id,
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std::string search_oprtation);
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std::string GetExpression();
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std::vector<int> GetInputIds() { return input_ids_; }
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int GetOutputId() { return output_id_; }
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private:
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std::vector<int> input_ids_;
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int output_id_;
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std::string search_operation_;
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};
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static const char indentation[] = R"( )";
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static const char const_kernel_start[] = R"(
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template <typename T>
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extern "C" __global__ void
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)";
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static const char const_kernel_mid[] = R"(
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{
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for(int idx = blockIdx.x * blockDim.x + threadIdx.x;
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idx < N;
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idx += gridDim.x * blockDim.x) {
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)";
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static const char const_kernel_end[] = R"(
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}
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}
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)";
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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