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70 lines
2.5 KiB
70 lines
2.5 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 <stdio.h>
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#include <cassert>
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#include <vector>
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#include "glog/logging.h"
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#include "paddle/fluid/inference/tensorrt/plugin/prelu_op_plugin.h"
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#include "paddle/fluid/operators/math/prelu.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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namespace plugin {
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nvinfer1::Dims PReluPlugin::getOutputDimensions(int index,
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const nvinfer1::Dims *inputDims,
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int nbInputs) {
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assert(nbInputs == 1);
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assert(index < this->getNbOutputs());
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nvinfer1::Dims const &input_dims = inputDims[0];
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nvinfer1::Dims output_dims = input_dims;
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return output_dims;
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}
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int PReluPlugin::enqueue(int batch_size, const void *const *inputs,
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void **outputs, void *workspace, cudaStream_t stream) {
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// input dims is CHW.
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const auto &input_dims = this->getInputDims(0);
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const float *input = reinterpret_cast<const float *>(inputs[0]);
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const float *alpha = reinterpret_cast<const float *>(alpha_.get().values);
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float *output = reinterpret_cast<float **>(outputs)[0];
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std::vector<int> input_shape;
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input_shape.push_back(batch_size);
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for (int i = 0; i < input_dims.nbDims; i++) {
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input_shape.push_back(input_dims.d[i]);
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}
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if (mode_ == "channel") {
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operators::math::PreluChannelWiseDirectCUDAFunctor<float>
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prelu_channel_wise;
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prelu_channel_wise(stream, input, alpha, output, input_shape);
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} else if (mode_ == "element") {
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operators::math::PreluElementWiseDirectCUDAFunctor<float>
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prelu_element_wise;
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prelu_element_wise(stream, input, alpha, output, input_shape);
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} else {
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operators::math::PreluScalarDirectCUDAFunctor<float> prelu_scalar;
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prelu_scalar(stream, input, alpha, output, input_shape);
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}
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return cudaGetLastError() != cudaSuccess;
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}
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} // namespace plugin
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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