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92 lines
3.7 KiB
92 lines
3.7 KiB
/* Copyright (c) 2016 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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#include "paddle/fluid/operators/math/unpooling.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename T>
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class Unpool2dMaxFunctor<platform::CPUDeviceContext, T> {
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public:
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void operator()(const platform::CPUDeviceContext& context,
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const framework::Tensor& input,
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const framework::Tensor& indices, framework::Tensor* output) {
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const int batch_size = input.dims()[0];
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const int input_height = input.dims()[2];
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const int input_width = input.dims()[3];
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const int output_channels = output->dims()[1];
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const int output_height = output->dims()[2];
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const int output_width = output->dims()[3];
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int input_feasize = input_height * input_width;
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int output_feasize = output_height * output_width;
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const T* input_data = input.data<T>();
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const int* indices_data = indices.data<int>();
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T* output_data = output->mutable_data<T>(context.GetPlace());
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for (int b = 0; b < batch_size; ++b) {
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for (int c = 0; c < output_channels; ++c) {
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for (int i = 0; i < input_feasize; ++i) {
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int index = indices_data[i];
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PADDLE_ENFORCE(index < output_feasize, "err index in unpooling!");
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output_data[index] = input_data[i];
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}
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input_data += input_feasize;
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indices_data += input_feasize;
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output_data += output_feasize;
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}
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}
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}
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};
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template <class T>
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class Unpool2dMaxGradFunctor<platform::CPUDeviceContext, T> {
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public:
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void operator()(const platform::CPUDeviceContext& context,
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const framework::Tensor& input,
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const framework::Tensor& indices,
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const framework::Tensor& output,
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const framework::Tensor& output_grad,
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framework::Tensor* input_grad) {
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const int batch_size = input.dims()[0];
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const int input_height = input.dims()[2];
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const int input_width = input.dims()[3];
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const int output_channels = output.dims()[1];
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const int output_height = output.dims()[2];
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const int output_width = output.dims()[3];
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int input_feasize = input_height * input_width;
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int output_feasize = output_height * output_width;
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const int* indices_data = indices.data<int>();
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const T* output_grad_data = output_grad.data<T>();
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T* input_grad_data = input_grad->mutable_data<T>(context.GetPlace());
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for (int b = 0; b < batch_size; ++b) {
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for (int c = 0; c < output_channels; ++c) {
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for (int i = 0; i < input_feasize; ++i) {
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int index = indices_data[i];
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PADDLE_ENFORCE(index < output_feasize, "err index in unpooling!");
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input_grad_data[i] = output_grad_data[index];
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}
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input_grad_data += input_feasize;
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indices_data += input_feasize;
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output_grad_data += output_feasize;
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}
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}
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}
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};
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template class Unpool2dMaxGradFunctor<platform::CPUDeviceContext, float>;
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template class Unpool2dMaxGradFunctor<platform::CPUDeviceContext, double>;
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template class Unpool2dMaxFunctor<platform::CPUDeviceContext, float>;
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template class Unpool2dMaxFunctor<platform::CPUDeviceContext, double>;
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} // namespace math
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} // namespace operators
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} // namespace paddle
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