chengduo
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/* 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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#include "paddle/fluid/operators/math/concat.h"
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namespace paddle {
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namespace operators {
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namespace math {
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/*
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* All tensors' dimension should be the same and the values of
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* each dimension are the same, except the axis dimension.
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*/
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template <typename T>
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class ConcatFunctor<platform::CPUDeviceContext, T> {
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public:
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void operator()(const platform::CPUDeviceContext& context,
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const std::vector<framework::Tensor>& input, const int axis,
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framework::Tensor* output) {
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// TODO(zcd): Add input data validity checking
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int num = input.size();
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int rows = 1;
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auto dim_0 = input[0].dims();
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for (int i = 0; i < axis; ++i) {
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rows *= dim_0[i];
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}
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int out_rows = rows, out_cols = 0;
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std::vector<int64_t> input_cols(input.size());
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for (int i = 0; i < num; ++i) {
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int t_cols = input[i].numel() / rows;
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out_cols += t_cols;
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input_cols[i] = t_cols;
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}
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auto& cpu_place = boost::get<platform::CPUPlace>(context.GetPlace());
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// computation
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for (int k = 0; k < out_rows; ++k) {
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T* dst_ptr = output->data<T>() + k * out_cols;
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int col_idx = 0;
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for (int j = 0; j < num; ++j) {
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int col_len = input_cols[j];
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const T* src_prt = input[j].data<T>() + k * col_len;
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memory::Copy(cpu_place, dst_ptr + col_idx, cpu_place, src_prt,
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sizeof(T) * col_len);
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col_idx += col_len;
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}
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}
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}
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};
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/*
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* All tensors' dimension should be the same and the values of
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* each dimension are the same, except the axis dimension.
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*/
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template <typename T>
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class ConcatGradFunctor<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, const int axis,
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std::vector<framework::Tensor>& outputs) {
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// TODO(zcd): Add input data validity checking
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int num = outputs.size();
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int input_rows = 1;
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auto dim_0 = outputs[0].dims();
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for (int i = 0; i < axis; ++i) {
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input_rows *= dim_0[i];
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}
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int input_cols = 0;
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std::vector<int64_t> output_cols(outputs.size());
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for (int i = 0; i < num; ++i) {
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int t_cols = outputs[i].numel() / input_rows;
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input_cols += t_cols;
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output_cols[i] = t_cols;
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}
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auto& cpu_place = boost::get<platform::CPUPlace>(context.GetPlace());
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// computation
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for (int k = 0; k < input_rows; ++k) {
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const T* src_ptr = input.data<T>() + k * input_cols;
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int col_idx = 0;
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for (int j = 0; j < num; ++j) {
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int col_len = output_cols[j];
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T* dst_ptr = outputs[j].data<T>() + k * col_len;
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memory::Copy(cpu_place, dst_ptr, cpu_place, src_ptr + col_idx,
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sizeof(T) * col_len);
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col_idx += col_len;
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}
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}
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}
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};
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template class ConcatFunctor<platform::CPUDeviceContext, int>;
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template class ConcatFunctor<platform::CPUDeviceContext, int64_t>;
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template class ConcatFunctor<platform::CPUDeviceContext, float>;
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template class ConcatFunctor<platform::CPUDeviceContext, double>;
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template class ConcatGradFunctor<platform::CPUDeviceContext, int>;
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template class ConcatGradFunctor<platform::CPUDeviceContext, int64_t>;
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template class ConcatGradFunctor<platform::CPUDeviceContext, float>;
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template class ConcatGradFunctor<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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@ -0,0 +1,63 @@
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/* 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 "paddle/fluid/framework/tensor.h"
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namespace paddle {
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namespace operators {
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namespace math {
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/*
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* \brief Concatenate the input tensors along the dimension axis.
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* TODO(zcd): maybe it needs to be more detailed.
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* Examples:
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* Input[0] = [[1,2],[3,4]]
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* Input[1] = [[5,6]]
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* axis = 0
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*
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* Output = [[1,2],
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* [3,4],
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* [5,6]]
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*/
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template <typename DeviceContext, typename T>
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class ConcatFunctor {
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public:
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void operator()(const DeviceContext& context,
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const std::vector<framework::Tensor>& input, const int axis,
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framework::Tensor* output);
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};
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/*
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* \brief Split the input tensors along the dimension axis into outputs.
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* TODO(zcd): maybe it needs to be more detailed.
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* Examples:
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* Input = [[1,2],
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* [3,4],
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* [5,6]]
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* axis = 0
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*
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* Output[0] = [[1,2],[3,4]]
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* Output[1] = [[5,6]]
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*/
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template <typename DeviceContext, typename T>
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class ConcatGradFunctor {
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public:
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void operator()(const DeviceContext& context, const framework::Tensor& input,
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const int axis, std::vector<framework::Tensor>& outputs);
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};
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} // namespace math
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} // namespace operators
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} // namespace paddle
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