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Merge pull request #8669 from chengduoZH/feature/concat_op
Refine concat_op
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,119 @@ | ||
| /* Copyright (c) 2018 paddlepaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
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| #include "paddle/fluid/operators/math/concat.h" | ||
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| namespace paddle { | ||
| namespace operators { | ||
| namespace math { | ||
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| /* | ||
| * All tensors' dimension should be the same and the values of | ||
| * each dimension are the same, except the axis dimension. | ||
| */ | ||
| template <typename T> | ||
| class ConcatFunctor<platform::CPUDeviceContext, T> { | ||
| public: | ||
| void operator()(const platform::CPUDeviceContext& context, | ||
| const std::vector<framework::Tensor>& input, const int axis, | ||
| framework::Tensor* output) { | ||
| // TODO(zcd): Add input data validity checking | ||
| int num = input.size(); | ||
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| int rows = 1; | ||
| auto dim_0 = input[0].dims(); | ||
| for (int i = 0; i < axis; ++i) { | ||
| rows *= dim_0[i]; | ||
| } | ||
| int out_rows = rows, out_cols = 0; | ||
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| std::vector<int64_t> input_cols(input.size()); | ||
| for (int i = 0; i < num; ++i) { | ||
| int t_cols = input[i].numel() / rows; | ||
| out_cols += t_cols; | ||
| input_cols[i] = t_cols; | ||
| } | ||
| auto& cpu_place = boost::get<platform::CPUPlace>(context.GetPlace()); | ||
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| // computation | ||
| for (int k = 0; k < out_rows; ++k) { | ||
| T* dst_ptr = output->data<T>() + k * out_cols; | ||
| int col_idx = 0; | ||
| for (int j = 0; j < num; ++j) { | ||
| int col_len = input_cols[j]; | ||
| const T* src_prt = input[j].data<T>() + k * col_len; | ||
| memory::Copy(cpu_place, dst_ptr + col_idx, cpu_place, src_prt, | ||
| sizeof(T) * col_len); | ||
| col_idx += col_len; | ||
| } | ||
| } | ||
| } | ||
| }; | ||
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| /* | ||
| * All tensors' dimension should be the same and the values of | ||
| * each dimension are the same, except the axis dimension. | ||
| */ | ||
| template <typename T> | ||
| class ConcatGradFunctor<platform::CPUDeviceContext, T> { | ||
| public: | ||
| void operator()(const platform::CPUDeviceContext& context, | ||
| const framework::Tensor& input, const int axis, | ||
| std::vector<framework::Tensor>& outputs) { | ||
| // TODO(zcd): Add input data validity checking | ||
| int num = outputs.size(); | ||
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| int input_rows = 1; | ||
| auto dim_0 = outputs[0].dims(); | ||
| for (int i = 0; i < axis; ++i) { | ||
| input_rows *= dim_0[i]; | ||
| } | ||
| int input_cols = 0; | ||
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| std::vector<int64_t> output_cols(outputs.size()); | ||
| for (int i = 0; i < num; ++i) { | ||
| int t_cols = outputs[i].numel() / input_rows; | ||
| input_cols += t_cols; | ||
| output_cols[i] = t_cols; | ||
| } | ||
| auto& cpu_place = boost::get<platform::CPUPlace>(context.GetPlace()); | ||
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| // computation | ||
| for (int k = 0; k < input_rows; ++k) { | ||
| const T* src_ptr = input.data<T>() + k * input_cols; | ||
| int col_idx = 0; | ||
| for (int j = 0; j < num; ++j) { | ||
| int col_len = output_cols[j]; | ||
| T* dst_ptr = outputs[j].data<T>() + k * col_len; | ||
| memory::Copy(cpu_place, dst_ptr, cpu_place, src_ptr + col_idx, | ||
| sizeof(T) * col_len); | ||
| col_idx += col_len; | ||
| } | ||
| } | ||
| } | ||
| }; | ||
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| template class ConcatFunctor<platform::CPUDeviceContext, int>; | ||
| template class ConcatFunctor<platform::CPUDeviceContext, int64_t>; | ||
| template class ConcatFunctor<platform::CPUDeviceContext, float>; | ||
| template class ConcatFunctor<platform::CPUDeviceContext, double>; | ||
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| template class ConcatGradFunctor<platform::CPUDeviceContext, int>; | ||
| template class ConcatGradFunctor<platform::CPUDeviceContext, int64_t>; | ||
| template class ConcatGradFunctor<platform::CPUDeviceContext, float>; | ||
| template class ConcatGradFunctor<platform::CPUDeviceContext, double>; | ||
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| } // namespace math | ||
| } // namespace operators | ||
| } // namespace paddle |
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