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115 lines
4.2 KiB
115 lines
4.2 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/operators/math/selected_rows_functor.h"
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#include "paddle/operators/math/math_function.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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struct SelectedRowsAdd<platform::CPUPlace, T> {
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void operator()(const platform::DeviceContext& context,
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const framework::SelectedRows& input1,
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const framework::SelectedRows& input2,
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framework::SelectedRows* output) {
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auto in1_height = input1.height();
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PADDLE_ENFORCE_EQ(in1_height, input2.height());
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output->set_height(in1_height);
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auto& in1_rows = input1.rows();
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auto& in2_rows = input2.rows();
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std::vector<int64_t> out_rows;
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out_rows.reserve(in1_rows.size() + in2_rows.size());
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// concat rows
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out_rows.insert(out_rows.end(), in1_rows.begin(), in1_rows.end());
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out_rows.insert(out_rows.end(), in2_rows.begin(), in2_rows.end());
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output->set_rows(out_rows);
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auto* out_value = output->mutable_value();
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auto& in1_value = input1.value();
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auto& in2_value = input2.value();
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auto in1_row_numel = in1_value.numel() / in1_rows.size();
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PADDLE_ENFORCE_EQ(in1_row_numel, in2_value.numel() / in2_rows.size());
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PADDLE_ENFORCE_EQ(in1_row_numel, out_value->numel() / out_rows.size());
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auto in1_place = input1.place();
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PADDLE_ENFORCE(platform::is_cpu_place(in1_place));
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auto in2_place = input2.place();
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PADDLE_ENFORCE(platform::is_cpu_place(in2_place));
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auto out_place = context.GetPlace();
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PADDLE_ENFORCE(platform::is_cpu_place(out_place));
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auto* out_data = out_value->data<T>();
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auto* in1_data = in1_value.data<T>();
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memory::Copy(boost::get<platform::CPUPlace>(out_place), out_data,
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boost::get<platform::CPUPlace>(in1_place), in1_data,
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in1_value.numel() * sizeof(T));
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auto* in2_data = in2_value.data<T>();
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memory::Copy(boost::get<platform::CPUPlace>(out_place),
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out_data + in1_value.numel(),
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boost::get<platform::CPUPlace>(in2_place), in2_data,
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in2_value.numel() * sizeof(T));
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}
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};
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template struct SelectedRowsAdd<platform::CPUPlace, float>;
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template <typename T>
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struct SelectedRowsAddTensor<platform::CPUPlace, T> {
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void operator()(const platform::DeviceContext& context,
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const framework::SelectedRows& input1,
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const framework::Tensor& input2, framework::Tensor* output) {
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auto in1_height = input1.height();
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auto in2_dims = input2.dims();
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auto out_dims = output->dims();
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PADDLE_ENFORCE_EQ(in1_height, in2_dims[0]);
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PADDLE_ENFORCE_EQ(in1_height, out_dims[0]);
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auto& in1_value = input1.value();
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auto& in1_rows = input1.rows();
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int64_t in1_row_numel = in1_value.numel() / in1_rows.size();
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PADDLE_ENFORCE_EQ(in1_row_numel, input2.numel() / in1_height);
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PADDLE_ENFORCE_EQ(in1_row_numel, output->numel() / in1_height);
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SetConstant<platform::CPUPlace, T> functor;
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functor(context, output, 0.0);
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auto* in1_data = in1_value.data<T>();
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auto* out_data = output->data<T>();
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for (size_t i = 0; i < in1_rows.size(); i++) {
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for (int64_t j = 0; j < in1_row_numel; j++) {
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out_data[in1_rows[i] * in1_row_numel + j] +=
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in1_data[i * in1_row_numel + j];
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}
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}
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auto out_eigen = framework::EigenVector<T>::Flatten(*output);
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auto in2_eigen = framework::EigenVector<T>::Flatten(input2);
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out_eigen.device(*context.GetEigenDevice<platform::CPUPlace>()) =
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out_eigen + in2_eigen;
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}
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};
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template struct SelectedRowsAddTensor<platform::CPUPlace, float>;
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} // namespace math
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} // namespace operators
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} // namespace paddle
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