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135 lines
5.2 KiB
135 lines
5.2 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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#pragma once
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/selected_rows.h"
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#include "paddle/fluid/platform/device_context.h"
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#define INLINE_FOR2(sizei, sizej) \
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for (int64_t i = 0; i < sizei; i++) \
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for (int64_t j = 0; j < sizej; j++)
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namespace paddle {
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namespace operators {
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namespace math {
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// SelectedRows + SelectedRows will simplely concat value and rows.
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// The real computation happens in dealing with LoDTensor.
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template <typename DeviceContext, typename T>
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struct SelectedRowsAdd {
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void operator()(const 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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};
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template <typename DeviceContext, typename T>
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struct SelectedRowsAddTensor {
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void operator()(const 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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};
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// input2 = input1 + input2
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template <typename DeviceContext, typename T>
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struct SelectedRowsAddTo {
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void operator()(const DeviceContext& context,
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const framework::SelectedRows& input1,
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const int64_t input2_offset, framework::SelectedRows* input2);
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};
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// input2 = input1 + input2
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template <typename DeviceContext, typename T>
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struct SelectedRowsAddToTensor {
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void operator()(const DeviceContext& context,
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const framework::SelectedRows& input1,
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framework::Tensor* input2);
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};
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namespace scatter {
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// functors for manuplating SelectedRows data
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template <typename DeviceContext, typename T>
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struct MergeAdd {
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// unary functor, merge by adding duplicated rows in
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// the input SelectedRows object.
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framework::SelectedRows operator()(const DeviceContext& context,
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const framework::SelectedRows& input);
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};
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template <typename DeviceContext, typename T>
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struct Add {
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framework::SelectedRows operator()(const DeviceContext& context,
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const framework::SelectedRows& input1,
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const framework::SelectedRows& input2) {
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framework::SelectedRows out;
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out.set_rows(input1.rows());
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out.set_height(input1.height());
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out.mutable_value()->mutable_data<T>(input1.value().dims(),
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context.GetPlace());
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auto e_out = framework::EigenVector<T>::Flatten(*(out.mutable_value()));
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auto e_in1 = framework::EigenVector<T>::Flatten(input1.value());
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auto e_in2 = framework::EigenVector<T>::Flatten(input2.value());
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e_out.device(*context.eigen_device()) = e_in1 + e_in2;
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return out;
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}
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};
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template <typename DeviceContext, typename T>
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struct Mul {
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// multiply two SelectedRows
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framework::SelectedRows operator()(const DeviceContext& context,
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const framework::SelectedRows& input1,
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const framework::SelectedRows& input2) {
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framework::SelectedRows out;
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out.set_rows(input1.rows());
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out.set_height(input1.height());
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out.mutable_value()->mutable_data<T>(input1.value().dims(),
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context.GetPlace());
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auto e_out = framework::EigenVector<T>::Flatten(*(out.mutable_value()));
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auto e_in1 = framework::EigenVector<T>::Flatten(input1.value());
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auto e_in2 = framework::EigenVector<T>::Flatten(input2.value());
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e_out.device(*context.eigen_device()) = e_in1 * e_in2;
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return out;
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}
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// multiply scalar to SelectedRows
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framework::SelectedRows operator()(const DeviceContext& context,
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const framework::SelectedRows& input1,
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const T input2) {
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framework::SelectedRows out;
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out.set_rows(input1.rows());
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out.set_height(input1.height());
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out.mutable_value()->mutable_data<T>(input1.value().dims(),
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context.GetPlace());
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auto e_out = framework::EigenVector<T>::Flatten(*(out.mutable_value()));
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auto e_in1 = framework::EigenVector<T>::Flatten(input1.value());
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e_out.device(*context.eigen_device()) = input2 * e_in1;
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return out;
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}
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};
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enum class ScatterOps { ASSIGN, ADD, SUB, SUBBY, MUL, DIV, DIVBY };
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// out = seleted_rows_in / tensor
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template <typename DeviceContext, typename T>
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struct UpdateToTensor {
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void operator()(const DeviceContext& context, const ScatterOps& op,
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const framework::SelectedRows& input1,
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framework::Tensor* input2);
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};
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} // namespace scatter
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} // namespace math
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} // namespace operators
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} // namespace paddle
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