Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into public_to_protected
qiaolongfei
8 years ago
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/* 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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#pragma once
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#include <cstring>
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#include "paddle/framework/ddim.h"
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#include "paddle/framework/eigen.h"
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#include "paddle/framework/tensor.h"
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#include "paddle/platform/place.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename T, int MajorType = Eigen::RowMajor,
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typename IndexType = Eigen::DenseIndex>
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using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
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// Implementation of CPU copy
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template <typename T>
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void CPUScatterUpdate(const paddle::framework::Tensor* src, const int* index,
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const size_t index_size,
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paddle::framework::Tensor* output) {
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paddle::framework::DDim output_dims = output->dims();
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for (size_t i = 0; i < index_size; ++i) {
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int index_ = index[i];
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paddle::framework::Tensor src_ = *src;
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paddle::framework::Tensor output_ = *output;
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if (index_size > 1) src_ = src->Slice<T>(i, i + 1);
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if (output_dims[0] > 1) output_ = output->Slice<T>(index_, index_ + 1);
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auto X = EigenVector<T>::Flatten(src_);
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auto Y = EigenVector<T>::Flatten(output_);
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Y = X + Y;
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}
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}
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// Implementation of GPU scatter:
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template <typename T>
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void GPUScatterUpdate(const T* src, const int* index, const int slice_size,
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const int index_size, T* output);
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/**
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* Return a updated tensor from source tensor, scattered according to index:
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* dst[i] += src[index[i]]
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* input[src]: type-T source Tensor
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* input[index]: type-int index Tensor (1-D)
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* return: output tensor
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*/
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template <typename T>
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void ScatterUpdate(const platform::Place& place,
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const paddle::framework::Tensor* src,
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const paddle::framework::Tensor* index,
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paddle::framework::Tensor* output) {
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// check index of shape 1-D
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PADDLE_ENFORCE(index->dims().size() == 1);
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int index_size = index->dims()[0];
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auto src_dims = src->dims();
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auto dst_dims = output->dims();
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// check src shape and dst shape should match
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for (int i = 1; i < src_dims.size(); i++)
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PADDLE_ENFORCE(src_dims[i] == dst_dims[i]);
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// slice size
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size_t slice_size = 1;
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for (int i = 0; i < src_dims.size(); ++i) slice_size *= src_dims[i];
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if (platform::is_cpu_place(place)) {
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CPUScatterUpdate<T>(src, index->data<int>(), index_size, output);
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} else {
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}
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}
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,52 @@
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/* 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/scatter.h"
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#include "paddle/framework/ddim.h"
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#include "paddle/framework/tensor.h"
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#include "paddle/platform/place.h"
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#include <gtest/gtest.h>
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#include <iostream>
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#include <string>
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TEST(scatter, ScatterUpdate) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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using namespace paddle::operators;
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Tensor* src = new Tensor();
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Tensor* index = new Tensor();
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Tensor* output = new Tensor();
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float* p_src = nullptr;
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int* p_index = nullptr;
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p_src = src->mutable_data<float>(make_ddim({1, 4}), CPUPlace());
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p_index = index->mutable_data<int>(make_ddim({1}), CPUPlace());
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for (size_t i = 0; i < 4; ++i) p_src[i] = float(i);
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p_index[0] = 1;
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float* p_output = output->mutable_data<float>(make_ddim({4, 4}), CPUPlace());
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ScatterUpdate<float>(CPUPlace(), src, index, output);
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for (size_t i = 0; i < 4; ++i) EXPECT_EQ(p_output[i], float(0));
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for (size_t i = 0; i < 4; ++i) EXPECT_EQ(output->data<float>()[i], float(0));
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for (size_t i = 4; i < 8; ++i) EXPECT_EQ(p_output[i], float(i - 4));
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for (size_t i = 4; i < 8; ++i)
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EXPECT_EQ(output->data<float>()[i], float(i - 4));
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for (size_t i = 8; i < 16; ++i) EXPECT_EQ(p_output[i], float(0));
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for (size_t i = 8; i < 16; ++i) EXPECT_EQ(output->data<float>()[i], float(0));
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}
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