/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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. */ #pragma once #include #include "paddle/framework/ddim.h" #include "paddle/framework/eigen.h" #include "paddle/framework/tensor.h" #include "paddle/platform/place.h" namespace paddle { namespace operators { using Tensor = framework::Tensor; template using EigenVector = framework::EigenVector; // Implementation of CPU copy template void CPUScatterUpdate(const paddle::framework::Tensor* src, const int* index, const size_t index_size, paddle::framework::Tensor* output) { paddle::framework::DDim output_dims = output->dims(); for (size_t i = 0; i < index_size; ++i) { int index_ = index[i]; paddle::framework::Tensor src_ = *src; paddle::framework::Tensor output_ = *output; if (index_size > 1) src_ = src->Slice(i, i + 1); if (output_dims[0] > 1) output_ = output->Slice(index_, index_ + 1); auto X = EigenVector::Flatten(src_); auto Y = EigenVector::Flatten(output_); Y = X + Y; } } // Implementation of GPU scatter: template void GPUScatterUpdate(const T* src, const int* index, const int slice_size, const int index_size, T* output); /** * Return a updated tensor from source tensor, scattered according to index: * dst[i] += src[index[i]] * input[src]: type-T source Tensor * input[index]: type-int index Tensor (1-D) * return: output tensor */ template void ScatterUpdate(const platform::Place& place, const paddle::framework::Tensor* src, const paddle::framework::Tensor* index, paddle::framework::Tensor* output) { // check index of shape 1-D PADDLE_ENFORCE(index->dims().size() == 1); int index_size = index->dims()[0]; auto src_dims = src->dims(); auto dst_dims = output->dims(); // check src shape and dst shape should match for (int i = 1; i < src_dims.size(); i++) PADDLE_ENFORCE(src_dims[i] == dst_dims[i]); // slice size size_t slice_size = 1; for (int i = 0; i < src_dims.size(); ++i) slice_size *= src_dims[i]; if (platform::is_cpu_place(place)) { CPUScatterUpdate(src, index->data(), index_size, output); } else { } } } // namespace operators } // namespace paddle