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98 lines
2.8 KiB
98 lines
2.8 KiB
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 <memory.h>
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#include <cstring>
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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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using paddle::framework::Tensor;
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using paddle::framework::DDim;
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namespace paddle {
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namespace operators {
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/* Implementation of CPU copy */
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template <typename T>
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void CPUGather(const T* params,
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const int* indices,
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const int slice_size,
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const int index_size,
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T* output) {
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const size_t slice_bytes = slice_size * sizeof(T);
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for (size_t i = 0; i < index_size; ++i) {
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int index_ = indices[i];
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// copy src[index_] to output[i]
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memcpy(output + i * slice_size, params + index_ * slice_size, slice_bytes);
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}
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}
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/* Implementation of GPU copy:
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I suppose the GPUDevice& d, contains gpu_id and thread_id
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d = cuda_stream(gpu_id_, stream_id_);
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*/
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template <typename T>
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void GPUGather(const T* src,
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const int* index,
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const int slice_size,
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const int index_size,
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T* output);
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/**
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* Return a new tensor from source tensor, gathered according to index
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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 Gather(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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DDim output_dims(src_dims);
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output_dims[0] = index_size;
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// slice size
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int slice_size = 1;
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for (size_t i = 1; i < src_dims.size(); ++i) slice_size *= src_dims[i];
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// Gathering
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if (platform::is_cpu_place(place)) {
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CPUGather<T>(src->data<T>(),
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index->data<int>(),
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slice_size,
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index_size,
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output->data<T>());
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} else {
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// init for GPU
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// output_arr = output->mutable_data<T>(output_dims, platform::GPUPlace());
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// how to specialize device??
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// GPUGather(
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// d, src->data(), index->data(), slice_size,
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// new_tensor->mutable_data());
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}
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}
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} // namespace operators
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} // namespace paddle
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