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117 lines
3.8 KiB
117 lines
3.8 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 <memory.h>
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#include <cstring>
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#include "paddle/fluid/framework/ddim.h"
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/platform/place.h"
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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/**
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* A thin wrapper for gathering on cpu tensor
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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-IndexT index Tensor (1-D)
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* return: output tensor
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*/
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template <typename T, typename IndexT = int>
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void CPUGather(const platform::DeviceContext& ctx, const Tensor& src,
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const Tensor& index, Tensor* output) {
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PADDLE_ENFORCE_EQ(platform::is_cpu_place(ctx.GetPlace()), true);
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// check index of shape 1-D
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if (index.dims().size() == 2) {
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PADDLE_ENFORCE_EQ(index.dims()[1], 1,
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"index.dims()[1] should be 1 when index.dims().size() == "
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"2 in gather_op.");
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} else {
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PADDLE_ENFORCE_EQ(index.dims().size(), 1,
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"index.dims().size() should be 1 or 2 in gather_op.");
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}
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int64_t index_size = index.dims()[0];
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auto src_dims = src.dims();
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const T* p_src = src.data<T>();
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const IndexT* p_index = index.data<IndexT>();
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T* p_output = output->data<T>();
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// slice size
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int slice_size = 1;
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for (int i = 1; i < src_dims.size(); ++i) slice_size *= src_dims[i];
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const size_t slice_bytes = slice_size * sizeof(T);
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for (int64_t i = 0; i < index_size; ++i) {
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IndexT index_ = p_index[i];
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memcpy(p_output + i * slice_size, p_src + index_ * slice_size, slice_bytes);
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}
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}
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template <typename T, typename IndexT = int>
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void CPUGatherNd(const platform::DeviceContext& ctx, const Tensor& input,
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const Tensor& index, Tensor* output) {
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PADDLE_ENFORCE_EQ(platform::is_cpu_place(ctx.GetPlace()), true,
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"It should be running on the CPU");
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auto index_dims = index.dims();
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auto index_dims_size = index_dims.size();
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auto input_dims = input.dims();
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auto input_dims_size = input_dims.size();
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const T* p_input = input.data<T>();
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const IndexT* p_index = index.data<IndexT>();
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T* p_output = output->data<T>();
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// final dim
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int64_t end_size = index_dims[index_dims_size - 1];
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// remain dim
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auto remain_ddim = framework::slice_ddim(index_dims, 0, index_dims_size - 1);
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int64_t remain_numel = framework::product(remain_ddim);
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// slice size
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int64_t slice_size = 1;
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for (int64_t i = end_size; i < input_dims_size; ++i) {
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slice_size *= input_dims[i];
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}
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const size_t slice_bytes = slice_size * sizeof(T);
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for (int64_t i = 0; i < remain_numel; ++i) {
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int64_t index_ = 0;
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int64_t temp = 1;
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for (int64_t j = end_size - 1; j >= 0; --j) {
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IndexT index_value = p_index[i * end_size + j];
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PADDLE_ENFORCE_LT(index_value, input_dims[j],
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"Input(index[-1)] has wrong value, it is %d",
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index_value);
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PADDLE_ENFORCE_GE(index_value, 0UL,
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"The value of Input(index) must be no less than 0");
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index_ += (index_value * temp);
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temp *= input_dims[j];
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}
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memcpy(p_output + i * slice_size, p_input + index_ * slice_size,
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slice_bytes);
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}
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}
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} // namespace operators
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} // namespace paddle
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