wehub-resource-sync
131 lines
4.3 KiB
C++
131 lines
4.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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 "glog/logging.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/phi/kernels/funcs/blas/blas.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace phi {
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template <typename Context, typename T, typename IndexT = int>
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void IndexAddInner(const Context& dev_ctx,
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DenseTensor* input,
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const DenseTensor& index,
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int axis,
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DenseTensor* add_value,
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DenseTensor* output) {
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auto input_dim = input->dims();
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auto input_dim_size = input_dim.size();
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auto output_dim = output->dims();
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auto index_size = index.dims()[0];
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auto add_value_dim = add_value->dims();
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const IndexT* index_data = index.data<IndexT>();
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dev_ctx.template Alloc<T>(output);
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// copy x to output.
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// todo(@limin29): inplace do not need copy.
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Copy(dev_ctx, *input, dev_ctx.GetPlace(), false, output);
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if (index.numel() == 0) return;
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auto slice_size = 1;
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for (auto i = axis + 1; i < input_dim_size; i++) {
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slice_size *= input_dim[i];
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}
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auto outer_nums = 1;
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for (auto i = 0; i < axis; i++) {
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outer_nums *= input_dim[i];
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}
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for (int i = 0; i < index_size; i++) {
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PADDLE_ENFORCE_GE(
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index_data[i],
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-input_dim[axis],
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common::errors::InvalidArgument(
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"Variable value (index) of OP(index_add) "
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"expected >= %ld and < %ld, but got %ld. Please check input "
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"value.",
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-input_dim[axis],
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input_dim[axis],
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index_data[i]));
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PADDLE_ENFORCE_LT(
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index_data[i],
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input_dim[axis],
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common::errors::InvalidArgument(
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"Variable value (index) of OP(index_add) "
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"expected >= %ld and < %ld, but got %ld. Please check input "
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"value.",
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-input_dim[axis],
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input_dim[axis],
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index_data[i]));
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}
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VLOG(3) << "Index_Add_Debug; outer_nums: " << outer_nums
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<< "; slice_size: " << slice_size << "; index_size: " << index_size;
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output->Resize({outer_nums, input_dim[axis], slice_size});
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add_value->Resize({outer_nums, index_size, slice_size});
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VLOG(3) << "output.dims: " << output->dims()
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<< ", add_value.dims: " << add_value->dims();
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auto add_value_tensor = EigenTensor<T, 3>::From(*add_value);
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auto output_tensor = EigenTensor<T, 3>::From(*output);
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auto& place = *dev_ctx.eigen_device();
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for (auto j = 0; j < index_size; j++) {
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IndexT index_value = index_data[j];
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if (index_value < 0) {
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index_value += input_dim[axis];
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}
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auto output_t = output_tensor.chip(index_value, 1);
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output_t.device(place) = output_t + add_value_tensor.chip(j, 1);
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}
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output->Resize(output_dim);
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add_value->Resize(add_value_dim);
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}
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template <typename T, typename Context>
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void IndexAddBaseKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& index,
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int axis,
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const DenseTensor& add_value,
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DenseTensor* output) {
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if (output && output->numel() == 0) {
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dev_ctx.template Alloc<T>(output);
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return;
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}
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const auto& index_type = index.dtype();
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if (axis < 0) {
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axis += x.dims().size();
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}
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auto inputs = x;
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auto add_values = add_value;
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if (index_type == phi::DataType::INT32) {
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IndexAddInner<Context, T, int>(
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dev_ctx, &inputs, index, axis, &add_values, output);
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} else if (index_type == phi::DataType::INT64) {
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IndexAddInner<Context, T, int64_t>(
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dev_ctx, &inputs, index, axis, &add_values, output);
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}
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}
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} // namespace phi
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