wehub-resource-sync
85 lines
3.3 KiB
C++
85 lines
3.3 KiB
C++
// Copyright (c) 2023 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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#include "paddle/phi/kernels/index_sample_grad_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/utils/data_type.h"
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namespace phi {
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template <typename T, typename Context>
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void IndexSampleGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& index,
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const DenseTensor& out_grad,
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DenseTensor* in_grad) {
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using XPUType = typename XPUTypeTrait<T>::Type;
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const auto& index_type = index.dtype();
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bool index_type_match =
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index_type == DataType::INT32 || index_type == DataType::INT64;
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PADDLE_ENFORCE_EQ(index_type_match,
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true,
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common::errors::InvalidArgument(
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"Input(Index) holds the wrong type, it holds %s, but "
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"desires to be %s or %s",
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index_type,
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DataType::INT32,
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DataType::INT64));
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XPUType* in_grad_data = dev_ctx.template Alloc<XPUType>(in_grad);
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const XPUType* out_grad_data = out_grad.data<XPUType>();
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auto in_grad_shape = vectorize<int64_t>(in_grad->dims());
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auto out_grad_shape = vectorize<int64_t>(out_grad.dims());
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auto index_shape = vectorize<int64_t>(index.dims());
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int r = xpu::constant(dev_ctx.x_context(),
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in_grad_data,
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in_grad->numel(),
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static_cast<XPUType>(0));
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if (index_type == DataType::INT32) {
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const int* index_data = index.data<int>();
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r = xpu::scatter_element(dev_ctx.x_context(),
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in_grad_data,
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out_grad_data,
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index_data,
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in_grad_data,
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in_grad_shape,
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out_grad_shape,
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index_shape,
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1,
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1);
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} else if (index_type == DataType::INT64) {
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const int64_t* index_data = index.data<int64_t>();
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r = xpu::scatter_element(dev_ctx.x_context(),
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in_grad_data,
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out_grad_data,
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index_data,
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in_grad_data,
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in_grad_shape,
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out_grad_shape,
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index_shape,
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1,
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1);
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}
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "scatter_element");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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index_sample_grad, XPU, ALL_LAYOUT, phi::IndexSampleGradKernel, float) {}
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