wehub-resource-sync
86 lines
2.7 KiB
C++
86 lines
2.7 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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#include "paddle/phi/kernels/where_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/kernels/full_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void WhereGradKernel(const Context& dev_ctx,
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const DenseTensor& condition,
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const DenseTensor& x,
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const DenseTensor& y,
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const DenseTensor& out_grad,
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DenseTensor* x_grad,
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DenseTensor* y_grad) {
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using XPUType = typename XPUTypeTrait<T>::Type;
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if (out_grad.numel() == 0) {
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if (x_grad) {
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Full<T, Context>(dev_ctx, x_grad->dims(), static_cast<T>(0), x_grad);
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}
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if (y_grad) {
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Full<T, Context>(dev_ctx, y_grad->dims(), static_cast<T>(0), y_grad);
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}
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return;
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}
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const auto* cond_data = condition.data<bool>();
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auto* dout = out_grad.data<T>();
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auto cond_shape = vectorize(condition.dims());
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auto out_shape = vectorize(out_grad.dims());
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// use [1] to replace [], because xpu not support []
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if (cond_shape.size() == 0) {
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cond_shape = std::vector<int64_t>({1});
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}
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if (out_shape.size() == 0) {
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out_shape = std::vector<int64_t>({1});
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}
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T* dx = nullptr;
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T* dy = nullptr;
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if (x_grad != nullptr) {
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dx = dev_ctx.template Alloc<T>(x_grad);
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}
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if (y_grad != nullptr) {
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dy = dev_ctx.template Alloc<T>(y_grad);
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}
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int r = xpu::select_grad(dev_ctx.x_context(),
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cond_data,
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reinterpret_cast<const XPUType*>(dout),
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reinterpret_cast<XPUType*>(dx),
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reinterpret_cast<XPUType*>(dy),
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cond_shape,
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out_shape);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "select_grad");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(where_grad,
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XPU,
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ALL_LAYOUT,
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phi::WhereGradKernel,
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float,
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double,
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int,
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int64_t,
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phi::float16,
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phi::bfloat16) {}
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