wehub-resource-sync
75 lines
2.4 KiB
C++
75 lines
2.4 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 "paddle/phi/kernels/funcs/for_range.h"
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#include "paddle/phi/kernels/funcs/tril_triu_compute.h"
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#include "paddle/phi/kernels/tril_triu_grad_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void TrilTriuGradKernel(const Context& dev_ctx,
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const DenseTensor& out_grad,
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int diagonal,
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bool lower,
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DenseTensor* x_grad) {
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auto* dx_data = dev_ctx.template Alloc<T>(x_grad);
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// Early return for empty tensor to avoid invalid CUDA kernel launch
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if (out_grad.numel() == 0) {
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return;
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}
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const auto* dout_data = out_grad.data<T>();
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const auto& dims = out_grad.dims();
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const auto H = dims[dims.size() - 2];
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const auto W = dims[dims.size() - 1];
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funcs::ForRange<Context> for_range(dev_ctx,
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static_cast<size_t>(out_grad.numel()));
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funcs::TrilTriuCompute<T> tril_triu_grad_computer(
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dout_data, diagonal, lower, H, W, dx_data);
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for_range(tril_triu_grad_computer);
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}
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template <typename T, typename Context>
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void TrilGradKernel(const Context& dev_ctx,
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const DenseTensor& out_grad,
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int diagonal,
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DenseTensor* x_grad) {
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if (x_grad && x_grad->numel() == 0) {
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dev_ctx.template Alloc<T>(x_grad);
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return;
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}
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TrilTriuGradKernel<T, Context>(dev_ctx, out_grad, diagonal, true, x_grad);
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}
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template <typename T, typename Context>
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void TriuGradKernel(const Context& dev_ctx,
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const DenseTensor& out_grad,
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int diagonal,
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DenseTensor* x_grad) {
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if (x_grad && x_grad->numel() == 0) {
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dev_ctx.template Alloc<T>(x_grad);
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return;
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}
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TrilTriuGradKernel<T, Context>(dev_ctx, out_grad, diagonal, false, x_grad);
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}
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} // namespace phi
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