wehub-resource-sync
58 lines
1.9 KiB
C++
58 lines
1.9 KiB
C++
/* Copyright (c) 2022 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 "paddle/phi/kernels/funcs/axis_utils.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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#include "paddle/phi/kernels/funcs/softmax.h"
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#include "paddle/phi/kernels/softmax_grad_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void SoftmaxGradKernel(const Context& dev_ctx,
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const DenseTensor& out,
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const DenseTensor& out_grad,
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int axis,
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DenseTensor* x_grad) {
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dev_ctx.template Alloc<T>(x_grad);
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const int rank = x_grad->dims().size();
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// For 0D Tensor
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if (rank == 0) {
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funcs::set_constant(dev_ctx, x_grad, static_cast<T>(0.0));
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return;
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}
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// For zero-sized Tensor
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if (x_grad->numel() == 0) {
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return;
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}
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const int calc_axis = funcs::CanonicalAxis(axis, rank);
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int64_t axis_dim = x_grad->dims()[calc_axis];
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const int64_t n = funcs::SizeToAxis(calc_axis, x_grad->dims());
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const int64_t d = funcs::SizeFromAxis(calc_axis, x_grad->dims());
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DenseTensor dX_2d, Out_2d, dOut_2d;
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dX_2d.ShareDataWith(*x_grad).Resize({n, d});
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Out_2d.ShareDataWith(out).Resize({n, d});
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dOut_2d.ShareDataWith(out_grad).Resize({n, d});
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funcs::SoftmaxGradFunctor<Context, T>()(
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dev_ctx, axis_dim, &Out_2d, &dOut_2d, &dX_2d);
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}
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} // namespace phi
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