wehub-resource-sync
63 lines
1.8 KiB
C++
63 lines
1.8 KiB
C++
// Copyright (c) 2024 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/swiglu_grad_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/activation_functor.h"
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namespace phi {
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template <typename T, typename Context>
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void SwiGLUGradKernelImpl(const Context &dev_ctx,
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const T *x,
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const T *y,
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const T *dz,
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T *dx,
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T *dy,
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int64_t m,
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int64_t n) {
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funcs::SwiGLUGradFunctor<T> functor;
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int64_t stride;
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if (y) {
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stride = n;
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} else {
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stride = 2 * n;
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y = x + n;
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dy = dx + n;
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}
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for (int64_t i = 0; i < m; ++i) {
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for (int64_t j = 0; j < n; ++j) {
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T dx_tmp, dy_tmp;
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functor(x[i * stride + j],
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y[i * stride + j],
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dz[i * n + j],
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&dx_tmp,
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&dy_tmp);
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if (dx) {
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dx[i * stride + j] = dx_tmp;
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}
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if (dy) {
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dy[i * stride + j] = dy_tmp;
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}
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}
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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swiglu_grad, CPU, ALL_LAYOUT, phi::SwiGLUGradKernel, float, double) {}
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