wehub-resource-sync
68 lines
2.3 KiB
C++
68 lines
2.3 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/elementwise_divide_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/core/tensor_utils.h"
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#include "paddle/phi/kernels/cpu/elementwise_grad.h"
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#include "paddle/phi/kernels/funcs/elementwise_functor.h"
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#include "paddle/phi/kernels/impl/elementwise_grad_kernel_impl.h"
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namespace phi {
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template <typename T, typename Context>
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void DivideGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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const DenseTensor& out,
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const DenseTensor& dout,
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int axis,
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DenseTensor* dx,
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DenseTensor* dy) {
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funcs::ElementwiseGradPreProcess(dout, dx);
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funcs::ElemwiseGradCompute<Context, T, DivGradDX<T>, DivGradDY<T>>(
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dev_ctx, x, y, out, dout, axis, dx, dy, DivGradDX<T>(), DivGradDY<T>());
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}
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} // namespace phi
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PD_REGISTER_KERNEL(divide_grad,
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CPU,
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ALL_LAYOUT,
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phi::DivideGradKernel,
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float,
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double,
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int8_t,
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uint8_t,
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int16_t,
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int,
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int64_t,
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bool,
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phi::complex64,
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phi::complex128) {}
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PD_REGISTER_KERNEL(divide_double_grad,
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CPU,
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ALL_LAYOUT,
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phi::DivideDoubleGradKernel,
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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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bool,
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phi::complex64,
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phi::complex128) {}
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