wehub-resource-sync
64 lines
2.2 KiB
Plaintext
64 lines
2.2 KiB
Plaintext
// 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/bce_loss_grad_kernel.h"
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#include <algorithm>
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#include <vector>
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#include "paddle/common/hostdevice.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/amp_type_traits.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/elementwise_base.h"
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namespace phi {
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template <typename T>
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struct BCELossGradFunctor {
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using MT = typename MPTypeTrait<T>::Type;
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MT one = static_cast<MT>(1.0f);
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MT eps = static_cast<MT>(1e-12);
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HOSTDEVICE inline T operator()(const T x, const T label, const T dout) const {
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MT x_mt = static_cast<MT>(x);
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MT term1 = max((one - x_mt) * x_mt, eps);
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return static_cast<T>(static_cast<MT>(dout) *
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(x_mt - static_cast<MT>(label)) / term1);
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}
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};
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template <typename T, typename Context>
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void BCELossGradKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& label,
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const DenseTensor& out_grad,
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DenseTensor* input_grad) {
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dev_ctx.template Alloc<T>(input_grad);
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std::vector<const DenseTensor*> ins = {&input, &label, &out_grad};
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std::vector<DenseTensor*> outs = {input_grad};
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auto functor = BCELossGradFunctor<T>();
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funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(bce_loss_grad,
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GPU,
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ALL_LAYOUT,
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phi::BCELossGradKernel,
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float,
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double,
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phi::float16) {}
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