chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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/* 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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#include "paddle/phi/kernels/activation_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/full_kernel.h"
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#include "paddle/phi/kernels/impl/activation_grad_impl.h"
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namespace phi {
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#define DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(name, functor_class) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& dout, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, &x, nullptr, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX( \
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name, functor_class, attr) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& dout, \
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float attr, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, &x, nullptr, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_DOUBLE_ATTRS_DEPX( \
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name, functor_class, attr) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& dout, \
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double attr, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, &x, nullptr, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX( \
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name, functor_class, attr1, attr2) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& dout, \
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float attr1, \
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float attr2, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr1; \
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*(attrs[1].second) = attr2; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, &x, nullptr, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_DOUBLE_ATTRS_DEPX( \
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name, functor_class, attr1, attr2) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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const DenseTensor& dout, \
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double attr1, \
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double attr2, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr1; \
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*(attrs[1].second) = attr2; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, &x, nullptr, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(name, functor_class) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& out, \
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const DenseTensor& dout, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, nullptr, &out, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT( \
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name, functor_class, attr) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& out, \
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const DenseTensor& dout, \
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float attr, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, nullptr, &out, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT( \
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name, functor_class, attr1, attr2) \
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template <typename T, typename Context> \
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void name##GradKernel(const Context& dev_ctx, \
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const DenseTensor& out, \
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const DenseTensor& dout, \
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float attr1, \
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float attr2, \
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DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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auto attrs = functor.GetAttrs(); \
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*(attrs[0].second) = attr1; \
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*(attrs[1].second) = attr2; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, nullptr, &out, &dout, dx, functor); \
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}
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#define DEFINE_CPU_ACTIVATION_GRAD_KERNEL_NODEP(name, functor_class) \
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template <typename T, typename Context> \
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void name##GradKernel( \
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const Context& dev_ctx, const DenseTensor& dout, DenseTensor* dx) { \
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funcs::functor_class<T> functor; \
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ActivationGradImpl<T, Context, funcs::functor_class<T>>( \
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dev_ctx, nullptr, nullptr, &dout, dx, functor); \
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}
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Cos, CosGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Tan, TanGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Acos, AcosGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Sin, SinGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Asin, AsinGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Atan, AtanGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Sinh, SinhGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Cosh, CoshGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Asinh, AsinhGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Acosh, AcoshGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Atanh, AtanhGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(TanhShrink, TanhShrinkGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Square, SquareGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Exp, ExpGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Expm1, Expm1GradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Reciprocal, ReciprocalGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sqrt, SqrtGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Rsqrt, RsqrtGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Relu6, Relu6GradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Softsign, SoftsignGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(LogSigmoid, LogSigmoidGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Log, LogGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Log2, Log2GradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Log10, Log10GradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Log1p, Log1pGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPX(Swish, SwishGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Relu, ReluGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Tanh, TanhGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sigmoid, SigmoidGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_NODEP(Rint, ZeroGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_NODEP(Round, ZeroGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_NODEP(Floor, ZeroGradFunctor);
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DEFINE_CPU_ACTIVATION_GRAD_KERNEL_NODEP(Ceil, ZeroGradFunctor);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_DOUBLE_ATTRS_DEPX(LeakyRelu,
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LeakyReluGradFunctor,
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alpha);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(SoftShrink,
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SoftShrinkGradFunctor,
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lambda);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(HardShrink,
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HardShrinkGradFunctor,
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threshold);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Mish,
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MishGradFunctor,
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threshold);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Celu, CELUGradFunctor, alpha);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(HardTanh,
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HardTanhGradFunctor,
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t_min,
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t_max);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(STanh,
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STanhGradFunctor,
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scale_a,
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scale_b);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_DOUBLE_ATTRS_DEPX(Softplus,
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SoftplusGradFunctor,
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beta,
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threshold);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT(HardSigmoid,
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HardSigmoidGradFunctor,
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slope,
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offset);
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DEFINE_CPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(ThresholdedRelu,
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ThresholdedReluGradFunctor,
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threshold,
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value);
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template <typename T, typename Context>
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void SiluGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& out,
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const DenseTensor& dout,
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DenseTensor* dx) {
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funcs::SiluGradFunctor<T> functor;
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ActivationGradImpl<T, Context, funcs::SiluGradFunctor<T>>(
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dev_ctx, &x, &out, &dout, dx, functor);
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}
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template <typename T, typename Context>
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void EluGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& out,
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const DenseTensor& dout,
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float alpha,
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DenseTensor* dx) {
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dev_ctx.template Alloc<T>(dx);
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if (dx->numel() == 0) {
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return;
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}
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auto x_flatten =
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EigenVector<T>::Flatten(GET_DATA_SAFELY(&x, "Input", "X", "elu_grad"));
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auto out_flatten = EigenVector<T>::Flatten(
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GET_DATA_SAFELY(&out, "Input", "Out", "elu_grad"));
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auto dout_flatten = EigenVector<T>::Flatten(
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GET_DATA_SAFELY(&dout, "Input", "dOut", "elu_grad"));
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auto dx_flatten =
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EigenVector<T>::Flatten(GET_DATA_SAFELY(dx, "Output", "dX", "elu_grad"));
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auto* place = dev_ctx.eigen_device();
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if (alpha > 0) {
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funcs::ELUGradFunctor<T> functor;
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functor.alpha = alpha;
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functor(*place, x_flatten, out_flatten, dout_flatten, dx_flatten);
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} else {
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funcs::ELUGradNegativeAlphaFunctor<T> functor;
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functor.alpha = alpha;
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functor(*place, x_flatten, out_flatten, dout_flatten, dx_flatten);
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}
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}
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template <typename T, typename Context>
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void HardSwishGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& dout,
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DenseTensor* dx) {
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funcs::HardSwishGradFunctor<T> functor;
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float threshold = 6;
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float scale = 6;
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float offset = 3;
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auto attrs = functor.GetAttrs();
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*(attrs[0].second) = threshold;
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*(attrs[1].second) = scale;
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*(attrs[2].second) = offset;
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ActivationGradImpl<T, Context, funcs::HardSwishGradFunctor<T>>(
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dev_ctx, &x, nullptr, &dout, dx, functor);
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}
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template <typename T, typename Context>
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void PowGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& dout,
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const Scalar& factor,
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DenseTensor* dx) {
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if (factor.to<float>() == 0) {
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std::vector<int64_t> vec_dims = vectorize(dx->dims());
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Full<T, Context>(dev_ctx, vec_dims, static_cast<T>(0), dx);
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return;
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}
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PADDLE_ENFORCE_NOT_NULL(
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dx,
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errors::InvalidArgument("The output DenseTensor dx can not be nullptr"));
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dev_ctx.template Alloc<T>(dx);
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auto dout_flatten = EigenVector<T>::Flatten(
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GET_DATA_SAFELY(&dout, "Input", "Out@GRAD", "PowGrad"));
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auto dx_flatten = EigenVector<T>::Flatten(
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GET_DATA_SAFELY(dx, "Output", "X@GRAD", "PowGrad"));
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auto x_flatten =
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EigenVector<T>::Flatten(GET_DATA_SAFELY(&x, "Input", "X", "PowGrad"));
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auto* place = dev_ctx.eigen_device();
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funcs::PowGradFunctor<T> functor;
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auto attrs = functor.GetAttrs();
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*(attrs[0].second) = factor.to<float>();
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functor(*place, x_flatten, nullptr, dout_flatten, dx_flatten);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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relu_grad, CPU, ALL_LAYOUT, phi::ReluGradKernel, float, double) {}
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#define PD_REGISTER_ACTIVATION_GRAD_KERNEL(name, func) \
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PD_REGISTER_KERNEL(name, CPU, ALL_LAYOUT, phi::func, float, double) {}
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#define PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(name, func) \
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PD_REGISTER_KERNEL(name, \
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CPU, \
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ALL_LAYOUT, \
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phi::func, \
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float, \
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double, \
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phi::complex64, \
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phi::complex128) {}
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#define PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(name, func) \
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PD_REGISTER_KERNEL( \
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name, CPU, ALL_LAYOUT, phi::func, float, double, phi::float16) {}
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#define PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL_WITH_COMPLEX(name, func) \
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PD_REGISTER_KERNEL(name, \
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CPU, \
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ALL_LAYOUT, \
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phi::func, \
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float, \
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double, \
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phi::float16, \
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phi::complex64, \
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phi::complex128) {}
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sin_grad, SinGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(cos_grad, CosGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(tan_grad, TanGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(acos_grad, AcosGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(asin_grad, AsinGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(atan_grad, AtanGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sinh_grad, SinhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(cosh_grad, CoshGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(asinh_grad, AsinhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(acosh_grad, AcoshGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(atanh_grad, AtanhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(tanh_grad, TanhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(hardtanh_grad, HardTanhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(leaky_relu_grad, LeakyReluGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(thresholded_relu_grad,
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ThresholdedReluGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(relu6_grad, Relu6GradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(softshrink_grad, SoftShrinkGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_shrink_grad, HardShrinkGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_shrink_grad, TanhShrinkGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(elu_grad, EluGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(silu_grad, SiluGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(mish_grad, MishGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(stanh_grad, STanhGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(reciprocal_grad,
|
||||
ReciprocalGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sqrt_grad, SqrtGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(rsqrt_grad, RsqrtGradKernel)
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||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(softplus_grad,
|
||||
SoftplusGradKernel)
|
||||
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(relu_double_grad,
|
||||
ReluDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL_WITH_COMPLEX(tanh_double_grad,
|
||||
TanhDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(leaky_relu_double_grad,
|
||||
LeakyReluDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(elu_double_grad, EluDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(sqrt_double_grad,
|
||||
SqrtDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(rsqrt_double_grad,
|
||||
RsqrtDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL_WITH_COMPLEX(softplus_double_grad,
|
||||
SoftplusDoubleGradKernel)
|
||||
|
||||
PD_REGISTER_KERNEL(tanh_triple_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::TanhTripleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(exp_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::ExpGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(expm1_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::Expm1GradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(
|
||||
logit_grad, CPU, ALL_LAYOUT, phi::LogitGradKernel, float, double) {}
|
||||
PD_REGISTER_KERNEL(square_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::SquareGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
PD_REGISTER_KERNEL(square_double_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::SquareDoubleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(sin_double_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::SinDoubleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(sin_triple_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::SinTripleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(cos_double_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::CosDoubleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(cos_triple_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::CosTripleGradKernel,
|
||||
float,
|
||||
double,
|
||||
phi::float16,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(softsign_grad,
|
||||
SoftsignGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sigmoid_grad, SigmoidGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sigmoid_double_grad,
|
||||
SigmoidDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(sigmoid_triple_grad,
|
||||
SigmoidTripleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL(hardsigmoid_grad, HardSigmoidGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(logsigmoid_grad,
|
||||
LogSigmoidGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(log_grad, LogGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(log2_grad, Log2GradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(log10_grad, Log10GradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(log1p_grad, Log1pGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL_WITH_COMPLEX(log_double_grad,
|
||||
LogDoubleGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL_WITH_COMPLEX(hardswish_grad,
|
||||
HardSwishGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL(swish_grad, SwishGradKernel)
|
||||
PD_REGISTER_ACTIVATION_GRAD_KERNEL(celu_grad, CeluGradKernel)
|
||||
PD_REGISTER_ACTIVATION_DOUBLE_GRAD_KERNEL(celu_double_grad,
|
||||
CeluDoubleGradKernel)
|
||||
|
||||
PD_REGISTER_KERNEL(rint_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::RintGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t) {}
|
||||
|
||||
PD_REGISTER_KERNEL(round_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::RoundGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(pow_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::PowGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(pow_double_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::PowDoubleGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(pow_triple_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::PowTripleGradKernel,
|
||||
float,
|
||||
double,
|
||||
int,
|
||||
int64_t,
|
||||
phi::complex64,
|
||||
phi::complex128) {}
|
||||
|
||||
PD_REGISTER_KERNEL(ceil_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::CeilGradKernel,
|
||||
float,
|
||||
double,
|
||||
uint8_t,
|
||||
int8_t,
|
||||
int16_t,
|
||||
int,
|
||||
int64_t,
|
||||
phi::float16,
|
||||
phi::bfloat16) {}
|
||||
|
||||
PD_REGISTER_KERNEL(floor_grad,
|
||||
CPU,
|
||||
ALL_LAYOUT,
|
||||
phi::FloorGradKernel,
|
||||
float,
|
||||
double,
|
||||
uint8_t,
|
||||
int8_t,
|
||||
int16_t,
|
||||
int,
|
||||
int64_t,
|
||||
phi::float16,
|
||||
phi::bfloat16) {}
|
||||
Reference in New Issue
Block a user