/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/phi/kernels/activation_grad_kernel.h" #include "paddle/fluid/platform/device/gpu/gpu_device_function.h" #include "paddle/phi/backends/gpu/gpu_context.h" #include "paddle/phi/common/bfloat16.h" #include "paddle/phi/common/float16.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/elementwise_base.h" #include "paddle/phi/kernels/impl/activation_grad_impl.h" namespace phi { template void ActivationGradGPUImpl(const Context& dev_ctx, const DenseTensor* x, const DenseTensor* out, const DenseTensor* d_out, DenseTensor* d_x, const Functor& functor) { if (static_cast(Functor::FwdDeps()) & static_cast(funcs::ActBwdOpFwdDeps::kDepOut)) { PADDLE_ENFORCE_NOT_NULL( out, errors::NotFound("The input DenseTensor Out can not be nullptr")); } PADDLE_ENFORCE_NOT_NULL( d_out, errors::NotFound("The input DenseTensor dOut can not be nullptr")); PADDLE_ENFORCE_NOT_NULL( d_x, errors::NotFound("The output DenseTensor dX can not be nullptr")); if (!out) { out = d_out; // fake out } if (static_cast(Functor::FwdDeps()) & static_cast(funcs::ActBwdOpFwdDeps::kDepX)) { PADDLE_ENFORCE_NOT_NULL( x, errors::NotFound("The input DenseTensor X can not be nullptr")); } else { VLOG(10) << "Inplace activation of Op Functor: " << typeid(Functor).name(); x = d_x; } dev_ctx.template Alloc(d_x); std::vector ins = {d_out}; std::vector outs = {d_x}; if (static_cast(Functor::FwdDeps()) == static_cast(funcs::ActBwdOpFwdDeps::kDepOut)) { // Only need forward output Out ins.push_back(out); funcs::ElementwiseKernel(dev_ctx, ins, &outs, functor); } else if (static_cast(Functor::FwdDeps()) == static_cast(funcs::ActBwdOpFwdDeps::kDepX)) { // Only need forward input X ins.push_back(x); funcs::ElementwiseKernel(dev_ctx, ins, &outs, functor); } else { funcs::ElementwiseKernel(dev_ctx, ins, &outs, functor); } } #define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(name, functor_class) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& x, \ const DenseTensor& dout, \ DenseTensor* dx) { \ funcs::functor_class functor; \ ActivationGradGPUImpl>( \ dev_ctx, &x, nullptr, &dout, dx, functor); \ } #define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX( \ name, functor_class, attr) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& x, \ const DenseTensor& dout, \ float attr, \ DenseTensor* dx) { \ funcs::functor_class functor; \ auto attrs = functor.GetAttrs(); \ *(attrs[0].second) = attr; \ ActivationGradGPUImpl>( \ dev_ctx, &x, nullptr, &dout, dx, functor); \ } #define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX( \ name, functor_class, attr1, attr2) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& x, \ const DenseTensor& dout, \ float attr1, \ float attr2, \ DenseTensor* dx) { \ funcs::functor_class functor; \ auto attrs = functor.GetAttrs(); \ *(attrs[0].second) = attr1; \ *(attrs[1].second) = attr2; \ ActivationGradGPUImpl>( \ dev_ctx, &x, nullptr, &dout, dx, functor); \ } #define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(name, functor_class) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& out, \ const DenseTensor& dout, \ DenseTensor* dx) { \ funcs::functor_class functor; \ ActivationGradGPUImpl>( \ dev_ctx, nullptr, &out, &dout, dx, functor); \ } #define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT( \ name, functor_class, attr) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& out, \ const DenseTensor& dout, \ float attr, \ DenseTensor* dx) { \ funcs::functor_class functor; \ auto attrs = functor.GetAttrs(); \ *(attrs[0].second) = attr; \ ActivationGradGPUImpl>( \ dev_ctx, nullptr, &out, &dout, dx, functor); \ } #define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT( \ name, functor_class, attr1, attr2) \ template \ void name##GradKernel(const Context& dev_ctx, \ const DenseTensor& out, \ const DenseTensor& dout, \ float attr1, \ float attr2, \ DenseTensor* dx) { \ funcs::functor_class functor; \ auto attrs = functor.GetAttrs(); \ *(attrs[0].second) = attr1; \ *(attrs[1].second) = attr2; \ ActivationGradGPUImpl>( \ dev_ctx, nullptr, &out, &dout, dx, functor); \ } #define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(name, functor_class) \ template \ void name##GradKernel( \ const Context& dev_ctx, const DenseTensor& dout, DenseTensor* dx) { \ funcs::functor_class functor; \ ActivationGradGPUImpl>( \ dev_ctx, nullptr, nullptr, &dout, dx, functor); \ } DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Relu, CudaReluGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Tanh, CudaTanhGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sigmoid, CudaSigmoidGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Round, CudaZeroGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Floor, CudaZeroGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Ceil, CudaZeroGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Cos, CudaCosGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Tan, CudaTanGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Acos, CudaAcosGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Sin, CudaSinGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Asin, CudaAsinGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Atan, CudaAtanGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Sinh, CudaSinhGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Cosh, CudaCoshGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Asinh, CudaAsinhGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Acosh, CudaAcoshGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Atanh, CudaAtanhGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(TanhShrink, CudaTanhShrinkGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Silu, CudaSiluGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Square, CudaSquareGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Exp, CudaExpGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Expm1, CudaExpm1GradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Reciprocal, CudaReciprocalGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sqrt, CudaSqrtGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Rsqrt, CudaRsqrtGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Softsign, CudaSoftsignGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(LogSigmoid, CudaLogSigmoidGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log, CudaLogGradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log2, CudaLog2GradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log10, CudaLog10GradFunctor); DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log1p, CudaLog1pGradFunctor); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(LeakyRelu, CudaLeakyReluGradFunctor, alpha); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(ThresholdedRelu, CudaThresholdedReluGradFunctor, threshold); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(SoftShrink, CudaSoftShrinkGradFunctor, lambda); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(HardShrink, CudaHardShrinkGradFunctor, threshold); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Swish, CudaSwishGradFunctor, beta); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Mish, CudaMishGradFunctor, threshold); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Celu, CudaCELUGradFunctor, alpha); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT(Relu6, CudaRelu6GradFunctor, threshold); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(HardTanh, CudaHardTanhGradFunctor, t_min, t_max); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(STanh, CudaSTanhGradFunctor, scale_a, scale_b); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(Softplus, CudaSoftplusGradFunctor, beta, threshold); DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT(HardSigmoid, CudaHardSigmoidGradFunctor, slope, offset); template void EluGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& out, const DenseTensor& dout, float alpha, DenseTensor* dx) { dev_ctx.template Alloc(dx); std::vector ins = {&dout, &out}; std::vector outs = {dx}; if (alpha > 0) { funcs::CudaELUGradFunctor functor; functor.alpha = alpha; funcs::ElementwiseKernel(dev_ctx, ins, &outs, functor); } else { funcs::CudaELUGradNegativeAlphaFunctor functor; functor.alpha = alpha; ins.push_back(&x); funcs::ElementwiseKernel(dev_ctx, ins, &outs, functor); } } template void HardSwishGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& dout, float threshold, float scale, float offset, DenseTensor* dx) { funcs::CudaHardSwishGradFunctor functor; auto attrs = functor.GetAttrs(); *(attrs[0].second) = threshold; *(attrs[1].second) = scale; *(attrs[2].second) = offset; ActivationGradGPUImpl>( dev_ctx, &x, nullptr, &dout, dx, functor); } } // namespace phi #ifdef PADDLE_WITH_HIP PD_REGISTER_KERNEL(relu_grad, GPU, ALL_LAYOUT, phi::ReluGradKernel, float, double, phi::dtype::float16) {} PD_REGISTER_KERNEL(relu_double_grad, GPU, ALL_LAYOUT, phi::ReluDoubleGradKernel, float, double, phi::dtype::float16) {} #else PD_REGISTER_KERNEL(relu_grad, GPU, ALL_LAYOUT, phi::ReluGradKernel, float, double, phi::dtype::float16, phi::dtype::bfloat16) {} PD_REGISTER_KERNEL(relu_double_grad, GPU, ALL_LAYOUT, phi::ReluDoubleGradKernel, float, double, phi::dtype::float16, phi::dtype::bfloat16) {} #endif #define PD_REGISTER_ACTIVATION_GRAD_KERNEL(name, func) \ PD_REGISTER_KERNEL(name, \ GPU, \ ALL_LAYOUT, \ phi::func, \ float, \ double, \ phi::dtype::float16, \ phi::dtype::bfloat16) {} PD_REGISTER_ACTIVATION_GRAD_KERNEL(sin_grad, SinGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(cos_grad, CosGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(tan_grad, TanGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(acos_grad, AcosGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(asin_grad, AsinGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(atan_grad, AtanGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sinh_grad, SinhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(cosh_grad, CoshGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(asinh_grad, AsinhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(acosh_grad, AcoshGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(atanh_grad, AtanhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_grad, TanhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_double_grad, TanhDoubleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_triple_grad, TanhTripleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_tanh_grad, HardTanhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(leaky_relu_grad, LeakyReluGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(leaky_relu_double_grad, LeakyReluDoubleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(thresholded_relu_grad, ThresholdedReluGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(relu6_grad, Relu6GradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(mish_grad, MishGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(stanh_grad, STanhGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(reciprocal_grad, ReciprocalGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(softplus_grad, SoftplusGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sqrt_grad, SqrtGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sqrt_double_grad, SqrtDoubleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(rsqrt_grad, RsqrtGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(rsqrt_double_grad, RsqrtDoubleGradKernel) PD_REGISTER_KERNEL(exp_grad, GPU, ALL_LAYOUT, phi::ExpGradKernel, float, double, int, int64_t, phi::dtype::float16) {} PD_REGISTER_ACTIVATION_GRAD_KERNEL(softshrink_grad, SoftShrinkGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_shrink_grad, HardShrinkGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_shrink_grad, TanhShrinkGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(silu_grad, SiluGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(elu_grad, EluGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(elu_double_grad, EluDoubleGradKernel) PD_REGISTER_KERNEL(expm1_grad, GPU, ALL_LAYOUT, phi::Expm1GradKernel, float, double, phi::dtype::float16) {} PD_REGISTER_KERNEL(logit_grad, GPU, ALL_LAYOUT, phi::LogitGradKernel, float, double, phi::dtype::float16) {} PD_REGISTER_KERNEL(square_grad, GPU, ALL_LAYOUT, phi::SquareGradKernel, float, double, int, int64_t, phi::dtype::float16, phi::dtype::bfloat16) {} PD_REGISTER_KERNEL(square_double_grad, GPU, ALL_LAYOUT, phi::SquareDoubleGradKernel, float, double, int, int64_t, phi::dtype::float16, phi::dtype::bfloat16) {} PD_REGISTER_KERNEL(sin_double_grad, GPU, ALL_LAYOUT, phi::SinDoubleGradKernel, float, double, int, int64_t, phi::dtype::float16) {} PD_REGISTER_ACTIVATION_GRAD_KERNEL(softsign_grad, SoftsignGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_grad, SigmoidGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_double_grad, SigmoidDoubleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_triple_grad, SigmoidTripleGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_sigmoid_grad, HardSigmoidGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(logsigmoid_grad, LogSigmoidGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(log_grad, LogGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(log2_grad, Log2GradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(log10_grad, Log10GradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(log1p_grad, Log1pGradKernel) PD_REGISTER_KERNEL(log_double_grad, GPU, ALL_LAYOUT, phi::LogDoubleGradKernel, float, double, phi::dtype::float16) {} PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_swish_grad, HardSwishGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(swish_grad, SwishGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(round_grad, RoundGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(floor_grad, FloorGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(ceil_grad, CeilGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(celu_grad, CeluGradKernel) PD_REGISTER_ACTIVATION_GRAD_KERNEL(celu_double_grad, CeluDoubleGradKernel) PD_REGISTER_KERNEL(pow_grad, GPU, ALL_LAYOUT, phi::PowGradKernel, float, double, int, int64_t, phi::dtype::float16, phi::dtype::bfloat16) {}