/* Copyright (c) 2021 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 Licnse. */ #include "paddle/fluid/operators/huber_loss_op.h" #include "paddle/fluid/operators/npu_op_runner.h" namespace paddle { namespace operators { using Tensor = framework::Tensor; template void HuberLossSub(const platform::Place& place, const aclrtStream& stream, const Tensor* x, const Tensor* y, Tensor* z) { // Calculate z = x - y z->mutable_data(x->dims(), place); const auto& runner = NpuOpRunner("Sub", {*x, *y}, {*z}, {}); runner.Run(stream); } template void HuberLossMuls(const platform::Place& place, const aclrtStream& stream, const Tensor* x, float scalar, Tensor* y) { // Calculate y = x + scale y->mutable_data(x->dims(), place); const auto& runner = NpuOpRunner("Muls", {*x}, {*y}, {{"value", scalar}}); runner.Run(stream); } template void HuberLossZerosLike(const platform::Place& place, const aclrtStream& stream, const Tensor* x, Tensor* y) { y->mutable_data(x->dims(), place); const auto& runner = NpuOpRunner("ZerosLike", {*x}, {*y}, {}); runner.Run(stream); } template void HuberLossSmoothL1Loss(const platform::Place& place, const aclrtStream& stream, const Tensor* x, const Tensor* y, float delta, Tensor* z) { z->mutable_data(x->dims(), place); const auto& runner = NpuOpRunner("SmoothL1Loss", {*x, *y}, {*z}, {{"sigma", delta}}); runner.Run(stream); } template void HuberLossSmoothL1LossGrad(const platform::Place& place, const aclrtStream& stream, const Tensor* pred, const Tensor* lab, const Tensor* dout, float sigma, Tensor* grad) { grad->mutable_data(pred->dims(), place); const auto& runner = NpuOpRunner("SmoothL1LossGrad", {*pred, *lab, *dout}, {*grad}, {{"sigma", sigma}}); runner.Run(stream); } template class HuberLossNPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto* in0 = ctx.Input("X"); auto* in1 = ctx.Input("Y"); auto* residual = ctx.Output("Residual"); auto* out = ctx.Output("Out"); auto delta = ctx.Attr("delta"); auto stream = ctx.template device_context() .stream(); auto place = ctx.GetPlace(); HuberLossSub(place, stream, in1, in0, residual); HuberLossSmoothL1Loss(place, stream, in0, in1, delta, out); HuberLossMuls(place, stream, out, delta, out); } }; template class HuberLossGradNPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto* residual = ctx.Input("Residual"); auto* dout = ctx.Input(framework::GradVarName("Out")); auto* dx = ctx.Output(framework::GradVarName("X")); auto* dy = ctx.Output(framework::GradVarName("Y")); auto delta = ctx.Attr("delta"); auto stream = ctx.template device_context() .stream(); auto place = ctx.GetPlace(); Tensor t_grad_rd; if (dx || dy) { Tensor t_zero; HuberLossZerosLike(place, stream, residual, &t_zero); HuberLossSmoothL1LossGrad(place, stream, residual, &t_zero, dout, delta, &t_grad_rd); } if (dx) { HuberLossMuls(place, stream, &t_grad_rd, -delta, dx); } if (dy) { HuberLossMuls(place, stream, &t_grad_rd, delta, dy); } } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; namespace plat = paddle::platform; REGISTER_OP_NPU_KERNEL(huber_loss, ops::HuberLossNPUKernel, ops::HuberLossNPUKernel); REGISTER_OP_NPU_KERNEL(huber_loss_grad, ops::HuberLossGradNPUKernel, ops::HuberLossGradNPUKernel);