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							71 lines
						
					
					
						
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							71 lines
						
					
					
						
							2.4 KiB
						
					
					
				/* Copyright (c) 2016 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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#pragma once
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#include "paddle/fluid/operators/elementwise_op_function.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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struct SubFunctor {
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  inline HOSTDEVICE T operator()(T a, T b) const { return a - b; }
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};
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template <typename DeviceContext, typename T>
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class ElementwiseSubKernel : public framework::OpKernel<T> {
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 public:
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  void Compute(const framework::ExecutionContext& ctx) const override {
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    using Tensor = framework::Tensor;
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    auto* x = ctx.Input<Tensor>("X");
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    auto* y = ctx.Input<Tensor>("Y");
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    auto* z = ctx.Output<Tensor>("Out");
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    z->mutable_data<T>(ctx.GetPlace());
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    int axis = ctx.Attr<int>("axis");
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    ElementwiseComputeEx<SubFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
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                                                          SubFunctor<T>(), z);
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  }
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};
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template <typename T>
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struct SubGradDX {
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  HOSTDEVICE T operator()(T x, T y, T out, T dout) const { return dout; }
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};
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template <typename T>
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struct SubGradDY {
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  HOSTDEVICE T operator()(T x, T y, T out, T dout) const { return -dout; }
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};
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template <typename DeviceContext, typename T>
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class ElementwiseSubGradKernel : public framework::OpKernel<T> {
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 public:
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  void Compute(const framework::ExecutionContext& ctx) const override {
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    using Tensor = framework::Tensor;
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    auto* x = ctx.Input<Tensor>("X");
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    auto* y = ctx.Input<Tensor>("Y");
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    auto* out = ctx.Input<Tensor>("Out");
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    auto* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
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    auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
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    auto* dy = ctx.Output<Tensor>(framework::GradVarName("Y"));
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    int axis = ctx.Attr<int>("axis");
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    ElemwiseGradCompute<DeviceContext, T, SubGradDX<T>, SubGradDY<T>>(
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        ctx, *x, *y, *out, *dout, axis, dx, dy, SubGradDX<T>(), SubGradDY<T>());
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  }
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};
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}  // namespace operators
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}  // namespace paddle
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