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77 lines
2.5 KiB
77 lines
2.5 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/elementwise_op.h"
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#include "paddle/fluid/operators/elementwise/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 MinFunctor {
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inline HOSTDEVICE T operator()(T a, T b) const { return a < b ? a : b; }
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};
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template <typename DeviceContext, typename T>
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class ElementwiseMinKernel : 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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auto* x = ctx.Input<framework::LoDTensor>("X");
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auto* y = ctx.Input<framework::LoDTensor>("Y");
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auto* z = ctx.Output<framework::LoDTensor>("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<MinFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
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MinFunctor<T>(), z);
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}
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};
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template <typename T>
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struct MinGradDx {
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HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
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return dout * (x < y);
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}
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};
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template <typename T>
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struct MinGradDy {
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HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
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return dout * (x >= y);
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}
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};
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template <typename DeviceContext, typename T>
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class ElementwiseMinGradKernel : public ElemwiseGradKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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ElemwiseGradKernel<T>::Compute(ctx);
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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* 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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auto* out = dout; // Fake out, not used
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int axis = ctx.Attr<int>("axis");
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ElemwiseGradCompute<DeviceContext, T, MinGradDx<T>, MinGradDy<T>>(
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ctx, *x, *y, *out, *dout, axis, dx, dy, MinGradDx<T>(), MinGradDy<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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