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93 lines
3.2 KiB
93 lines
3.2 KiB
/* Copyright (c) 2018 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 <cmath>
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#include <type_traits>
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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 PowFunctor {
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inline HOSTDEVICE T operator()(T a, T b) const {
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// TODO(wujionghao): A potential speed improvement is supporting different
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// types in C++.
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#ifdef __CUDA_ARCH__
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// On CUDAPlace, std::pow(3, 1) calls pow(float, float), and
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// it will return a float number like 2.99... , which floor to 2
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// when cast to int by default and it is wrong.
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// Use llrint to cast it to the nearest integer, which is 3.
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if (std::is_integral<T>::value) {
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return std::llrint(std::pow(a, b));
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}
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#endif
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return std::pow(a, b);
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}
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};
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template <typename DeviceContext, typename T>
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class ElementwisePowKernel : 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::LoDTensor;
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auto* x = ctx.Input<Tensor>("X");
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PADDLE_ENFORCE_EQ(x != nullptr, true,
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platform::errors::NotFound(
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"Cannot get input Variable X, Variable name = %s",
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ctx.InputName("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<PowFunctor<T>, DeviceContext, T>(ctx, x, y, axis,
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PowFunctor<T>(), z);
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}
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};
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template <typename T>
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struct PowGradDX {
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HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
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return dout * y * std::pow(x, y - 1);
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}
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};
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template <typename T>
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struct PowGradDY {
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HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
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return dout * std::log(x) * std::pow(x, y);
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}
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};
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template <typename DeviceContext, typename T>
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class ElementwisePowGradKernel : 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* out = dout;
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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, PowGradDX<T>, PowGradDY<T>>(
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ctx, *x, *y, *out, *dout, axis, dx, dy, PowGradDX<T>(), PowGradDY<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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