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105 lines
2.9 KiB
105 lines
2.9 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/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/platform/transform.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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using platform::Transform;
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template <typename T>
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class PReluFunctor {
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public:
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explicit PReluFunctor(const T* alpha) : alpha_(alpha) {}
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HOSTDEVICE T operator()(const T& x) const {
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if (x > 0)
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return x;
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else
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return x * (*alpha_);
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}
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private:
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const T* alpha_;
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};
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template <typename DeviceContext, typename T>
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class PReluKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* x = context.Input<Tensor>("X");
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auto* alpha = context.Input<Tensor>("Alpha");
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auto* out = context.Output<Tensor>("Out");
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const T* x_ptr = x->data<T>();
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T* o_ptr = out->mutable_data<T>(context.GetPlace());
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auto* alpha_ptr = alpha->data<T>();
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int numel = x->numel();
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Transform<DeviceContext> trans;
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trans(context.template device_context<DeviceContext>(), x_ptr,
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x_ptr + numel, o_ptr, PReluFunctor<T>(alpha_ptr));
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}
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};
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template <typename T>
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class PReluGradFunctor {
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public:
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explicit PReluGradFunctor(const T* alpha) : alpha_(alpha) {}
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HOSTDEVICE T operator()(const T& out, const T& dout) const {
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if (out > 0)
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return dout;
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else
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return dout * (*alpha_);
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}
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private:
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const T* alpha_;
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};
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template <typename DeviceContext, typename T>
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class PReluGradKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* dx = context.Output<Tensor>(framework::GradVarName("X"));
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auto* dout = context.Input<Tensor>(framework::GradVarName("Out"));
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auto* out = context.Input<Tensor>("Out");
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auto* alpha = context.Input<Tensor>("Alpha");
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auto* alpha_ptr = alpha->data<T>();
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T* dx_ptr = dx->mutable_data<T>(context.GetPlace());
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const T* dout_ptr = dout->data<T>();
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const T* out_ptr = out->data<T>();
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int numel = dx->numel();
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Transform<DeviceContext> trans;
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trans(context.template device_context<DeviceContext>(), out_ptr,
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out_ptr + numel, dout_ptr, dx_ptr, PReluGradFunctor<T>(alpha_ptr));
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// TODO(Zhuoyuan): add dalpha upgrade when GPU kernels ready
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}
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};
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} // namespace operators
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} // namespace paddle
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