You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
91 lines
3.3 KiB
91 lines
3.3 KiB
// 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 License.
|
|
|
|
#pragma once
|
|
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/framework/operator.h"
|
|
#include "paddle/fluid/operators/math/complex_functors.h"
|
|
#include "paddle/fluid/platform/for_range.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
using Tensor = framework::Tensor;
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class AbsKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
const Tensor* x = context.Input<Tensor>("X");
|
|
Tensor* out = context.Output<Tensor>("Out");
|
|
|
|
auto numel = x->numel();
|
|
auto* x_data = x->data<T>();
|
|
auto* out_data = out->mutable_data<math::Real<T>>(
|
|
context.GetPlace(), size_t(x->numel() * sizeof(math::Real<T>)));
|
|
|
|
auto& dev_ctx = context.template device_context<DeviceContext>();
|
|
platform::ForRange<DeviceContext> for_range(dev_ctx, numel);
|
|
math::AbsFunctor<T> functor(x_data, out_data, numel);
|
|
for_range(functor);
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class AbsGradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& ctx) const {
|
|
const framework::Tensor* d_out =
|
|
ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
|
|
const framework::Tensor* x = ctx.Input<framework::Tensor>("X");
|
|
framework::Tensor* d_x =
|
|
ctx.Output<framework::Tensor>(framework::GradVarName("X"));
|
|
|
|
auto numel = d_out->numel();
|
|
auto* dout_data = d_out->data<math::Real<T>>();
|
|
auto* x_data = x->data<T>();
|
|
auto* dx_data = d_x->mutable_data<T>(
|
|
ctx.GetPlace(), static_cast<size_t>(numel * sizeof(T)));
|
|
|
|
auto& dev_ctx = ctx.template device_context<DeviceContext>();
|
|
platform::ForRange<DeviceContext> for_range(dev_ctx, numel);
|
|
math::AbsGradFunctor<T> functor(dout_data, x_data, dx_data, numel);
|
|
for_range(functor);
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class AbsDoubleGradKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& ctx) const {
|
|
const framework::Tensor* ddx = ctx.Input<framework::Tensor>("DDX");
|
|
const framework::Tensor* x = ctx.Input<framework::Tensor>("X");
|
|
framework::Tensor* ddout = ctx.Output<framework::Tensor>("DDOut");
|
|
|
|
auto numel = ddx->numel();
|
|
auto* ddx_data = ddx->data<T>();
|
|
auto* x_data = x->data<T>();
|
|
auto* ddout_data = ddout->mutable_data<T>(
|
|
ctx.GetPlace(), static_cast<size_t>(numel * sizeof(T)));
|
|
|
|
auto& dev_ctx = ctx.template device_context<DeviceContext>();
|
|
platform::ForRange<DeviceContext> for_range(dev_ctx, numel);
|
|
math::AbsGradGradFunctor<T> functor(ddx_data, x_data, ddout_data, numel);
|
|
for_range(functor);
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|