提交 568270f3 编写于 作者: Y Yang Yu

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上级 c365c61a
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#include "paddle/operators/increment_op.h"
REGISTER_OP_GPU_KERNEL(
increment,
paddle::operators::IncrementKernel<paddle::platform::GPUPlace, float>,
paddle::operators::IncrementKernel<paddle::platform::GPUPlace, double>,
paddle::operators::IncrementKernel<paddle::platform::GPUPlace, int>,
paddle::operators::IncrementKernel<paddle::platform::GPUPlace, int64_t>);
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/framework/eigen.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace operators {
template <typename Place, typename T>
class IncrementKernel : public framework::OpKernel<T> {
public:
virtual void Compute(const framework::ExecutionContext& context) const {
auto* tensor = context.Output<framework::Tensor>("Out");
auto* in = context.Input<framework::Tensor>("X");
tensor->mutable_data<T>(in->place());
auto step = static_cast<T>(context.Attr<float>("step"));
auto eigen_out = framework::EigenVector<T>::Flatten(*tensor);
auto eigen_in = framework::EigenVector<T>::Flatten(*in);
auto& place = context.GetEigenDevice<Place>();
eigen_out.device(place) = eigen_in + step;
}
};
} // namespace operators
} // namespace paddle
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