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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#include "paddle/operators/increment_op.h"
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REGISTER_OP_GPU_KERNEL(
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increment,
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paddle::operators::IncrementKernel<paddle::platform::GPUPlace, float>,
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paddle::operators::IncrementKernel<paddle::platform::GPUPlace, double>,
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paddle::operators::IncrementKernel<paddle::platform::GPUPlace, int>,
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paddle::operators::IncrementKernel<paddle::platform::GPUPlace, int64_t>);
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@ -1,40 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/framework/eigen.h"
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename Place, typename T>
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class IncrementKernel : public framework::OpKernel<T> {
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public:
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virtual void Compute(const framework::ExecutionContext& context) const {
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auto* tensor = context.Output<framework::Tensor>("Out");
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auto* in = context.Input<framework::Tensor>("X");
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tensor->mutable_data<T>(in->place());
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auto step = static_cast<T>(context.Attr<float>("step"));
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auto eigen_out = framework::EigenVector<T>::Flatten(*tensor);
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auto eigen_in = framework::EigenVector<T>::Flatten(*in);
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auto& place = context.GetEigenDevice<Place>();
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eigen_out.device(place) = eigen_in + step;
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}
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};
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} // namespace operators
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} // namespace paddle
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