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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/fluid/operators/minus_op.h"
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REGISTER_OP_CUDA_KERNEL(
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increment, ops::IncrementKernel<paddle::platform::CUDADeviceContext, float>,
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ops::IncrementKernel<paddle::platform::CUDADeviceContext, double>,
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ops::IncrementKernel<paddle::platform::CUDADeviceContext, int>,
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ops::IncrementKernel<paddle::platform::CUDADeviceContext, int64_t>)
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class IncrementKernel : 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_tensor = context.Input<framework::Tensor>("X");
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auto* out_tensor = context.Output<framework::Tensor>("Out");
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float step = context.Attr<float>("step");
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out_tensor->mutable_data<T>(context.GetPlace());
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auto& dev =
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*context.template device_context<DeviceContext>().eigen_device();
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framework::EigenScalar<T>::From(*out_tensor).device(dev) =
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framework::EigenScalar<T>::From(*x_tensor) + static_cast<T>(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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