/* Copyright 2016 The TensorFlow 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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==============================================================================*/
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// Helper functions to run 3d pooling on GPU using CuDNN.
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#ifndef TENSORFLOW_CORE_KERNELS_CUDNN_POOLING_GPU_H_
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#define TENSORFLOW_CORE_KERNELS_CUDNN_POOLING_GPU_H_
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#include <array>
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#include "tensorflow/core/framework/op_kernel.h"
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#if GOOGLE_CUDA
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#include "tensorflow/core/platform/stream_executor.h"
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#endif
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#include "tensorflow/core/util/padding.h"
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namespace tensorflow {
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#if GOOGLE_CUDA
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// Runs (avg/max)pooling on GPU.
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// Dimension order for all array arguments is: x, y, z.
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template <typename T>
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class DnnPooling3dOp {
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public:
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static void Compute(OpKernelContext* context,
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se::dnn::PoolingMode pooling_mode,
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const std::array<int64, 3>& size,
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const std::array<int64, 3>& stride,
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const std::array<int64, 3>& padding,
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TensorFormat data_format, const Tensor& tensor_in,
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Tensor* output);
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};
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// Computes the gradient of (avg/max)pooling on GPU.
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// Dimension order for all array arguments is: x, y, z.
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template <typename T>
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class DnnPooling3dGradOp {
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public:
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static void Compute(OpKernelContext* context,
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se::dnn::PoolingMode pooling_mode,
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const std::array<int64, 3>& window,
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const std::array<int64, 3>& stride,
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const std::array<int64, 3>& padding,
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const std::array<int64, 3>& output_size,
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TensorFormat data_format, const Tensor& out_backprop,
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const TensorShape& tensor_in_shape,
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const Tensor* tensor_in, const Tensor* tensor_out,
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Tensor* input_backprop);
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};
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#endif
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} // namespace tensorflow
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#endif // TENSORFLOW_CORE_KERNELS_CUDNN_POOLING_GPU_H_
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