/* 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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#ifndef TENSORFLOW_CORE_KERNELS_EXTRACT_IMAGE_PATCHES_OP_H_
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#define TENSORFLOW_CORE_KERNELS_EXTRACT_IMAGE_PATCHES_OP_H_
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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#include "tensorflow/core/framework/tensor_shape.h"
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#include "tensorflow/core/framework/tensor_types.h"
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namespace tensorflow {
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namespace functor {
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template <typename Device, typename T>
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struct ExtractImagePatchesForward {
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void operator()(const Device& d, typename TTypes<T, 4>::ConstTensor input,
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int patch_rows, int patch_cols, int stride_rows,
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int stride_cols, int rate_rows, int rate_cols,
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const Eigen::PaddingType& padding,
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typename TTypes<T, 4>::Tensor output) {
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// Need to swap row/col when calling Eigen, because our data is in
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// NHWC format while Eigen assumes NWHC format.
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const int64 N = std::max(input.size(), output.size());
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if (N <= std::numeric_limits<Index32>::max()) {
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auto output_32bit = To32Bit(output);
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output_32bit.device(d) =
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To32Bit(input)
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.extract_image_patches(patch_cols, patch_rows, stride_cols,
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stride_rows, rate_cols, rate_rows, padding)
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.reshape(output_32bit.dimensions());
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} else {
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output.device(d) =
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input
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.extract_image_patches(patch_cols, patch_rows, stride_cols,
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stride_rows, rate_cols, rate_rows, padding)
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.reshape(output.dimensions());
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}
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}
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};
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} // namespace functor
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} // namespace tensorflow
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#endif // TENSORFLOW_CORE_KERNELS_EXTRACT_IMAGE_PATCHES_OP_H_
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