tensorflow:: ops:: ExtractImagePatches
  #include <array_ops.h>
  Extract patches from images and put them in the "depth" output dimension. 
Summary
Arguments:
- scope: A Scope object
 - images: 4-D Tensor with shape 
[batch, in_rows, in_cols, depth]. - ksizes: The size of the sliding window for each dimension of 
images. - strides: How far the centers of two consecutive patches are in the images. Must be: 
[1, stride_rows, stride_cols, 1]. - rates: Must be: 
[1, rate_rows, rate_cols, 1]. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches withpatch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1), followed by subsampling them spatially by a factor ofrates. This is equivalent toratein dilated (a.k.a. Atrous) convolutions. - padding: The type of padding algorithm to use.
 
Returns:
Output: 4-D Tensor with shape[batch, out_rows, out_cols, ksize_rows * ksize_cols * depth]containing image patches with sizeksize_rows x ksize_cols x depthvectorized in the "depth" dimension. Noteout_rowsandout_colsare the dimensions of the output patches.
        Constructors and Destructors | 
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        ExtractImagePatches(const ::tensorflow::Scope & scope, ::tensorflow::Input images, const gtl::ArraySlice< int > & ksizes, const gtl::ArraySlice< int > & strides, const gtl::ArraySlice< int > & rates, StringPiece padding)
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        Public attributes | 
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        operation
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        patches
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        Public functions | 
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        node() const 
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        ::tensorflow::Node *
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        operator::tensorflow::Input() const 
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        operator::tensorflow::Output() const 
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Public attributes
operation
Operation operation
patches
::tensorflow::Output patches
Public functions
ExtractImagePatches
ExtractImagePatches( const ::tensorflow::Scope & scope, ::tensorflow::Input images, const gtl::ArraySlice< int > & ksizes, const gtl::ArraySlice< int > & strides, const gtl::ArraySlice< int > & rates, StringPiece padding )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const