tensorflow::
    
   ops::
    
   FusedResizeAndPadConv2D
  
  
   #include <nn_ops.h>
  
  Performs a resize and padding as a preprocess during a convolution.
Summary
It's often possible to do spatial transformations more efficiently as part of the packing stage of a convolution, so this op allows for an optimized implementation where these stages are fused together. This prevents the need to write out the intermediate results as whole tensors, reducing memory pressure, and we can get some latency gains by merging the transformation calculations. The data_format attribute for Conv2D isn't supported by this op, and defaults to 'NHWC' order. Internally this op uses a single per-graph scratch buffer, which means that it will block if multiple versions are being run in parallel. This is because this operator is primarily an optimization to minimize memory usage.
Args:
- scope: A Scope object
 - 
     input: 4-D with shape
     
[batch, in_height, in_width, in_channels]. - 
     size: A 1-D int32
     
      Tensor
     
     of 2 elements:
     
new_height, new_width. The new size for the images. - 
     paddings: A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of
     
input. - 
     filter: 4-D with shape
     
[filter_height, filter_width, in_channels, out_channels]. - 
     strides: 1-D of length 4. The stride of the sliding window for each dimension of
     
input. Must be in the same order as the dimension specified with format. - padding: The type of padding algorithm to use.
 
   Optional attributes (see
   
    
     Attrs
    
   
   ):
   
- resize_align_corners: If true, the centers of the 4 corner pixels of the input and output tensors are aligned, preserving the values at the corner pixels. Defaults to false.
 
Returns:
- 
     
Output: The output tensor. 
     Constructors and Destructors | 
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       FusedResizeAndPadConv2D
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      input, ::
      
       tensorflow::Input
      
      size, ::
      
       tensorflow::Input
      
      paddings, ::
      
       tensorflow::Input
      
      filter, StringPiece mode, const gtl::ArraySlice< int > & strides, StringPiece padding)
     
      | 
   |
     
      
       FusedResizeAndPadConv2D
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      input, ::
      
       tensorflow::Input
      
      size, ::
      
       tensorflow::Input
      
      paddings, ::
      
       tensorflow::Input
      
      filter, StringPiece mode, const gtl::ArraySlice< int > & strides, StringPiece padding, const
      
       FusedResizeAndPadConv2D::Attrs
      
      & attrs)
     
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     Public attributes | 
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       operation
      
     
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       output
      
     
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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 static functions | 
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       ResizeAlignCorners
      
      (bool x)
     
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     Structs | 
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      tensorflow::
       | 
    
      Optional attribute setters for FusedResizeAndPadConv2D .  | 
   
Public attributes
Public functions
FusedResizeAndPadConv2D
FusedResizeAndPadConv2D( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input size, ::tensorflow::Input paddings, ::tensorflow::Input filter, StringPiece mode, const gtl::ArraySlice< int > & strides, StringPiece padding )
FusedResizeAndPadConv2D
FusedResizeAndPadConv2D( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input size, ::tensorflow::Input paddings, ::tensorflow::Input filter, StringPiece mode, const gtl::ArraySlice< int > & strides, StringPiece padding, const FusedResizeAndPadConv2D::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const