tf.extract_volume_patches
    
    
      
    
    
      
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Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.
tf.extract_volume_patches(
    input: Annotated[Any, TV_ExtractVolumePatches_T],
    ksizes,
    strides,
    padding: str,
    name=None
) -> Annotated[Any, TV_ExtractVolumePatches_T]
| Args | 
|---|
| input | A Tensor. Must be one of the following types:float32,float64,int32,uint8,int16,int8,int64,bfloat16,uint16,half,uint32,uint64.
5-D Tensor with shape[batch, in_planes, in_rows, in_cols, depth]. | 
| ksizes | A list of intsthat has length>= 5.
The size of the sliding window for each dimension ofinput. | 
| strides | A list of intsthat has length>= 5.
1-D of length 5. How far the centers of two consecutive patches are ininput. Must be:[1, stride_planes, stride_rows, stride_cols, 1]. | 
| padding | A stringfrom:"SAME", "VALID".
The type of padding algorithm to use.The size-related attributes are specified as follows: ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
strides = [1, stride_planes, strides_rows, strides_cols, 1]
 | 
| name | A name for the operation (optional). | 
| Returns | 
|---|
| A Tensor. Has the same type asinput. | 
  
  
 
  
    
    
      
       
    
    
  
  
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  Last updated 2024-04-26 UTC.
  
  
  
    
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