tf.raw_ops.Conv3DBackpropInput
    
    
      
    
    
      
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Computes the gradients of 3-D convolution with respect to the input.
tf.raw_ops.Conv3DBackpropInput(
    input,
    filter,
    out_backprop,
    strides,
    padding,
    dilations=[1, 1, 1, 1, 1],
    name=None
)
| Args | 
|---|
| input | A Tensor. Must be one of the following types:half,float32,float64.
Shape[batch, depth, rows, cols, in_channels]. | 
| filter | A Tensor. Must have the same type asinput.
Shape[depth, rows, cols, in_channels, out_channels].in_channelsmust match betweeninputandfilter. | 
| out_backprop | A Tensor. Must have the same type asinput.
Backprop signal of shape[batch, out_depth, out_rows, out_cols,
out_channels]. | 
| strides | A list of intsthat has length>= 5.
1-D tensor of length 5. The stride of the sliding window for each
dimension ofinput. Must havestrides[0] = strides[4] = 1. | 
| padding | A stringfrom:"SAME", "VALID".
The type of padding algorithm to use. | 
| dilations | An optional list of ints. Defaults to[1, 1, 1, 1, 1]. | 
| name | A name for the operation (optional). | 
| Returns | 
|---|
| A Tensor. Has the same type asinput. | 
  
  
 
  
    
    
      
       
    
    
  
  
  Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
  Last updated 2023-10-06 UTC.
  
  
  
    
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