parameters: (input, ksize, strides, padding, data_format="NDHWC", name=None)
docstring: Performs the average pooling on the input.
  
    Each entry in `output` is the mean of the corresponding size `ksize`
    window in `value`.
  
    Args:
      input: A 5-D `Tensor` of shape `[batch, height, width, channels]` and type
        `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
      ksize: An int or list of `ints` that has length `1`, `3` or `5`. The size of
        the window for each dimension of the input tensor.
      strides: An int or list of `ints` that has length `1`, `3` or `5`. The
        stride of the sliding window for each dimension of the input tensor.
      padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
        See the "returns" section of `tf.nn.convolution` for details.
      data_format: A string. 'NDHWC' and 'NCDHW' are supported.
      name: Optional name for the operation.
  
    Returns:
      A `Tensor` with the same type as `value`.  The average pooled output tensor.
docstring_summary: Performs the average pooling on the input.
docstring_tokens: Performs the average pooling on the input .
function: def avg_pool3d(input, ksize, strides, padding, data_format="NDHWC", name=None):  # pylint: disable=redefined-builtin
    """Performs the average pooling on the input.
  
    Each entry in `output` is the mean of the corresponding size `ksize`
    window in `value`.
  
    Args:
      input: A 5-D `Tensor` of shape `[batch, height, width, channels]` and type
        `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
      ksize: An int or list of `ints` that has length `1`, `3` or `5`. The size of
        the window for each dimension of the input tensor.
      strides: An int or list of `ints` that has length `1`, `3` or `5`. The
        stride of the sliding window for each dimension of the input tensor.
      padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
        See the "returns" section of `tf.nn.convolution` for details.
      data_format: A string. 'NDHWC' and 'NCDHW' are supported.
      name: Optional name for the operation.
  
    Returns:
      A `Tensor` with the same type as `value`.  The average pooled output tensor.
    """
    with ops.name_scope(name, "AvgPool3D", [input]) as name:
      if data_format is None:
        data_format = "NDHWC"
      channel_index = 1 if data_format.startswith("NC") else 3
  
      ksize = _get_sequence(ksize, 3, channel_index, "ksize")
      strides = _get_sequence(strides, 3, channel_index, "strides")
  
      return gen_nn_ops.avg_pool3d(
          input,
          ksize=ksize,
          strides=strides,
          padding=padding,
          data_format=data_format,
          name=name)
function_tokens: def avg_pool3d ( input , ksize , strides , padding , data_format = "NDHWC" , name = None ) : # pylint: disable=redefined-builtin with ops . name_scope ( name , "AvgPool3D" , [ input ] ) as name : if data_format is None : data_format = "NDHWC" channel_index = 1 if data_format . startswith ( "NC" ) else 3 ksize = _get_sequence ( ksize , 3 , channel_index , "ksize" ) strides = _get_sequence ( strides , 3 , channel_index , "strides" ) return gen_nn_ops . avg_pool3d ( input , ksize = ksize , strides = strides , padding = padding , data_format = data_format , name = name )