parameters: (value, ksize, strides, padding, data_format="NHWC", 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:
      value: A 4-D `Tensor` of shape `[batch, height, width, channels]` and type
        `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
      ksize: A list of ints that has length >= 4.
        The size of the window for each dimension of the input tensor.
      strides: A list of ints that has length >= 4.
        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 [comment here](https://www.tensorflow.org/api_docs/python/nn.html#convolution)
      data_format: A string. 'NHWC' and 'NCHW' 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_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
    """Performs the average pooling on the input.
  
    Each entry in `output` is the mean of the corresponding size `ksize`
    window in `value`.
  
    Args:
      value: A 4-D `Tensor` of shape `[batch, height, width, channels]` and type
        `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
      ksize: A list of ints that has length >= 4.
        The size of the window for each dimension of the input tensor.
      strides: A list of ints that has length >= 4.
        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 [comment here](https://www.tensorflow.org/api_docs/python/nn.html#convolution)
      data_format: A string. 'NHWC' and 'NCHW' are supported.
      name: Optional name for the operation.
  
    Returns:
      A `Tensor` with the same type as `value`.  The average pooled output tensor.
    """
    with ops.op_scope([value], name, "AvgPool") as name:
      value = ops.convert_to_tensor(value, name="input")
      return gen_nn_ops._avg_pool(value,
                                  ksize=ksize,
                                  strides=strides,
                                  padding=padding,
                                  data_format=data_format,
                                  name=name)
function_tokens: def avg_pool ( value , ksize , strides , padding , data_format = "NHWC" , name = None ) : with ops . op_scope ( [ value ] , name , "AvgPool" ) as name : value = ops . convert_to_tensor ( value , name = "input" ) return gen_nn_ops . _avg_pool ( value , ksize = ksize , strides = strides , padding = padding , data_format = data_format , name = name )