parameters: (inputs, name=None, data_format='channels_last')
return_statement: return layer.apply(inputs)
docstring: Flattens an input tensor while preserving the batch axis (axis 0).
  
    Args:
      inputs: Tensor input.
      name: The name of the layer (string).
      data_format: A string, one of `channels_last` (default) or `channels_first`.
        The ordering of the dimensions in the inputs.
        `channels_last` corresponds to inputs with shape
        `(batch, height, width, channels)` while `channels_first` corresponds to
        inputs with shape `(batch, channels, height, width)`.
  
    Returns:
      Reshaped tensor.
  
    Examples:
  
    ```
      x = tf.compat.v1.placeholder(shape=(None, 4, 4), dtype='float32')
      y = flatten(x)
      # now `y` has shape `(None, 16)`
  
      x = tf.compat.v1.placeholder(shape=(None, 3, None), dtype='float32')
      y = flatten(x)
      # now `y` has shape `(None, None)`
    ```
docstring_summary: Flattens an input tensor while preserving the batch axis (axis 0).
docstring_tokens: Flattens an input tensor while preserving the batch axis ( axis 0 ) .
function: def flatten(inputs, name=None, data_format='channels_last'):
    """Flattens an input tensor while preserving the batch axis (axis 0).
  
    Args:
      inputs: Tensor input.
      name: The name of the layer (string).
      data_format: A string, one of `channels_last` (default) or `channels_first`.
        The ordering of the dimensions in the inputs.
        `channels_last` corresponds to inputs with shape
        `(batch, height, width, channels)` while `channels_first` corresponds to
        inputs with shape `(batch, channels, height, width)`.
  
    Returns:
      Reshaped tensor.
  
    Examples:
  
    ```
      x = tf.compat.v1.placeholder(shape=(None, 4, 4), dtype='float32')
      y = flatten(x)
      # now `y` has shape `(None, 16)`
  
      x = tf.compat.v1.placeholder(shape=(None, 3, None), dtype='float32')
      y = flatten(x)
      # now `y` has shape `(None, None)`
    ```
    """
    warnings.warn('`tf.layers.flatten` is deprecated and '
                  'will be removed in a future version. '
                  'Please use `tf.keras.layers.Flatten` instead.')
    layer = Flatten(name=name, data_format=data_format)
    return layer.apply(inputs)
function_tokens: def flatten ( inputs , name = None , data_format = 'channels_last' ) : warnings . warn ( '`tf.layers.flatten` is deprecated and ' 'will be removed in a future version. ' 'Please use `tf.keras.layers.Flatten` instead.' ) layer = Flatten ( name = name , data_format = data_format ) return layer . apply ( inputs )