message: Fix `Reshape` layer docs.
diff: @@ -402,41 +402,45 @@ class Activation(Layer):
  @keras_export('keras.layers.Reshape')
  class Reshape(Layer):
  - """Reshapes an output to a certain shape.
  -
  - Arguments:
  - target_shape: Target shape. Tuple of integers,
  - does not include the samples dimension (batch size).
  + """Layer that reshapes inputs into the given shape.
  Input shape:
  - Arbitrary, although all dimensions in the input shaped must be fixed.
  - Use the keyword argument `input_shape`
  - (tuple of integers, does not include the samples axis)
  - when using this layer as the first layer in a model.
  + Arbitrary, although all dimensions in the input shape must be known/fixed.
  + Use the keyword argument `input_shape` (tuple of integers, does not include
  + the samples/batch size axis) when using this layer as the first layer
  + in a model.
  Output shape:
  `(batch_size,) + target_shape`
  Example:
  - ```python
  - # as first layer in a Sequential model
  - model = Sequential()
  - model.add(Reshape((3, 4), input_shape=(12,)))
  - # now: model.output_shape == (None, 3, 4)
  - # note: `None` is the batch dimension
  -
  - # as intermediate layer in a Sequential model
  - model.add(Reshape((6, 2)))
  - # now: model.output_shape == (None, 6, 2)
  -
  - # also supports shape inference using `-1` as dimension
  - model.add(Reshape((-1, 2, 2)))
  - # now: model.output_shape == (None, None, 2, 2)
  - ```
  + >>> # as first layer in a Sequential model
  + >>> model = tf.keras.Sequential()
  + >>> model.add(tf.keras.layers.Reshape((3, 4), input_shape=(12,)))
  + >>> # model.output_shape == (None, 3, 4), `None` is the batch size.
  + >>> model.output_shape
  + (None, 3, 4)
  +
  + >>> # as intermediate layer in a Sequential model
  + >>> model.add(tf.keras.layers.Reshape((6, 2)))
  + >>> model.output_shape
  + (None, 6, 2)
  +
  + >>> # also supports shape inference using `-1` as dimension
  + >>> model.add(tf.keras.layers.Reshape((-1, 2, 2)))
  + >>> model.output_shape
  + (None, None, 2, 2)
  """
  def __init__(self, target_shape, **kwargs):
  + """Creates a `tf.keras.layers.Reshape` layer instance.
  +
  + Args:
  + target_shape: Target shape. Tuple of integers, does not include the
  + samples dimension (batch size).
  + **kwargs: Any additional layer keyword arguments.
  + """
  super(Reshape, self).__init__(**kwargs)
  self.target_shape = tuple(target_shape)
  