message: Fix the formatting of doctests.
diff: @@ -1448,12 +1448,10 @@ def random_uniform_variable(shape, low, high, dtype=None, name=None, seed=None):
  Example:
  - # TensorFlow example
  >>> kvar = tf.keras.backend.random_uniform_variable((2,3), 0, 1)
  >>> kvar
  <tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=...,
  dtype=float32)>
  -
  """
  if dtype is None:
  dtype = floatx()
  @@ -1484,12 +1482,10 @@ def random_normal_variable(shape, mean, scale, dtype=None, name=None,
  Example:
  - # TensorFlow example
  >>> kvar = tf.keras.backend.random_normal_variable((2,3), 0, 1)
  >>> kvar
  <tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=...,
  dtype=float32)>
  -
  """
  if dtype is None:
  dtype = floatx()
  @@ -1626,27 +1622,23 @@ def dot(x, y):
  Examples:
  - # dot product between tensors
  >>> x = tf.keras.backend.placeholder(shape=(2, 3))
  >>> y = tf.keras.backend.placeholder(shape=(3, 4))
  >>> xy = tf.keras.backend.dot(x, y)
  >>> xy
  <tf.Tensor ... shape=(2, 4) dtype=float32>
  - # dot product between tensors
  >>> x = tf.keras.backend.placeholder(shape=(32, 28, 3))
  >>> y = tf.keras.backend.placeholder(shape=(3, 4))
  >>> xy = tf.keras.backend.dot(x, y)
  >>> xy
  <tf.Tensor ... shape=(32, 28, 4) dtype=float32>
  - # Theano-like behavior example
  >>> x = tf.keras.backend.random_uniform_variable(shape=(2, 3), low=0, high=1)
  >>> y = tf.keras.backend.ones((4, 3, 5))
  >>> xy = tf.keras.backend.dot(x, y)
  >>> tf.keras.backend.int_shape(xy)
  (2, 4, 5)
  -
  """
  if ndim(x) is not None and (ndim(x) > 2 or ndim(y) > 2):
  x_shape = []
  @@ -2398,7 +2390,6 @@ def maximum(x, y):
  Examples:
  - # maximum of two tensors
  >>> x = tf.Variable([[1, 2], [3, 4]])
  >>> y = tf.Variable([[2, 1], [0, -1]])
  >>> m = tf.keras.backend.maximum(x, y)
  @@ -2406,7 +2397,6 @@ def maximum(x, y):
  <tf.Tensor: shape=(2, 2), dtype=int32, numpy=
  array([[2, 2],
  [3, 4]], dtype=int32)>
  -
  """
  return math_ops.maximum(x, y)
  