message: Improving variable_scope documentation.
diff: @@ -1365,7 +1365,9 @@ Args:
  name: The name of the new or existing variable.
  shape: Shape of the new or existing variable.
  dtype: Type of the new or existing variable (defaults to `DT_FLOAT`).
  - initializer: Initializer for the variable if one is created.
  + initializer: Initializer for the variable if one is created. Can either be
  + an initializer object or a Tensor. If it's a Tensor, its shape must be known
  + unless validate_shape is False.
  regularizer: A (Tensor -> Tensor or None) function; the result of
  applying it on a newly created variable will be added to the collection
  @{tf.GraphKeys.REGULARIZATION_LOSSES} and can be used for regularization.
  @@ -1381,7 +1383,8 @@ Args:
  partitions for each axis (currently only one axis can be partitioned).
  validate_shape: If False, allows the variable to be initialized with a
  value of unknown shape. If True, the default, the shape of initial_value
  - must be known.
  + must be known. For this to be used the initializer must be a Tensor and
  + not an initializer object.
  use_resource: If False, creates a regular Variable. If true, creates an
  experimental ResourceVariable instead with well-defined semantics.
  Defaults to False (will later change to True). When eager execution is
  