tensorflow_probability/python/util/docstring.py
def expand_docstring(**kwargs):
  """Decorator to programmatically expand the docstring.

  Args:
    **kwargs: Keyword arguments to set. For each key-value pair `k` and `v`,
      the key is found as `${k}` in the docstring and replaced with `v`.

  Returns:
    Decorated function.
  """
  def _fn_wrapped(fn):
    """Original function with modified `__doc__` attribute."""
    doc = inspect.cleandoc(fn.__doc__)
    for k, v in six.iteritems(kwargs):
      # Capture each ${k} reference to replace with v.
      # We wrap the replacement in a function so no backslash escapes
      # are processed.
      pattern = r'\$\{' + str(k) + r'\}'
      doc = re.sub(pattern, lambda match: v, doc)  # pylint: disable=cell-var-from-loop
    fn.__doc__ = doc
    return fn
  return _fn_wrapped
def expand_docstring(**kwargs):
  """Decorator to programmatically expand the docstring.

  Args:
    **kwargs: Keyword arguments to set. For each key-value pair `k` and `v`,
      the key is found as `${k}` in the docstring and replaced with `v`.

  Returns:
    Decorated function.
  """
  def _fn_wrapped(fn):
    """Original function with modified `__doc__` attribute."""
    doc = inspect.cleandoc(fn.__doc__)
    for k, v in six.iteritems(kwargs):
      # Capture each ${k} reference to replace with v.
      # We wrap the replacement in a function so no backslash escapes
      # are processed.
      pattern = r'\$\{' + str(k) + r'\}'
      doc = re.sub(pattern, lambda match: v, doc)  # pylint: disable=cell-var-from-loop
    fn.__doc__ = doc
    return fn
  return _fn_wrapped
Decorator to programmatically expand the docstring.

  Args:
    **kwargs: Keyword arguments to set. For each key-value pair `k` and `v`,
      the key is found as `${k}` in the docstring and replaced with `v`.

  Returns:
    Decorated function.