tensorflow_probability/python/sts/structural_time_series.py
def _canonicalize_param_vals_as_map(self, param_vals):
    """If given an ordered list of parameter values, build a name:value map.

    This is a utility method that allows parameter values to be specified as
    either lists or dicts, by transforming lists to a canonical dict
    representation.

    Args:
      param_vals: Python list (or other `iterable`) of `Tensor` values
        corresponding to the parameters listed in `self.parameters`,
        OR a map (Python `dict`) of parameter names to values.

    Returns:
      param_map: Python `dict` mapping from the names given in `self.parameters`
        to the specified parameter values.
    """
    if hasattr(param_vals, 'keys'):
      param_map = param_vals
    else:
      param_map = {p.name: v for (p, v) in zip(self.parameters, param_vals)}

    return param_map
def _canonicalize_param_vals_as_map(self, param_vals):
    """If given an ordered list of parameter values, build a name:value map.

    This is a utility method that allows parameter values to be specified as
    either lists or dicts, by transforming lists to a canonical dict
    representation.

    Args:
      param_vals: Python list (or other `iterable`) of `Tensor` values
        corresponding to the parameters listed in `self.parameters`,
        OR a map (Python `dict`) of parameter names to values.

    Returns:
      param_map: Python `dict` mapping from the names given in `self.parameters`
        to the specified parameter values.
    """
    if hasattr(param_vals, 'keys'):
      param_map = param_vals
    else:
      param_map = {p.name: v for (p, v) in zip(self.parameters, param_vals)}

    return param_map
If given an ordered list of parameter values, build a name:value map.

    This is a utility method that allows parameter values to be specified as
    either lists or dicts, by transforming lists to a canonical dict
    representation.

    Args:
      param_vals: Python list (or other `iterable`) of `Tensor` values
        corresponding to the parameters listed in `self.parameters`,
        OR a map (Python `dict`) of parameter names to values.

    Returns:
      param_map: Python `dict` mapping from the names given in `self.parameters`
        to the specified parameter values.