tensorflow_probability/python/internal/distribution_util.py
def _largest_integer_by_dtype(dt):
  """Helper returning the largest integer exactly representable by dtype."""
  if not _is_known_dtype(dt):
    raise TypeError("Unrecognized dtype: {}".format(dt.name))
  if dt.is_floating:
    return int(2**(np.finfo(dt.as_numpy_dtype).nmant + 1))
  if dt.is_integer:
    return np.iinfo(dt.as_numpy_dtype).max
  if dt.base_dtype == tf.bool:
    return int(1)
  # We actually can't land here but keep the case for completeness.
  raise TypeError("Unrecognized dtype: {}".format(dt.name))
def _largest_integer_by_dtype(dt):
  """Helper returning the largest integer exactly representable by dtype."""
  if not _is_known_dtype(dt):
    raise TypeError("Unrecognized dtype: {}".format(dt.name))
  if dt.is_floating:
    return int(2**(np.finfo(dt.as_numpy_dtype).nmant + 1))
  if dt.is_integer:
    return np.iinfo(dt.as_numpy_dtype).max
  if dt.base_dtype == tf.bool:
    return int(1)
  # We actually can't land here but keep the case for completeness.
  raise TypeError("Unrecognized dtype: {}".format(dt.name))
Helper returning the largest integer exactly representable by dtype.