def __init__(self, batch_shape=(), event_shape=(), validate_args=None):
self._batch_shape = batch_shape
self._event_shape = event_shape
if validate_args is not None:
self._validate_args = validate_args
if self._validate_args:
for param, constraint in self.arg_constraints.items():
if is_dependent(constraint):
continue # skip constraints that cannot be checked
if not np.all(constraint(getattr(self, param))):
raise ValueError(
"The parameter {} has invalid values".format(param))
super(Distribution, self).__init__()
def __init__(self, batch_shape=(), event_shape=(), validate_args=None):
self._batch_shape = batch_shape
self._event_shape = event_shape
if validate_args is not None:
self._validate_args = validate_args
if self._validate_args:
for param, constraint in self.arg_constraints.items():
if param not in self.__dict__ and isinstance(getattr(type(self), param), lazy_property):
continue
if is_dependent(constraint):
continue # skip constraints that cannot be checked
is_valid = np.all(constraint(getattr(self, param)))
if not_jax_tracer(is_valid):
if not is_valid:
raise ValueError("The parameter {} has invalid values".format(param))
super(Distribution, self).__init__()
