def __init__(self,
default_variable=None,
mode: tc.optional(
tc.enum(MAX_VAL, MAX_ABS_VAL, MAX_INDICATOR,
MAX_ABS_INDICATOR, MIN_VAL, MIN_ABS_VAL,
MIN_INDICATOR, MIN_ABS_INDICATOR, PROB,
PROB_INDICATOR)) = None,
seed=None,
params=None,
owner=None,
prefs: tc.optional(is_pref_set) = None):
if seed is None:
seed = get_global_seed()
random_state = np.random.RandomState([seed])
reset_variable_shape_flexibility = False
if mode in {PROB, PROB_INDICATOR} and default_variable is None:
default_variable = [[0], [0]]
reset_variable_shape_flexibility = True
super().__init__(
default_variable=default_variable,
mode=mode,
random_state=random_state,
params=params,
owner=owner,
prefs=prefs,
)
if reset_variable_shape_flexibility:
self._variable_shape_flexibility = DefaultsFlexibility.FLEXIBLE
def __init__(self,
default_variable=None,
mode: tc.enum(MAX_VAL, MAX_ABS_VAL, MAX_INDICATOR,
MAX_ABS_INDICATOR, MIN_VAL, MIN_ABS_VAL,
MIN_INDICATOR, MIN_ABS_INDICATOR, PROB,
PROB_INDICATOR) = MAX_VAL,
seed=None,
params=None,
owner=None,
prefs: is_pref_set = None):
if seed is None:
seed = get_global_seed()
random_state = np.random.RandomState([seed])
if not hasattr(self, "stateful_attributes"):
self.stateful_attributes = ["random_state"]
reset_default_variable_flexibility = False
if mode in {PROB, PROB_INDICATOR} and default_variable is None:
default_variable = [[0], [0]]
reset_default_variable_flexibility = True
super().__init__(
default_variable=default_variable,
mode=mode,
random_state=random_state,
params=params,
owner=owner,
prefs=prefs,
)
if reset_default_variable_flexibility:
self._default_variable_flexibility = DefaultsFlexibility.FLEXIBLE
def __deepcopy__(self, memo):
new = super().__deepcopy__(memo)
# ensure copy does not have identical name
register_category(new, Function_Base, new.name, FunctionRegistry)
try:
# HACK: Make sure any copies are re-seeded to avoid dependent RNG.
new.random_state.seed([get_global_seed()])
except:
pass
return new
def _seed_setter(value, owning_component, context):
if value in {None, DEFAULT_SEED}:
value = get_global_seed()
value = int(value)
owning_component.parameters.random_state._set(
np.random.RandomState([value]),
context
)
return value