def _check_user_params(self, **kwargs):
params = self._user_params = self.user_params
formula = kwargs.pop("f")
if params is None:
return False
if formula is not None:
raise opvi.ParametrizationError(
"No formula is allowed if user params are provided")
if not isinstance(params, dict):
raise TypeError("params should be a dict")
if not all(isinstance(k, int) for k in params.keys()):
raise TypeError("params should be a dict with `int` keys")
needed = set(range(len(params)))
givens = set(params.keys())
if givens != needed:
raise opvi.ParametrizationError(
"Passed parameters do not have a needed set of keys, "
"they should be equal, needed {needed}, got {givens}".format(
givens=list(sorted(givens)),
needed="[0, 1, ..., %d]" % len(formula.flows)))
for i in needed:
flow = flows.flow_for_params(params[i])
flow_keys = set(flow.__param_spec__)
user_keys = set(params[i].keys())
if flow_keys != user_keys:
raise opvi.ParametrizationError(
"Passed parameters for flow `{i}` ({cls}) do not have a needed set of keys, "
"they should be equal, needed {needed}, got {givens}".
format(givens=user_keys,
needed=flow_keys,
i=i,
cls=flow.__name__))
return True
def create_shared_params(self,
trace=None,
size=None,
jitter=1,
start=None):
if trace is None:
if size is None:
raise opvi.ParametrizationError(
"Need `trace` or `size` to initialize")
else:
if start is None:
start = self.model.initial_point
else:
start_ = self.model.initial_point.copy()
self.model.update_start_vals(start_, start)
start = start_
start = pm.floatX(DictToArrayBijection.map(start))
# Initialize particles
histogram = np.tile(start, (size, 1))
histogram += pm.floatX(
np.random.normal(0, jitter, histogram.shape))
else:
histogram = np.empty((len(trace) * len(trace.chains), self.ddim))
i = 0
for t in trace.chains:
for j in range(len(trace)):
histogram[i] = DictToArrayBijection.map(trace.point(j, t))
i += 1
return dict(histogram=aesara.shared(pm.floatX(histogram), "histogram"))
def __init__(self, op, tf):
if not isinstance(op, KSD):
raise opvi.ParametrizationError("Op should be KSD")
ObjectiveFunction.__init__(self, op, tf)