def test_empirical_from_trace(another_simple_model):
with another_simple_model:
step = pm.Metropolis()
trace = pm.sample(100, step=step, chains=1, tune=0)
emp = Empirical(trace)
assert emp.histogram.shape[0].eval() == 100
trace = pm.sample(100, step=step, chains=4, tune=0)
emp = Empirical(trace)
assert emp.histogram.shape[0].eval() == 400
def __init__(self,
n_particles=100,
jitter=.01,
model=None,
kernel=test_functions.rbf,
temperature=1,
scale_cost_to_minibatch=False,
start=None,
histogram=None,
random_seed=None,
local_rv=None):
if histogram is None:
histogram = Empirical.from_noise(
n_particles,
jitter=jitter,
scale_cost_to_minibatch=scale_cost_to_minibatch,
start=start,
model=model,
local_rv=local_rv,
random_seed=random_seed)
super(SVGD, self).__init__(KSD,
histogram,
kernel,
op_kwargs=dict(temperature=temperature),
model=model,
random_seed=random_seed)
def __init__(self, n_particles=100, jitter=1, model=None, start=None,
random_seed=None, estimator=KSD, kernel=test_functions.rbf, **kwargs):
if kwargs.get('local_rv') is not None:
raise opvi.AEVBInferenceError('SVGD does not support local groups')
empirical = Empirical(
size=n_particles, jitter=jitter,
start=start, model=model, random_seed=random_seed)
super().__init__(approx=empirical, estimator=estimator, kernel=kernel, **kwargs)
def __init__(self, n_particles=100, jitter=.01, model=None, kernel=test_functions.rbf,
start=None, histogram=None, seed=None, local_rv=None):
if histogram is None:
histogram = Empirical.from_noise(
n_particles, jitter=jitter, start=start, model=model, local_rv=local_rv, seed=seed)
super(SVGD, self).__init__(
KSD, histogram,
kernel,
model=model, seed=seed)
def __init__(self, n_particles=100, jitter=.01, model=None, kernel=test_functions.rbf,
temperature=1, scale_cost_to_minibatch=False, start=None,
random_seed=None, local_rv=None):
empirical = Empirical.from_noise(
n_particles, jitter=jitter,
scale_cost_to_minibatch=scale_cost_to_minibatch,
start=start, model=model, local_rv=local_rv, random_seed=random_seed)
super(SVGD, self).__init__(
KSD, empirical,
kernel, op_kwargs=dict(temperature=temperature),
model=model, random_seed=random_seed)
