def test_no_redundant_unions():
s = """{"p0" : uniform(0, 1), "p1": gaussian(0, 1),
"p2":choice([1, this.p0]), "p3":choice([2, this.p1])}"""
template = gd.gDist(s)
idxs, vals, s_N = template.theano_sampler(123)
for v in theano.gof.graph.ancestors(idxs):
assert v.owner is None or not isinstance(v.owner.op, gd.SetOp)
def pickle_helper(s):
#pickle_helper_len(s)
template = gd.gDist(s)
template2 = cPickle.loads(cPickle.dumps(template, protocol=1))
assert template.sample(5) == template2.sample(5)
idxs, vals, s_N = template.theano_sampler(5)
idxs2, vals2, s_N2 = template.theano_sampler(5)
len(idxs) == len(idxs2)
len(vals) == len(vals2)
if len(template.flatten()) != len(template2.flatten()):
tf1 = template.flatten()
tf2 = template2.flatten()
for i in range(max(len(tf1), len(tf1))):
print '----'
print i
if i < len(tf1):
print tf1[i]
else:
print 'N/A'
if i < len(tf2):
print tf2[i]
else:
print 'N/A'
raise WrongLen()
if len(template.random_nodes()) != len(template2.random_nodes()):
raise WrongRandomLen()
assert template == template2
def base_func(s, length, names, random_types, idxs, vals, res):
template = gd.gDist(s)
random_nodes = template.random_nodes()
assert len(random_nodes) == length
assert template.flatten_names() == names
assert [node.__class__.__name__ for node in random_nodes] == random_types
assert res == template.idxs_vals_to_dict_list(idxs, vals)
