def test_none_Constant():
""" Tests equals
We had an error in the past with unpickling
"""
o1 = Constant(NoneTypeT(), None, name='NoneConst')
o2 = Constant(NoneTypeT(), None, name='NoneConst')
assert o1.equals(o2)
assert NoneConst.equals(o1)
assert o1.equals(NoneConst)
assert NoneConst.equals(o2)
assert o2.equals(NoneConst)
# This trigger equals that returned the wrong answer in the past.
import six.moves.cPickle as pickle
import theano
from theano import tensor
x = tensor.vector('x')
y = tensor.argmax(x)
kwargs = {}
# We can't pickle DebugMode
if theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
kwargs = {'mode': 'FAST_RUN'}
f = theano.function([x], [y], **kwargs)
pickle.loads(pickle.dumps(f))
def make_node(self, rv, val):
"""Make an `Observed` random variable.
Parameters
----------
rv: RandomVariable
The distribution from which `val` is assumed to be a sample value.
val: Variable
The observed value.
"""
val = as_tensor_variable(val)
if rv is not None:
if not hasattr(rv, "type") or rv.type.convert_variable(val) is None:
raise TypeError(
(
"`rv` and `val` do not have compatible types:"
f" rv={rv}, val={val}"
)
)
else:
rv = NoneConst.clone()
inputs = [rv, val]
return Apply(self, inputs, [val.type()])
def test_none_Constant():
""" Tests equals
We had an error in the past with unpickling
"""
o1 = Constant(NoneTypeT(), None, name='NoneConst')
o2 = Constant(NoneTypeT(), None, name='NoneConst')
assert o1.equals(o2)
assert NoneConst.equals(o1)
assert o1.equals(NoneConst)
assert NoneConst.equals(o2)
assert o2.equals(NoneConst)
# This trigger equals that returned the wrong answer in the past.
import cPickle
import theano
from theano import tensor
x = tensor.vector('x')
y = tensor.argmax(x)
f = theano.function([x], [y])
cPickle.loads(cPickle.dumps(f))
