def test_pickling(self):
data = np.random.uniform(size=(1000, 10))
minibatches = DataSampler(data, batchsize=50)
gen = generator(minibatches)
pickle.loads(pickle.dumps(gen))
bad_gen = generator(integers())
with pytest.raises(Exception):
pickle.dumps(bad_gen)
def test_gen_cloning_with_shape_change(self):
data = floatX(np.random.uniform(size=(1000, 10)))
minibatches = DataSampler(data, batchsize=50)
gen = generator(minibatches)
gen_r = tt_rng().normal(size=gen.shape).T
X = gen.dot(gen_r)
res, _ = theano.scan(lambda x: x.sum(), X, n_steps=X.shape[0])
assert res.eval().shape == (50, )
shared = theano.shared(data)
res2 = theano.clone(res, {gen: shared**2})
assert res2.eval().shape == (1000, )