def test_unroll1():
i = T.arange(100)
A = theano.shared(np.random.normal(size=(10,10)))
def fn1(seq, acc):
return T.dot(acc, A)
# Unrolled scan
outputs, updates = unrolled_scan(fn1, name='fn1',
sequences=[i], outputs_info=[T.ones_like(A)],
unroll=1
)
f_fn1 = theano.function([], outputs[-1], name='fn1')
def test_last_out_only():
i = T.arange(100)
A = theano.shared(np.random.normal(size=(10,10)))
def fn1(seq, acc):
return T.dot(acc, A)
# Normal Theano scan
outputs, updates = theano.scan(fn1, name='fn1',
sequences=[i], outputs_info=[T.ones_like(A)]
)
f_fn1 = theano.function([], outputs[-1], name='fn1')
res_normal = f_fn1()
# Unrolled scan
outputs, updates = unrolled_scan(fn1, name='fn1',
sequences=[i], outputs_info=[T.ones_like(A)],
unroll=10
)
f_fn1 = theano.function([], outputs[-1], name='fn1')
res_unrolled = f_fn1()
assert np.allclose(res_normal, res_unrolled)