def test_updates_add():
up1 = Updates()
up2 = Updates()
a = theano.shared('a')
b = theano.shared('b')
assert not up1 + up2
up1[a] = 5
# test that addition works
assert up1
assert up1 + up2
assert not up2
assert len(up1 + up2) == 1
assert (up1 + up2)[a] == 5
up2[b] = 7
assert up1
assert up1 + up2
assert up2
assert len(up1 + up2) == 2
assert (up1 + up2)[a] == 5
assert (up1 + up2)[b] == 7
assert a in (up1 + up2)
assert b in (up1 + up2)
# this works even though there is a collision
# because values all match
assert len(up1 + up1 + up1) == 1
up2[a] = 8 # a gets different value in up1 and up2
try:
up1 + up2
assert 0
except KeyError:
pass
# reassigning to a key works fine right?
up2[a] = 10
def test_updates_setitem(self):
ok = True
up = Updates()
sv = theano.shared('asdf')
# keys have to be SharedVariables
self.assertRaises(TypeError, up.__setitem__, 5, 7)
self.assertRaises(TypeError, up.__setitem__, T.vector(), 7)
up[theano.shared(88)] = 7
def test_updates_setitem():
ok = True
up = Updates()
sv = theano.shared('asdf')
# keys have to be SharedVariables
try:
up[5] = 7
ok = False
except TypeError:
ok = True
assert ok
# keys have to be SharedVariables
try:
up[T.vector()] = 7
ok = False
except TypeError:
ok = True
assert ok
# keys have to be SharedVariables
up[theano.shared(88)] = 7
try:
arg = tensor.as_tensor_variable(arg)
except TypeError:
# This happens for Random States for e.g. but it is a good way
# to make sure no input is a cuda ndarrays
pass
scan_inputs += [arg]
scan_outs = local_op(*scan_inputs)
if type(scan_outs) not in (list, tuple):
scan_outs = [scan_outs]
##
### Step 9. Figure out which outs are update rules for shared variables
### and so on ...
##
update_map = Updates()
def remove_dimensions(outs, steps_return, offsets=None):
out_ls = []
for idx, out in enumerate(outs):
if idx in steps_return:
if steps_return[idx] > 1:
out_ls.append(out[-steps_return[idx]:])
else:
out_ls.append(out[-1])
else:
if offsets is None:
out_ls.append(out)
else:
out_ls.append(out[offsets[idx]:])
return out_ls
def test_updates_init(self):
self.assertRaises(TypeError, Updates, dict(d=3))
sv = theano.shared('asdf')
Updates({sv: 3})