def test_convert_variable():
test_type = TensorType(config.floatX, [False, False])
test_var = test_type()
test_type2 = TensorType(config.floatX, [True, False])
test_var2 = test_type2()
res = test_type.convert_variable(test_var)
assert res is test_var
res = test_type.convert_variable(test_var2)
assert res is test_var2
res = test_type2.convert_variable(test_var)
assert res.type == test_type2
test_type3 = TensorType(config.floatX, [True, False, True])
test_var3 = test_type3()
res = test_type2.convert_variable(test_var3)
assert res is None
const_var = at.as_tensor([[1, 2], [3, 4]], dtype=config.floatX)
res = test_type.convert_variable(const_var)
assert res is const_var
def test_fixed_shape_convert_variable():
# These are equivalent types
t1 = TensorType("float64", (True, True))
t2 = TensorType("float64", (1, 1))
assert t1 == t2
assert t1.shape == t2.shape
t2_var = t2()
res = t2.convert_variable(t2_var)
assert res is t2_var
res = t1.convert_variable(t2_var)
assert res is t2_var
t1_var = t1()
res = t2.convert_variable(t1_var)
assert res is t1_var
t3 = TensorType("float64", (False, True))
t3_var = t3()
res = t2.convert_variable(t3_var)
assert isinstance(res.owner.op, Rebroadcast)
t3 = TensorType("float64", (False, False))
t4 = TensorType("float64", (3, 2))
t4_var = t4()
assert t3.shape == (None, None)
res = t3.convert_variable(t4_var)
assert res.type == t4
assert res.type.shape == (3, 2)
