def test_properties(a, constant, scalar, creator):
array = np.asarray(a)
if creator:
ref = Operation()
tensor = Tensor(a, constant=constant, _creator=ref, _scalar_only=scalar)
else:
tensor = Tensor(a, constant=constant, _scalar_only=scalar)
assert tensor.ndim == array.ndim
assert tensor.shape == array.shape
assert tensor.size == array.size
assert len(tensor) == len(array)
assert tensor.dtype == array.dtype
assert_equal(actual=tensor.data, desired=a)
assert (not creator) or tensor.creator is ref
assert_equal(actual=Tensor(x).data, desired=x)
@given(x=hnp.arrays(dtype=float, shape=hnp.array_shapes()))
def test_items(x):
""" verify that tensor.item() mirrors array.item()"""
tensor = Tensor(x)
try:
value = x.item()
assert_allclose(value, tensor.item())
except ValueError:
with raises(ValueError):
tensor.item()
op = Operation()
dtype_strat = st.sampled_from((
None,
int,
float,
np.int8,
np.int16,
np.int32,
np.int64,
np.float16,
np.float32,
np.float64,
))
dtype_strat_numpy = st.sampled_from((np.int8, np.int16, np.int32, np.int64,
np.float16, np.float32, np.float64))