def test_tensors_handles_constant_strat(constant):
constants = []
kwargs = dict(dtype=np.int8, shape=(2, 3))
if constant is not None:
kwargs["constant"] = constant
@given(x=tensors(**kwargs))
def f(x):
constants.append(x.constant)
f()
assert len(set(constants)) > 1
def test_tensors_with_grad(dtype, data: st.DataObject, shape, grad_dtype,
grad_elements_bounds):
tensor = data.draw(
tensors(
dtype=dtype,
shape=shape,
include_grad=True,
grad_dtype=grad_dtype,
grad_elements_bounds=grad_elements_bounds,
),
label="tensor",
)
assert isinstance(tensor, Tensor)
assert tensor.dtype == dtype
assert isinstance(tensor.grad, np.ndarray)
assert tensor.grad.shape == tensor.shape
assert tensor.grad.dtype == (grad_dtype
if grad_dtype is not None else tensor.dtype)
if grad_elements_bounds is not None:
assert np.all((100 <= tensor.grad) & (tensor.grad <= 200))
else:
assert np.all((-10 <= tensor.grad) & (tensor.grad <= 10))
@settings(deadline=None)
@backprop_test_factory(
mygrad_func=power,
true_func=np.power,
index_to_bnds={0: (1, 10), 1: (-3, 3)},
num_arrays=2,
)
def test_power_bkwd():
pass
@given(
t=tensors(
dtype=np.float64,
shape=hnp.array_shapes(min_dims=0, min_side=0),
elements=st.floats(-1e6, 1e6),
constant=False,
)
)
def test_x_pow_0_special_case(t):
y = t ** 0
y.backward()
assert_allclose(y.data, np.ones_like(t))
assert_allclose(t.grad, np.zeros_like(t))
@given(
t=tensors(
dtype=np.float64,
shape=hnp.array_shapes(min_dims=0, min_side=0),
elements=st.floats(1e-10, 1e6),
def test_tensors_dtype(dtype, data: st.DataObject):
tensor = data.draw(tensors(dtype=dtype, shape=(2, 3)), label="tensor")
assert isinstance(tensor, Tensor)
assert tensor.dtype == dtype
assert tensor.grad is None
def test_tensors_shape(shape, data: st.DataObject):
tensor = data.draw(tensors(np.int8, shape=shape), label="tensor")
assert isinstance(tensor, Tensor)
assert tensor.shape == shape
assert tensor.grad is None
def test_tensors_static_constant(constant: bool, data: st.DataObject):
tensor = data.draw(tensors(np.int8, (2, 3), constant=constant),
label="tensor")
assert isinstance(tensor, Tensor)
assert tensor.constant is constant
assert tensor.grad is None