def test_get_random_args(self, args, num, bounds):
"""Tests the utility ``_get_random_args`` using a fixed seed."""
torch = pytest.importorskip("torch")
seed = 921
rnd_args = _get_random_args(args, self.interface, num, seed, bounds)
assert len(rnd_args) == num
torch.random.manual_seed(seed)
for _rnd_args in rnd_args:
expected = tuple(
torch.rand(np.shape(arg)) * (bounds[1] - bounds[0]) + bounds[0] for arg in args
)
assert all(np.allclose(_exp, _rnd) for _exp, _rnd in zip(expected, _rnd_args))
def test_get_random_args(self, args, num, bounds):
"""Tests the utility ``_get_random_args`` using a fixed seed."""
tf = pytest.importorskip("tensorflow")
seed = 921
rnd_args = _get_random_args(args, self.interface, num, seed, bounds)
assert len(rnd_args) == num
tf.random.set_seed(seed)
for _rnd_args in rnd_args:
expected = tuple(
tf.random.uniform(tf.shape(arg)) * (bounds[1] - bounds[0]) + bounds[0]
for arg in args
)
expected = tuple(
tf.Variable(_exp) if isinstance(_arg, tf.Variable) else _exp
for _arg, _exp in zip(args, expected)
)
assert all(np.allclose(_exp, _rnd) for _exp, _rnd in zip(expected, _rnd_args))
