def test_basics(self, rng_ctor):
random = RandomStream(seed=utt.fetch_seed(), rng_ctor=rng_ctor)
with pytest.raises(ValueError):
random.uniform(0, 1, size=(2, 2), rng=np.random.default_rng(23))
with pytest.raises(AttributeError):
random.blah
assert hasattr(random, "standard_normal")
with pytest.raises(AttributeError):
np_random = RandomStream(namespace=np, rng_ctor=rng_ctor)
np_random.ndarray
fn = function([],
random.uniform(0, 1, size=(2, 2)),
updates=random.updates())
fn_val0 = fn()
fn_val1 = fn()
rng_seed = np.random.SeedSequence(utt.fetch_seed())
(rng_seed, ) = rng_seed.spawn(1)
rng = random.rng_ctor(rng_seed)
numpy_val0 = rng.uniform(0, 1, size=(2, 2))
numpy_val1 = rng.uniform(0, 1, size=(2, 2))
assert np.allclose(fn_val0, numpy_val0)
assert np.allclose(fn_val1, numpy_val1)
def test_uniform(self, rng_ctor):
# Test that RandomStream.uniform generates the same results as numpy
# Check over two calls to see if the random state is correctly updated.
random = RandomStream(utt.fetch_seed(), rng_ctor=rng_ctor)
fn = function([], random.uniform(-1, 1, size=(2, 2)))
fn_val0 = fn()
fn_val1 = fn()
rng_seed = np.random.SeedSequence(utt.fetch_seed())
(rng_seed, ) = rng_seed.spawn(1)
rng = random.rng_ctor(rng_seed)
numpy_val0 = rng.uniform(-1, 1, size=(2, 2))
numpy_val1 = rng.uniform(-1, 1, size=(2, 2))
assert np.allclose(fn_val0, numpy_val0)
assert np.allclose(fn_val1, numpy_val1)
def test_seed(self, rng_ctor):
init_seed = 234
random = RandomStream(init_seed, rng_ctor=rng_ctor)
assert random.default_instance_seed == init_seed
new_seed = 43298
random.seed(new_seed)
rng_seed = np.random.SeedSequence(new_seed)
assert random.gen_seedgen.entropy == rng_seed.entropy
random.seed()
rng_seed = np.random.SeedSequence(init_seed)
assert random.gen_seedgen.entropy == rng_seed.entropy
# Reset the seed
random.seed(new_seed)
# Check state updates
_ = random.normal()
# Now, change the seed when there are state updates
random.seed(new_seed)
update_seed = np.random.SeedSequence(new_seed)
(update_seed, ) = update_seed.spawn(1)
ref_rng = random.rng_ctor(update_seed)
state_rng = random.state_updates[0][0].get_value(borrow=True)
if hasattr(state_rng, "get_state"):
ref_state = ref_rng.get_state()
random_state = state_rng.get_state()
assert np.array_equal(random_state[1], ref_state[1])
assert random_state[0] == ref_state[0]
assert random_state[2:] == ref_state[2:]
else:
ref_state = ref_rng.__getstate__()
random_state = state_rng.__getstate__()
assert random_state["bit_generator"] == ref_state["bit_generator"]
assert random_state["state"] == ref_state["state"]
