def testDistributionOfNormal(self, dtype):
"""Use Anderson-Darling test to test distribution appears normal."""
n = 1000
gen = random.Generator(seed=1234)
x = gen.normal(shape=[n], dtype=dtype).numpy()
# The constant 2.492 is the 5% critical value for the Anderson-Darling
# test where the mean and variance are known. This test is probabilistic
# so to avoid flakiness the seed is fixed.
self.assertLess(
random_test_util.anderson_darling(x.astype(float)), 2.492)
def testDistributionOfNormal(self):
"""Use Anderson-Darling test to test distribution appears normal."""
with ops.device(xla_device_name()):
n = 1000
for dtype in {dtypes.float32}:
gen = random.Generator(seed=1234, algorithm=random.RNG_ALG_THREEFRY)
x = gen.normal(shape=[n], dtype=dtype).numpy()
# The constant 2.492 is the 5% critical value for the Anderson-Darling
# test where the mean and variance are known. This test is probabilistic
# so to avoid flakiness the seed is fixed.
self.assertLess(
random_test_util.anderson_darling(x.astype(float)), 2.492)
def testDistributionOfNormal(self):
"""Use Anderson-Darling test to test distribution appears normal."""
with ops.device(xla_device_name()):
n = 1000
for dtype in self._floats:
gen = random.Generator(seed=1234, algorithm=random.RNG_ALG_THREEFRY)
x = gen.normal(shape=[n], dtype=dtype).numpy()
# The constant 2.492 is the 5% critical value for the Anderson-Darling
# test where the mean and variance are known. This test is probabilistic
# so to avoid flakiness the seed is fixed.
self.assertLess(
random_test_util.anderson_darling(x.astype(float)), 2.492)
def testDistributionOfStatelessRandomNormal(self):
"""Use Anderson-Darling test to test distribution appears normal."""
with self.session() as sess, self.test_scope():
for dtype in self._random_types():
seed_t = array_ops.placeholder(dtypes.int32, shape=[2])
n = 1000
x = stateless.stateless_random_normal(
shape=[n], seed=seed_t, dtype=dtype)
y = sess.run(x, {seed_t: [25252, 314159]})
# The constant 2.492 is the 5% critical value for the Anderson-Darling
# test where the mean and variance are known. This test is probabilistic
# so to avoid flakiness the seed is fixed.
self.assertLess(
random_test_util.anderson_darling(y.astype(float)), 2.492)
def testDistributionOfStatelessRandomNormal(self):
"""Use Anderson-Darling test to test distribution appears normal."""
with self.cached_session() as sess, self.test_scope():
for dtype in self._random_types():
seed_t = array_ops.placeholder(dtypes.int32, shape=[2])
n = 1000
x = stateless.stateless_random_normal(
shape=[n], seed=seed_t, dtype=dtype)
y = sess.run(x, {seed_t: [25252, 314159]})
# The constant 2.492 is the 5% critical value for the Anderson-Darling
# test where the mean and variance are known. This test is probabilistic
# so to avoid flakiness the seed is fixed.
self.assertLess(
random_test_util.anderson_darling(y.astype(float)), 2.492)
