def testDistributionOfStatelessRandomUniform(self):
"""Use Pearson's Chi-squared test to test for uniformity."""
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_uniform(shape=[n],
seed=seed_t,
dtype=dtype)
y = sess.run(x, {seed_t: [565656, 121212]})
# Tests that the values are distributed amongst 10 bins with equal
# probability. 16.92 is the Chi^2 value for 9 degrees of freedom with
# p=0.05. This test is probabilistic and would be flaky if the random
# seed were not fixed.
self.assertLess(random_test_util.chi_squared(y, 10), 16.92)
def testDistributionOfUniform(self, dtype):
"""Use Pearson's Chi-squared test to test for uniformity."""
n = 1000
seed = 12
gen = random.Generator(seed=seed)
maxval = 1
if dtype.is_integer:
maxval = 100
x = gen.uniform(shape=[n], maxval=maxval, dtype=dtype).numpy()
if maxval > 1:
# Normalize y to range [0, 1).
x = x.astype(float) / maxval
# Tests that the values are distributed amongst 10 bins with equal
# probability. 16.92 is the Chi^2 value for 9 degrees of freedom with
# p=0.05. This test is probabilistic and would be flaky if the random
# seed were not fixed.
val = random_test_util.chi_squared(x, 10)
self.assertLess(val, 16.92)
def testDistributionOfStatelessRandomUniform(self):
"""Use Pearson's Chi-squared test to test for uniformity."""
with self.session() as sess, self.test_scope():
for dtype in self._random_types(include_int=True):
seed_t = array_ops.placeholder(dtypes.int32, shape=[2])
n = 1000
maxval = 1
if dtype.is_integer:
maxval = 100
x = stateless.stateless_random_uniform(
shape=[n], seed=seed_t, maxval=maxval, dtype=dtype)
y = sess.run(x, {seed_t: [565656, 121212]})
# Convert y to float and normalize its value to range [0, 1) when
# maxval != 1.
y = y.astype(float) / maxval
# Tests that the values are distributed amongst 10 bins with equal
# probability. 16.92 is the Chi^2 value for 9 degrees of freedom with
# p=0.05. This test is probabilistic and would be flaky if the random
# seed were not fixed.
self.assertLess(random_test_util.chi_squared(y, 10), 16.92)
def testDistributionOfStatelessRandomUniform(self):
"""Use Pearson's Chi-squared test to test for uniformity."""
with self.cached_session() as sess, self.test_scope():
for dtype in self._random_types(include_int=True):
seed_t = array_ops.placeholder(dtypes.int32, shape=[2])
n = 1000
maxval = 1
if dtype.is_integer:
maxval = 100
x = stateless.stateless_random_uniform(
shape=[n], seed=seed_t, maxval=maxval, dtype=dtype)
y = sess.run(x, {seed_t: [565656, 121212]})
if maxval > 1:
# Normalize y to range [0, 1).
y = y.astype(float) / maxval
# Tests that the values are distributed amongst 10 bins with equal
# probability. 16.92 is the Chi^2 value for 9 degrees of freedom with
# p=0.05. This test is probabilistic and would be flaky if the random
# seed were not fixed.
self.assertLess(random_test_util.chi_squared(y, 10), 16.92)
