def test_dtype(self):
def _distribution(param, dtype=None):
return Multinomial(param, 10, dtype)
utils.test_dtype_1parameter_discrete(self, _distribution)
with self.assertRaisesRegexp(TypeError, "n_experiments must be"):
Multinomial([1., 1.], tf.placeholder(tf.float32, []))
def test_dtype(self):
def _distribution(param, **kwargs):
return Multinomial(param, n_experiments=10, **kwargs)
utils.test_dtype_1parameter_discrete(self, _distribution)
with self.assertRaisesRegexp(TypeError, "n_experiments must be"):
Multinomial([1., 1.], n_experiments=tf.placeholder(tf.float32, []))
with self.assertRaisesRegexp(TypeError,
"n_experiments must be integer"):
Multinomial([1., 1.], n_experiments=2.0)
def test_dtype(self):
utils.test_dtype_1parameter_discrete(self, OnehotCategorical)
def test_dtype(self):
utils.test_dtype_1parameter_discrete(self,
UnnormalizedMultinomial,
prob_only=True)
def test_dtype(self):
utils.test_dtype_1parameter_discrete(self, Poisson)
def test_dtype(self):
utils.test_dtype_1parameter_discrete(self, Bernoulli)
