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)