def test_log_prob_shape(self): def _make_samples(shape): samples = np.zeros(shape) samples = samples.reshape((-1, shape[-1])) samples[:, 0] = 1 return samples.reshape(shape) utils.test_1parameter_log_prob_shape_one_rank_less( self, OnehotCategorical, _make_samples, _make_samples)
def test_log_prob_shape(self): def _proxy_distribution(logits): return Concrete(1., logits) def _make_samples(shape): samples = np.ones(shape, dtype=np.float32) return np.log(samples / samples.sum(axis=-1, keepdims=True)) utils.test_1parameter_log_prob_shape_one_rank_less( self, _proxy_distribution, np.ones, _make_samples)
def test_log_prob_shape(self): def _make_samples(shape): samples = np.ones(shape, dtype=np.float32) return samples / samples.sum(axis=-1, keepdims=True) # TODO: This failed with a bug in Tensorflow, waiting fix. # https://github.com/tensorflow/tensorflow/issues/8391 # _test_static([3, None], [3, 2, 1, None], [3, 2, 3]) utils.test_1parameter_log_prob_shape_one_rank_less( self, Dirichlet, np.ones, _make_samples)
def test_log_prob_shape(self): def _distribution(param): return Multinomial(param, 10) def _make_samples(shape): samples = np.zeros(shape) samples = samples.reshape((-1, shape[-1])) samples[:, 0] = 1 return samples.reshape(shape) utils.test_1parameter_log_prob_shape_one_rank_less( self, _distribution, _make_samples, _make_samples)