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)
