def test_log_prob_shape(self):
def _make_param(shape):
samples = np.zeros(shape)
samples = samples.reshape((-1, shape[-1]))
samples[:, 0] = 1
return samples.reshape(shape)
def _make_given(shape, dtype):
samples = np.zeros(shape)
samples = samples.reshape((-1, shape[-1]))
samples[:, 0] = 1
return samples.reshape(shape).astype(dtype)
utils.test_1parameter_log_prob_shape_same(
self, partial(Implicit, value_shape=[]), _make_param, _make_given)
utils.test_1parameter_log_prob_shape_same(
self, partial(Implicit, value_shape=5), _make_param, _make_given)
def test_log_prob_shape(self):
def _proxy_distribution(logits):
return BinConcrete(1., logits)
utils.test_1parameter_log_prob_shape_same(self, _proxy_distribution,
np.ones, np.ones)
def test_log_prob_shape(self):
def _distribution(param):
return Binomial(param, 10)
utils.test_1parameter_log_prob_shape_same(self, _distribution, np.ones,
np.ones)
def test_log_prob_shape(self):
utils.test_1parameter_log_prob_shape_same(self, Poisson, np.ones,
np.ones)
def test_log_prob_shape(self):
utils.test_1parameter_log_prob_shape_same(self, Bernoulli, np.zeros,
np.zeros)