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)