def test_support_shape(dist):
for idx in range(dist.get_num_test_data()):
dist_params = dist.get_dist_params(idx)
d = dist.pyro_dist(**dist_params)
assert d.support.event_dim == d.event_dim
x = dist.get_test_data(idx)
ok = d.support.check(x)
assert ok.shape == broadcast_shape(d.batch_shape, x.shape[:x.dim() - d.event_dim])
assert ok.all()
def test_batch_log_prob_shape(dist):
for idx in range(dist.get_num_test_data()):
dist_params = dist.get_dist_params(idx)
d = dist.pyro_dist(**dist_params)
x = dist.get_test_data(idx)
with xfail_if_not_implemented():
# Get log_prob shape after broadcasting.
expected_shape = _log_prob_shape(d, x.size())
log_p_obj = d.log_prob(x)
assert log_p_obj.size() == expected_shape
def test_batch_log_prob(dist):
if dist.scipy_arg_fn is None:
pytest.skip('{}.log_prob_sum has no scipy equivalent'.format(dist.pyro_dist.__name__))
for idx in dist.get_batch_data_indices():
dist_params = dist.get_dist_params(idx)
d = dist.pyro_dist(**dist_params)
test_data = dist.get_test_data(idx)
log_prob_sum_pyro = d.log_prob(test_data).sum().item()
log_prob_sum_np = np.sum(dist.get_scipy_batch_logpdf(-1))
assert_equal(log_prob_sum_pyro, log_prob_sum_np)
def test_batch_log_prob_shape(dist):
for idx in range(dist.get_num_test_data()):
dist_params = dist.get_dist_params(idx)
d = dist.pyro_dist(**dist_params)
x = dist.get_test_data(idx)
with xfail_if_not_implemented():
# Get log_prob shape after broadcasting.
expected_shape = _log_prob_shape(d, x.size())
log_p_obj = d.log_prob(x)
assert log_p_obj.size() == expected_shape
def test_batch_log_prob(dist):
if dist.scipy_arg_fn is None:
pytest.skip('{}.log_prob_sum has no scipy equivalent'.format(dist.pyro_dist.__name__))
for idx in dist.get_batch_data_indices():
dist_params = dist.get_dist_params(idx)
d = dist.pyro_dist(**dist_params)
test_data = dist.get_test_data(idx)
log_prob_sum_pyro = d.log_prob(test_data).sum().item()
log_prob_sum_np = np.sum(dist.get_scipy_batch_logpdf(-1))
assert_equal(log_prob_sum_pyro, log_prob_sum_np)