def test_sparsemax_loss_constructor_aginst_numpy(dtype):
"""check sparsemax-loss construcor against numpy."""
random = np.random.RandomState(1)
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1
loss_object = SparsemaxLoss()
tf_loss_op = loss_object(q, z)
np_loss = np.mean(_np_sparsemax_loss(z, q).astype(dtype))
test_utils.assert_allclose_according_to_type(np_loss, tf_loss_op)
assert np_loss.shape == tf_loss_op.shape
def test_sparsemax_loss_constructor_aginst_numpy(self, dtype=None):
"""check sparsemax-loss construcor against numpy."""
random = np.random.RandomState(1)
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1
loss_object = SparsemaxLoss()
tf_loss_op = loss_object(q, z)
tf_loss_out = self.evaluate(tf_loss_op)
np_loss = np.mean(_np_sparsemax_loss(z, q).astype(dtype))
self.assertAllCloseAccordingToType(np_loss, tf_loss_out)
self.assertShapeEqual(np_loss, tf_loss_op)
def test_sparsemax_loss_constructor_not_from_logits(self, dtype=None):
"""check sparsemax-loss construcor throws when from_logits=True."""
self.assertRaises(ValueError, lambda: SparsemaxLoss(from_logits=False))
def test_sparsemax_loss_constructor_not_from_logits(dtype):
"""check sparsemax-loss construcor throws when from_logits=True."""
with pytest.raises(ValueError):
SparsemaxLoss(from_logits=False)