def test_inference_model(self): model = TFRemBertModel.from_pretrained("google/rembert") input_ids = tf.constant([[312, 56498, 313, 2125, 313]]) segment_ids = tf.constant([[0, 0, 0, 1, 1]]) output = model(input_ids, token_type_ids=segment_ids, output_hidden_states=True) hidden_size = 1152 expected_shape = [1, 5, hidden_size] self.assertEqual(output["last_hidden_state"].shape, expected_shape) expected_implementation = tf.constant([[ [0.0754, -0.2022, 0.1904], [-0.3354, -0.3692, -0.4791], [-0.2314, -0.6729, -0.0749], [-0.0396, -0.3105, -0.4234], [-0.1571, -0.0525, 0.5353], ]]) tf.debugging.assert_near(output["last_hidden_state"][:, :, :3], expected_implementation, atol=1e-4)
def test_model_from_pretrained(self): model = TFRemBertModel.from_pretrained("google/rembert") self.assertIsNotNone(model)