Alber model integration testing added (#9980)

tests/test_modeling_albert.py

@@ -285,3 +285,19 @@ class AlbertModelTest(ModelTesterMixin, unittest.TestCase):
         for model_name in ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
             model = AlbertModel.from_pretrained(model_name)
             self.assertIsNotNone(model)
+
+
+@require_torch
+class AlbertModelIntegrationTest(unittest.TestCase):
+    @slow
+    def test_inference_no_head_absolute_embedding(self):
+        model = AlbertForPreTraining.from_pretrained("albert-base-v2")
+        input_ids = torch.tensor([[0, 345, 232, 328, 740, 140, 1695, 69, 6078, 1588, 2]])
+        output = model(input_ids)[0]
+        expected_shape = torch.Size((1, 11, 30000))
+        self.assertEqual(output.shape, expected_shape)
+        expected_slice = torch.tensor(
+            [[[4.6061, 0.7321, -1.7725], [4.6061, 0.7323, -1.7727], [4.6061, 0.7323, -1.7727]]]
+        )
+
+        self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))