Integration test for FlauBert (#10022)

tests/test_modeling_flaubert.py

@@ -399,3 +399,19 @@ class FlaubertModelTest(ModelTesterMixin, unittest.TestCase):
         for model_name in FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
             model = FlaubertModel.from_pretrained(model_name)
             self.assertIsNotNone(model)
+
+
+@require_torch
+class FlaubertModelIntegrationTest(unittest.TestCase):
+    @slow
+    def test_inference_no_head_absolute_embedding(self):
+        model = FlaubertModel.from_pretrained("flaubert/flaubert_base_cased")
+        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, 768))
+        self.assertEqual(output.shape, expected_shape)
+        expected_slice = torch.tensor(
+            [[[-2.6251, -1.4298, -0.0227], [-2.8510, -1.6387, 0.2258], [-2.8114, -1.1832, -0.3066]]]
+        )
+
+        self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))