From 804cd185d8baf03b02b8e31df3fb8677315a3199 Mon Sep 17 00:00:00 2001
From: Daniel Hug <38571110+danielpatrickhug@users.noreply.github.com>
Date: Thu, 4 Feb 2021 04:24:59 -0500
Subject: [PATCH] Added Integration testing for DistilBert model from issue
 #9948' (#9995)

---
 tests/test_modeling_distilbert.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/tests/test_modeling_distilbert.py b/tests/test_modeling_distilbert.py
index 7a24ad4502..9b65e69f89 100644
--- a/tests/test_modeling_distilbert.py
+++ b/tests/test_modeling_distilbert.py
@@ -24,6 +24,8 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 
 
 if is_torch_available():
+    import torch
+
     from transformers import (
         DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
         DistilBertConfig,
@@ -246,3 +248,19 @@ class DistilBertModelTest(ModelTesterMixin, unittest.TestCase):
         for model_name in DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
             model = DistilBertModel.from_pretrained(model_name)
             self.assertIsNotNone(model)
+
+
+@require_torch
+class DistilBertModelIntergrationTest(unittest.TestCase):
+    @slow
+    def test_inference_no_head_absolute_embedding(self):
+        model = DistilBertModel.from_pretrained("distilbert-base-uncased")
+        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(
+            [[[0.4026, -0.2919, 0.3902], [0.3828, -0.2129, 0.3563], [0.3919, -0.2287, 0.3438]]]
+        )
+
+        self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))