[BART] Delete redundant unit test (#3302)

tests/test_modeling_bart.py

@@ -381,7 +381,7 @@ TOLERANCE = 1e-4
 
 
 @require_torch
-class BartModelIntegrationTest(unittest.TestCase):
+class BartModelIntegrationTests(unittest.TestCase):
     @slow
     def test_inference_no_head(self):
         model = BartModel.from_pretrained("bart-large").to(torch_device)
@@ -431,25 +431,7 @@ class BartModelIntegrationTest(unittest.TestCase):
             self.assertIsNotNone(model)
 
     @slow
-    def test_cnn_summarization_same_as_fairseq_easy(self):
-        hf = BartForConditionalGeneration.from_pretrained("bart-large-cnn", output_past=True,).to(torch_device)
-        tok = BartTokenizer.from_pretrained("bart-large")
-        text = " (CNN)The Palestinian Authority officially became the 123rd member of the International Criminal Court on Wednesday, a step that gives the court jurisdiction over alleged crimes in Palestinian"
-        tokens = tok.encode(text, return_tensors="pt").to(torch_device)
-        extra_len = 20
-        gen_tokens = hf.generate(
-            tokens,
-            num_beams=4,
-            max_length=extra_len + 2,
-            do_sample=False,
-            decoder_start_token_id=hf.config.eos_token_ids[0],
-        )  # repetition_penalty=10.,
-        expected_result = "<s>The Palestinian Authority officially became the 123rd member of the International Criminal Court on Wednesday."
-        generated = [tok.decode(g,) for g in gen_tokens]
-        self.assertEqual(expected_result, generated[0])
-
-    @slow
-    def test_cnn_summarization_same_as_fairseq_hard(self):
+    def test_cnn_summarization_same_as_fairseq(self):
         hf = BartForConditionalGeneration.from_pretrained("bart-large-cnn", output_past=True,).to(torch_device)
         tok = BartTokenizer.from_pretrained("bart-large")