chore: fix typos in tests directory (#36785)
* chore: fix typos in tests directory * chore: fix typos in tests directory * chore: fix typos in tests directory * chore: fix typos in tests directory * chore: fix typos in tests directory * chore: fix typos in tests directory * chore: fix typos in tests directory
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@@ -613,7 +613,7 @@ class PipelineUtilsTest(unittest.TestCase):
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set_seed_fn = lambda: torch.manual_seed(0) # noqa: E731
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for task in SUPPORTED_TASKS.keys():
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if task == "table-question-answering":
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# test table in seperate test due to more dependencies
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# test table in separate test due to more dependencies
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continue
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self.check_default_pipeline(task, "pt", set_seed_fn, self.check_models_equal_pt)
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@@ -631,7 +631,7 @@ class PipelineUtilsTest(unittest.TestCase):
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set_seed_fn = lambda: keras.utils.set_random_seed(0) # noqa: E731
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for task in SUPPORTED_TASKS.keys():
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if task == "table-question-answering":
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# test table in seperate test due to more dependencies
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# test table in separate test due to more dependencies
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continue
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self.check_default_pipeline(task, "tf", set_seed_fn, self.check_models_equal_tf)
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@@ -778,7 +778,7 @@ class TokenClassificationPipelineTests(unittest.TestCase):
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@require_tf
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def test_tf_only(self):
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model_name = "hf-internal-testing/tiny-random-bert-tf-only" # This model only has a TensorFlow version
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# We test that if we don't specificy framework='tf', it gets detected automatically
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# We test that if we don't specify framework='tf', it gets detected automatically
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token_classifier = pipeline(task="ner", model=model_name)
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self.assertEqual(token_classifier.framework, "tf")
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