SUMIN/HuggingFace_transformer
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Mark tests in TFAutoModelTest as slow.

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Each test forces downloading the same 536MB file, which is slow
even with a decent internet connection.
This commit is contained in:
Aymeric Augustin
2019-12-01 18:25:15 +01:00
parent b0ee7c7df3
commit 5ab93083e4
1 changed files with 4 additions and 0 deletions
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4
transformers/tests/modeling_tf_auto_test.py
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@@ -38,6 +38,7 @@ else:
class TFAutoModelTest(unittest.TestCase): class TFAutoModelTest(unittest.TestCase):
@pytest.mark.slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
import h5py import h5py
self.assertTrue(h5py.version.hdf5_version.startswith("1.10")) self.assertTrue(h5py.version.hdf5_version.startswith("1.10"))
@@ -53,6 +54,7 @@ class TFAutoModelTest(unittest.TestCase):
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertModel) self.assertIsInstance(model, TFBertModel)
@pytest.mark.slow
def test_lmhead_model_from_pretrained(self): def test_lmhead_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO) logging.basicConfig(level=logging.INFO)
# for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: # for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
@@ -65,6 +67,7 @@ class TFAutoModelTest(unittest.TestCase):
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForMaskedLM) self.assertIsInstance(model, TFBertForMaskedLM)
@pytest.mark.slow
def test_sequence_classification_model_from_pretrained(self): def test_sequence_classification_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO) logging.basicConfig(level=logging.INFO)
# for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: # for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
@@ -77,6 +80,7 @@ class TFAutoModelTest(unittest.TestCase):
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForSequenceClassification) self.assertIsInstance(model, TFBertForSequenceClassification)
@pytest.mark.slow
def test_question_answering_model_from_pretrained(self): def test_question_answering_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO) logging.basicConfig(level=logging.INFO)
# for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: # for model_name in list(TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: