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Commit 830d212b authored by thomwolf's avatar thomwolf
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test circleCI h5py version

parent a31e591d
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pytorch_transformers/tests/modeling_tf_auto_test.py
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...@@ -39,46 +39,49 @@ else: ...@@ -39,46 +39,49 @@ else:
class TFAutoModelTest(unittest.TestCase): class TFAutoModelTest(unittest.TestCase):
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
import h5py
self.assertTrue(h5py.version.hdf5_version.startswith("1.10"))
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]:
config = AutoConfig.from_pretrained(model_name) config = AutoConfig.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(config) self.assertIsNotNone(config)
self.assertIsInstance(config, BertConfig) self.assertIsInstance(config, BertConfig)
model = TFAutoModel.from_pretrained(model_name) model = TFAutoModel.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertModel) self.assertIsInstance(model, TFBertModel)
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]:
config = AutoConfig.from_pretrained(model_name) config = AutoConfig.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(config) self.assertIsNotNone(config)
self.assertIsInstance(config, BertConfig) self.assertIsInstance(config, BertConfig)
model = TFAutoModelWithLMHead.from_pretrained(model_name) model = TFAutoModelWithLMHead.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForMaskedLM) self.assertIsInstance(model, TFBertForMaskedLM)
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]:
config = AutoConfig.from_pretrained(model_name) config = AutoConfig.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(config) self.assertIsNotNone(config)
self.assertIsInstance(config, BertConfig) self.assertIsInstance(config, BertConfig)
model = TFAutoModelForSequenceClassification.from_pretrained(model_name) model = TFAutoModelForSequenceClassification.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForSequenceClassification) self.assertIsInstance(model, TFBertForSequenceClassification)
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]:
config = AutoConfig.from_pretrained(model_name) config = AutoConfig.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(config) self.assertIsNotNone(config)
self.assertIsInstance(config, BertConfig) self.assertIsInstance(config, BertConfig)
model = TFAutoModelForQuestionAnswering.from_pretrained(model_name) model = TFAutoModelForQuestionAnswering.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model) self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForQuestionAnswering) self.assertIsInstance(model, TFBertForQuestionAnswering)
......
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