riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-31 02:02:21 +06:00
Code Issues Actions 33 Packages Projects Releases Wiki Activity

test circleCI h5py version

Browse Source
This commit is contained in:
thomwolf 2019-09-23 16:26:06 +02:00
parent a31e591d27
commit 830d212be7
1 changed files with 11 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
pytorch_transformers/tests/modeling_tf_auto_test.py
View File

@ -39,46 +39,49 @@ else:
class TFAutoModelTest(unittest.TestCase):
def test_model_from_pretrained(self):
import h5py
self.assertTrue(h5py.version.hdf5_version.startswith("1.10"))
logging.basicConfig(level=logging.INFO)
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.assertIsInstance(config, BertConfig)
model = TFAutoModel.from_pretrained(model_name)
model = TFAutoModel.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertModel)
def test_lmhead_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
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.assertIsInstance(config, BertConfig)
model = TFAutoModelWithLMHead.from_pretrained(model_name)
model = TFAutoModelWithLMHead.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForMaskedLM)
def test_sequence_classification_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
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.assertIsInstance(config, BertConfig)
model = TFAutoModelForSequenceClassification.from_pretrained(model_name)
model = TFAutoModelForSequenceClassification.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForSequenceClassification)
def test_question_answering_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
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.assertIsInstance(config, BertConfig)
model = TFAutoModelForQuestionAnswering.from_pretrained(model_name)
model = TFAutoModelForQuestionAnswering.from_pretrained(model_name, force_download=True)
self.assertIsNotNone(model)
self.assertIsInstance(model, TFBertForQuestionAnswering)