def test_inference_no_head(self):
model = TFRobertaModel.from_pretrained("roberta-base")
input_ids = tf.constant([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
output = model(input_ids)[0]
# compare the actual values for a slice.
expected_slice = tf.constant(
def test_model_from_pretrained(self):
cache_dir = "/tmp/transformers_test/"
for model_name in list(
TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFRobertaModel.from_pretrained(model_name,
cache_dir=cache_dir)
shutil.rmtree(cache_dir)
self.assertIsNotNone(model)
def test_inference_no_head(self):
model = TFRobertaModel.from_pretrained("roberta-base")
input_ids = tf.constant([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
output = model(input_ids)[0]
# compare the actual values for a slice.
expected_slice = tf.constant(
[[[-0.0231, 0.0782, 0.0074], [-0.1854, 0.0540, -0.0175], [0.0548, 0.0799, 0.1687]]]
)
self.assertTrue(numpy.allclose(output[:, :3, :3].numpy(), expected_slice.numpy(), atol=1e-4))
def test_model_from_pretrained(self):
for model_name in list(TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFRobertaModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
def test_model_from_pretrained(self):
for model_name in TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = TFRobertaModel.from_pretrained(model_name)
self.assertIsNotNone(model)