def create_and_check_distilbert_model(self, config, input_ids, input_mask,
sequence_labels, token_labels,
choice_labels):
model = TFDistilBertModel(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask}
result = model(inputs)
inputs = [input_ids, input_mask]
result = model(inputs)
self.parent.assertEqual(
result.last_hidden_state.shape,
(self.batch_size, self.seq_length, self.hidden_size))
def create_and_check_distilbert_model(self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels):
model = TFDistilBertModel(config=config)
inputs = {'input_ids': input_ids,
'attention_mask': input_mask}
outputs = model(inputs)
sequence_output = outputs[0]
inputs = [input_ids, input_mask]
(sequence_output,) = model(inputs)
result = {
"sequence_output": sequence_output.numpy(),
}
self.parent.assertListEqual(
list(result["sequence_output"].shape),
[self.batch_size, self.seq_length, self.hidden_size])
def test_model_from_pretrained(self):
for model_name in list(
TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]):
model = TFDistilBertModel.from_pretrained(model_name)
self.assertIsNotNone(model)