def create_and_check_xlm_lm_head(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
input_mask,
):
model = XLMWithLMHeadModel(config)
model.to(torch_device)
model.eval()
loss, logits = model(input_ids,
token_type_ids=token_type_ids,
labels=token_labels)
result = {
"loss": loss,
"logits": logits,
}
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["logits"].size()),
[self.batch_size, self.seq_length, self.vocab_size])
def create_and_check_xlm_lm_head(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = XLMWithLMHeadModel(config)
model.to(torch_device)
model.eval()
result = model(input_ids, token_type_ids=token_type_ids, labels=token_labels)
self.parent.assertEqual(result.loss.shape, ())
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.vocab_size))