def create_and_check_xlm_simple_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
input_mask,
):
model = XLMForQuestionAnsweringSimple(config)
model.to(torch_device)
model.eval()
outputs = model(input_ids)
outputs = model(input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels)
loss, start_logits, end_logits = outputs
result = {
"loss": loss,
"start_logits": start_logits,
"end_logits": end_logits,
}
self.parent.assertListEqual(list(result["start_logits"].size()),
[self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].size()),
[self.batch_size, self.seq_length])
self.check_loss_output(result)
def create_and_check_xlm_simple_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = XLMForQuestionAnsweringSimple(config)
model.to(torch_device)
model.eval()
outputs = model(input_ids)
outputs = model(input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels)
result = outputs
self.parent.assertEqual(result.start_logits.shape,
(self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape,
(self.batch_size, self.seq_length))