def create_and_check_flaubert_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = FlaubertForQuestionAnswering(config)
model.to(torch_device)
model.eval()
result = model(input_ids)
result_with_labels = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
cls_index=sequence_labels,
is_impossible=is_impossible_labels,
p_mask=input_mask,
)
result_with_labels = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
cls_index=sequence_labels,
is_impossible=is_impossible_labels,
)
(total_loss, ) = result_with_labels.to_tuple()
result_with_labels = model(input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels)
(total_loss, ) = result_with_labels.to_tuple()
self.parent.assertEqual(result_with_labels.loss.shape, ())
self.parent.assertEqual(result.start_top_log_probs.shape,
(self.batch_size, model.config.start_n_top))
self.parent.assertEqual(result.start_top_index.shape,
(self.batch_size, model.config.start_n_top))
self.parent.assertEqual(result.end_top_log_probs.shape,
(self.batch_size, model.config.start_n_top *
model.config.end_n_top))
self.parent.assertEqual(result.end_top_index.shape,
(self.batch_size, model.config.start_n_top *
model.config.end_n_top))
self.parent.assertEqual(result.cls_logits.shape, (self.batch_size, ))
def create_and_check_flaubert_qa(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
input_mask,
):
model = FlaubertForQuestionAnswering(config)
model.to(torch_device)
model.eval()
outputs = model(input_ids)
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = outputs
outputs = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
cls_index=sequence_labels,
is_impossible=is_impossible_labels,
p_mask=input_mask,
)
outputs = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
cls_index=sequence_labels,
is_impossible=is_impossible_labels,
)
(total_loss, ) = outputs
outputs = model(input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels)
(total_loss, ) = outputs
result = {
"loss": total_loss,
"start_top_log_probs": start_top_log_probs,
"start_top_index": start_top_index,
"end_top_log_probs": end_top_log_probs,
"end_top_index": end_top_index,
"cls_logits": cls_logits,
}
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["start_top_log_probs"].size()),
[self.batch_size, model.config.start_n_top])
self.parent.assertListEqual(
list(result["start_top_index"].size()),
[self.batch_size, model.config.start_n_top])
self.parent.assertListEqual(
list(result["end_top_log_probs"].size()),
[
self.batch_size,
model.config.start_n_top * model.config.end_n_top
],
)
self.parent.assertListEqual(
list(result["end_top_index"].size()),
[
self.batch_size,
model.config.start_n_top * model.config.end_n_top
],
)
self.parent.assertListEqual(list(result["cls_logits"].size()),
[self.batch_size])