def create_and_check_xlnet_qa(
self,
config,
input_ids_1,
input_ids_2,
input_ids_q,
perm_mask,
input_mask,
target_mapping,
segment_ids,
lm_labels,
sequence_labels,
is_impossible_labels,
):
model = TFXLNetForQuestionAnsweringSimple(config)
inputs = {
"input_ids": input_ids_1,
"attention_mask": input_mask,
"token_type_ids": segment_ids
}
result = model(inputs)
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))
self.parent.assertListEqual(
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] *
self.num_hidden_layers,
)
def create_and_check_xlnet_qa(self, config, input_ids_1, input_ids_2,
input_ids_q, perm_mask, input_mask,
target_mapping, segment_ids, lm_labels,
sequence_labels, is_impossible_labels):
model = TFXLNetForQuestionAnsweringSimple(config)
inputs = {
'input_ids': input_ids_1,
'attention_mask': input_mask,
'token_type_ids': segment_ids
}
start_logits, end_logits, mems = model(inputs)
result = {
"start_logits": start_logits.numpy(),
"end_logits": end_logits.numpy(),
"mems": [m.numpy() for m in mems],
}
self.parent.assertListEqual(list(result["start_logits"].shape),
[self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].shape),
[self.batch_size, self.seq_length])
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size, self.hidden_size]] *
self.num_hidden_layers)
