def create_and_check_xlnet_lm_head(
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,
token_labels,
):
model = XLNetLMHeadModel(config)
model.to(torch_device)
model.eval()
loss_1, all_logits_1, mems_1 = model(input_ids_1,
token_type_ids=segment_ids,
labels=lm_labels)
loss_2, all_logits_2, mems_2 = model(input_ids_2,
token_type_ids=segment_ids,
labels=lm_labels,
mems=mems_1)
logits, _ = model(input_ids_q,
perm_mask=perm_mask,
target_mapping=target_mapping)
result = {
"loss_1": loss_1,
"mems_1": mems_1,
"all_logits_1": all_logits_1,
"loss_2": loss_2,
"mems_2": mems_2,
"all_logits_2": all_logits_2,
}
self.parent.assertListEqual(list(result["loss_1"].size()), [])
self.parent.assertListEqual(
list(result["all_logits_1"].size()),
[self.batch_size, self.seq_length, self.vocab_size])
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_1"]),
[[self.seq_length, self.batch_size, self.hidden_size]] *
self.num_hidden_layers,
)
self.parent.assertListEqual(list(result["loss_2"].size()), [])
self.parent.assertListEqual(
list(result["all_logits_2"].size()),
[self.batch_size, self.seq_length, self.vocab_size])
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_2"]),
[[self.mem_len, self.batch_size, self.hidden_size]] *
self.num_hidden_layers,
)
def create_and_check_xlnet_lm_head(
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,
token_labels,
):
model = XLNetLMHeadModel(config)
model.to(torch_device)
model.eval()
result1 = model(input_ids_1,
token_type_ids=segment_ids,
labels=lm_labels)
result2 = model(input_ids_2,
token_type_ids=segment_ids,
labels=lm_labels,
mems=result1.mems)
_ = model(input_ids_q,
perm_mask=perm_mask,
target_mapping=target_mapping)
self.parent.assertEqual(result1.loss.shape, ())
self.parent.assertEqual(
result1.logits.shape,
(self.batch_size, self.seq_length, self.vocab_size))
self.parent.assertListEqual(
[mem.shape for mem in result1.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] *
self.num_hidden_layers,
)
self.parent.assertEqual(result2.loss.shape, ())
self.parent.assertEqual(
result2.logits.shape,
(self.batch_size, self.seq_length, self.vocab_size))
self.parent.assertListEqual(
[mem.shape for mem in result2.mems],
[(self.mem_len, self.batch_size, self.hidden_size)] *
self.num_hidden_layers,
)
