def create_and_check_xlnet_sequence_classif(
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 = TFXLNetForSequenceClassification(config)
logits, mems_1 = model(input_ids_1)
result = {
"mems_1": [mem.numpy() for mem in mems_1],
"logits": logits.numpy(),
}
self.parent.assertListEqual(
list(result["logits"].shape),
[self.batch_size, self.type_sequence_label_size])
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_1"]),
[[self.seq_length, self.batch_size, self.hidden_size]] *
self.num_hidden_layers,
)
def create_and_check_xlnet_sequence_classif(
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 = TFXLNetForSequenceClassification(config)
result = model(input_ids_1)
self.parent.assertEqual(
result.logits.shape,
(self.batch_size, self.type_sequence_label_size))
self.parent.assertListEqual(
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] *
self.num_hidden_layers,
)