def create_and_check_gpt2_double_head(
self, config, input_ids, input_mask, head_mask, token_type_ids, mc_token_ids, *args
):
model = TFGPT2DoubleHeadsModel(config=config)
multiple_choice_inputs_ids = tf.tile(tf.expand_dims(input_ids, 1), (1, self.num_choices, 1))
multiple_choice_input_mask = tf.tile(tf.expand_dims(input_mask, 1), (1, self.num_choices, 1))
multiple_choice_token_type_ids = tf.tile(tf.expand_dims(token_type_ids, 1), (1, self.num_choices, 1))
inputs = {
"input_ids": multiple_choice_inputs_ids,
"mc_token_ids": mc_token_ids,
"attention_mask": multiple_choice_input_mask,
"token_type_ids": multiple_choice_token_type_ids,
}
lm_logits, mc_logits = model(inputs)[:2]
result = {"lm_logits": lm_logits.numpy(), "mc_logits": mc_logits.numpy()}
self.parent.assertListEqual(
list(result["lm_logits"].shape), [self.batch_size, self.num_choices, self.seq_length, self.vocab_size],
)
self.parent.assertListEqual(list(result["mc_logits"].shape), [self.batch_size, self.num_choices])
def create_and_check_gpt2_double_head(self, config, input_ids, input_mask,
head_mask, token_type_ids,
mc_token_ids, *args):
model = TFGPT2DoubleHeadsModel(config=config)
multiple_choice_inputs_ids = tf.tile(tf.expand_dims(input_ids, 1),
(1, self.num_choices, 1))
multiple_choice_input_mask = tf.tile(tf.expand_dims(input_mask, 1),
(1, self.num_choices, 1))
multiple_choice_token_type_ids = tf.tile(
tf.expand_dims(token_type_ids, 1), (1, self.num_choices, 1))
inputs = {
"input_ids": multiple_choice_inputs_ids,
"mc_token_ids": mc_token_ids,
"attention_mask": multiple_choice_input_mask,
"token_type_ids": multiple_choice_token_type_ids,
}
result = model(inputs)
self.parent.assertEqual(result.lm_logits.shape,
(self.batch_size, self.num_choices,
self.seq_length, self.vocab_size))
self.parent.assertEqual(result.mc_logits.shape,
(self.batch_size, self.num_choices))
