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Cleaning TensorFlow models (#5229)

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* Cleaning TensorFlow models

Update all classes


stylr

* Don't average loss
This commit is contained in:
Lysandre Debut
2020-06-24 11:37:20 -04:00
committed by GitHub
parent 609e0c583f
commit cf10d4cfdd
13 changed files with 483 additions and 126 deletions
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24
tests/test_modeling_tf_roberta.py
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@@ -32,6 +32,7 @@ if is_tf_available():
TFRobertaForSequenceClassification,
TFRobertaForTokenClassification,
TFRobertaForQuestionAnswering,
TFRobertaForMultipleChoice,
TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
)
@@ -154,6 +155,25 @@ class TFRobertaModelTester:
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])
def create_and_check_roberta_for_multiple_choice(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_choices = self.num_choices
model = TFRobertaForMultipleChoice(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,
"attention_mask": multiple_choice_input_mask,
"token_type_ids": multiple_choice_token_type_ids,
}
(logits,) = model(inputs)
result = {
"logits": logits.numpy(),
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()
(
@@ -207,6 +227,10 @@ class TFRobertaModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_roberta_for_question_answering(*config_and_inputs)
def test_for_multiple_choice(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_roberta_for_multiple_choice(*config_and_inputs)
@slow
def test_model_from_pretrained(self):
for model_name in TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: