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Add a script to check all models are tested and documented (#6298)

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* Add a script to check all models are tested and documented

* Apply suggestions from code review

Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>

* Address comments

Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>
This commit is contained in:
Sylvain Gugger
2020-08-07 09:18:37 -04:00
committed by GitHub
parent e1638dce16
commit 6ba540b747
12 changed files with 351 additions and 2 deletions
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22
tests/test_modeling_tf_albert.py
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@@ -24,10 +24,12 @@ from .test_modeling_tf_common import TFModelTesterMixin, ids_tensor
if is_tf_available():
import tensorflow as tf
from transformers.modeling_tf_albert import (
TFAlbertModel,
TFAlbertForPreTraining,
TFAlbertForMaskedLM,
TFAlbertForMultipleChoice,
TFAlbertForSequenceClassification,
TFAlbertForQuestionAnswering,
TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
@@ -180,6 +182,22 @@ class TFAlbertModelTester:
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_albert_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 = TFAlbertForMultipleChoice(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,
}
result = model(inputs)
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()
(
@@ -229,6 +247,10 @@ class TFAlbertModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_albert_for_masked_lm(*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_albert_for_multiple_choice(*config_and_inputs)
def test_for_sequence_classification(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_albert_for_sequence_classification(*config_and_inputs)