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cleanup tf unittests: part 2 (#6260)

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* cleanup torch unittests: part 2

* remove trailing comma added by isort, and which breaks flake

* one more comma

* revert odd balls

* part 3: odd cases

* more ["key"] -> .key refactoring

* .numpy() is not needed

* more unncessary .numpy() removed

* more simplification
This commit is contained in:
Stas Bekman
2020-08-13 01:29:06 -07:00
committed by GitHub
parent bc820476a5
commit e983da0e7d
21 changed files with 159 additions and 239 deletions
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22
templates/adding_a_new_model/tests/test_modeling_tf_xxx.py
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@@ -148,10 +148,10 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
result = model(input_ids)
self.parent.assertListEqual(
list(result["last_hidden_state"].shape), [self.batch_size, self.seq_length, self.hidden_size]
self.parent.assertEqual(
result.last_hidden_state.shape, (self.batch_size, self.seq_length, self.hidden_size)
)
self.parent.assertListEqual(list(result["pooler_output"].shape), [self.batch_size, self.hidden_size])
self.parent.assertEqual(result.pooler_output.shape, (self.batch_size, self.hidden_size))
def create_and_check_xxx_for_masked_lm(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -159,9 +159,7 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFXxxForMaskedLM(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}
result = model(inputs)
self.parent.assertListEqual(
list(result["logits"].shape), [self.batch_size, self.seq_length, self.vocab_size]
)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.vocab_size))
def create_and_check_xxx_for_sequence_classification(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -170,7 +168,7 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFXxxForSequenceClassification(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}
result = model(inputs)
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_labels])
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.num_labels))
def create_and_check_bert_for_multiple_choice(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -186,7 +184,7 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
"token_type_ids": multiple_choice_token_type_ids,
}
result = model(inputs)
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.num_choices))
def create_and_check_xxx_for_token_classification(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -195,9 +193,7 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFXxxForTokenClassification(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}
result = model(inputs)
self.parent.assertListEqual(
list(result["logits"].shape), [self.batch_size, self.seq_length, self.num_labels]
)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.num_labels))
def create_and_check_xxx_for_question_answering(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -205,8 +201,8 @@ class TFXxxModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFXxxForQuestionAnswering(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}
result = model(inputs)
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])
self.parent.assertEqual(result.start_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape, (self.batch_size, self.seq_length))
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()