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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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16
tests/test_modeling_tf_distilbert.py
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@@ -106,9 +106,7 @@ class TFDistilBertModelTester:
result = model(inputs)
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))
def create_and_check_distilbert_for_masked_lm(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -116,7 +114,7 @@ class TFDistilBertModelTester:
model = TFDistilBertForMaskedLM(config=config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask}
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_distilbert_for_question_answering(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -127,8 +125,8 @@ class TFDistilBertModelTester:
"attention_mask": input_mask,
}
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 create_and_check_distilbert_for_sequence_classification(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -137,7 +135,7 @@ class TFDistilBertModelTester:
model = TFDistilBertForSequenceClassification(config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask}
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_distilbert_for_multiple_choice(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -151,7 +149,7 @@ class TFDistilBertModelTester:
"attention_mask": multiple_choice_input_mask,
}
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_distilbert_for_token_classification(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
@@ -160,7 +158,7 @@ class TFDistilBertModelTester:
model = TFDistilBertForTokenClassification(config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask}
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 prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()