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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_flaubert.py
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@@ -146,9 +146,7 @@ class TFFlaubertModelTester:
inputs = [input_ids, input_mask]
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_flaubert_lm_head(
self,
@@ -167,7 +165,7 @@ class TFFlaubertModelTester:
inputs = {"input_ids": input_ids, "lengths": input_lengths, "langs": 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_flaubert_qa(
self,
@@ -187,8 +185,8 @@ class TFFlaubertModelTester:
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_flaubert_sequence_classif(
self,
@@ -208,7 +206,7 @@ class TFFlaubertModelTester:
result = model(inputs)
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.type_sequence_label_size])
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.type_sequence_label_size))
def create_and_check_flaubert_for_token_classification(
self,
@@ -226,7 +224,7 @@ class TFFlaubertModelTester:
model = TFFlaubertForTokenClassification(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_flaubert_for_multiple_choice(
self,
@@ -251,7 +249,7 @@ class TFFlaubertModelTester:
"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 prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()