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Tf longformer for sequence classification (#8231)

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* working on LongformerForSequenceClassification

* add TFLongformerForMultipleChoice

* add TFLongformerForTokenClassification

* use add_start_docstrings_to_model_forward

* test TFLongformerForSequenceClassification

* test TFLongformerForMultipleChoice

* test TFLongformerForTokenClassification

* remove test from repo

* add test and doc for TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerForMultipleChoice

* add requested classes to modeling_tf_auto.py
update dummy_tf_objects
fix tests
fix bugs in requested classes

* pass all tests except test_inputs_embeds

* sync with master

* pass all tests except test_inputs_embeds

* pass all tests

* pass all tests

* work on test_inputs_embeds

* fix style and quality

* make multi choice work

* fix TFLongformerForTokenClassification signature

* fix TFLongformerForMultipleChoice, TFLongformerForSequenceClassification signature

* fix mult choice

* fix mc hint

* fix input embeds

* fix input embeds

* refactor input embeds

* fix copy issue

* apply sylvains changes and clean more

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
This commit is contained in:
elk-cloner
2020-11-19 19:07:27 +03:30
committed by GitHub
parent 62cd9ce9f8
commit 5362bb8a6b
10 changed files with 892 additions and 71 deletions
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40
tests/test_modeling_longformer.py
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@@ -129,7 +129,7 @@ class LongformerModelTester:
output_without_mask = model(input_ids)["last_hidden_state"]
self.parent.assertTrue(torch.allclose(output_with_mask[0, 0, :5], output_without_mask[0, 0, :5], atol=1e-4))
def create_and_check_longformer_model(
def create_and_check_model(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = LongformerModel(config=config)
@@ -141,7 +141,7 @@ class LongformerModelTester:
self.parent.assertEqual(result.last_hidden_state.shape, (self.batch_size, self.seq_length, self.hidden_size))
self.parent.assertEqual(result.pooler_output.shape, (self.batch_size, self.hidden_size))
def create_and_check_longformer_model_with_global_attention_mask(
def create_and_check_model_with_global_attention_mask(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = LongformerModel(config=config)
@@ -163,7 +163,7 @@ class LongformerModelTester:
self.parent.assertEqual(result.last_hidden_state.shape, (self.batch_size, self.seq_length, self.hidden_size))
self.parent.assertEqual(result.pooler_output.shape, (self.batch_size, self.hidden_size))
def create_and_check_longformer_for_masked_lm(
def create_and_check_for_masked_lm(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = LongformerForMaskedLM(config=config)
@@ -172,7 +172,7 @@ class LongformerModelTester:
result = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, labels=token_labels)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.vocab_size))
def create_and_check_longformer_for_question_answering(
def create_and_check_for_question_answering(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = LongformerForQuestionAnswering(config=config)
@@ -189,7 +189,7 @@ class LongformerModelTester:
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_longformer_for_sequence_classification(
def create_and_check_for_sequence_classification(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_labels = self.num_labels
@@ -199,7 +199,7 @@ class LongformerModelTester:
result = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, labels=sequence_labels)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.num_labels))
def create_and_check_longformer_for_token_classification(
def create_and_check_for_token_classification(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_labels = self.num_labels
@@ -209,7 +209,7 @@ class LongformerModelTester:
result = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, labels=token_labels)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.num_labels))
def create_and_check_longformer_for_multiple_choice(
def create_and_check_for_multiple_choice(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_choices = self.num_choices
@@ -296,37 +296,37 @@ class LongformerModelTest(ModelTesterMixin, unittest.TestCase):
def test_config(self):
self.config_tester.run_common_tests()
def test_longformer_model(self):
def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_longformer_model(*config_and_inputs)
self.model_tester.create_and_check_model(*config_and_inputs)
def test_longformer_model_attention_mask_determinism(self):
def test_model_attention_mask_determinism(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_attention_mask_determinism(*config_and_inputs)
def test_longformer_model_global_attention_mask(self):
def test_model_global_attention_mask(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_longformer_model_with_global_attention_mask(*config_and_inputs)
self.model_tester.create_and_check_model_with_global_attention_mask(*config_and_inputs)
def test_longformer_for_masked_lm(self):
def test_for_masked_lm(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_longformer_for_masked_lm(*config_and_inputs)
self.model_tester.create_and_check_for_masked_lm(*config_and_inputs)
def test_longformer_for_question_answering(self):
def test_for_question_answering(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs_for_question_answering()
self.model_tester.create_and_check_longformer_for_question_answering(*config_and_inputs)
self.model_tester.create_and_check_for_question_answering(*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_longformer_for_sequence_classification(*config_and_inputs)
self.model_tester.create_and_check_for_sequence_classification(*config_and_inputs)
def test_for_token_classification(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_longformer_for_token_classification(*config_and_inputs)
self.model_tester.create_and_check_for_token_classification(*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_longformer_for_multiple_choice(*config_and_inputs)
self.model_tester.create_and_check_for_multiple_choice(*config_and_inputs)
@require_torch
@@ -691,7 +691,7 @@ class LongformerModelIntegrationTest(unittest.TestCase):
) # long input
input_ids = input_ids.to(torch_device)
loss, prediction_scores = model(input_ids, labels=input_ids)
loss, prediction_scores = model(input_ids, labels=input_ids).to_tuple()
expected_loss = torch.tensor(0.0074, device=torch_device)
expected_prediction_scores_sum = torch.tensor(-6.1048e08, device=torch_device)