Tests for AlbertForQuestionAnswering AlbertForSequenceClassification
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@@ -26,7 +26,9 @@ from .modeling_common_test import (CommonTestCases, ids_tensor)
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from .configuration_common_test import ConfigTester
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if is_torch_available():
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from transformers import (AlbertConfig, AlbertModel, AlbertForMaskedLM)
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from transformers import (AlbertConfig, AlbertModel, AlbertForMaskedLM,
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AlbertForSequenceClassification, AlbertForQuestionAnswering,
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)
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from transformers.modeling_albert import ALBERT_PRETRAINED_MODEL_ARCHIVE_MAP
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else:
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pytestmark = pytest.mark.skip("Require Torch")
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@@ -157,6 +159,39 @@ class AlbertModelTest(CommonTestCases.CommonModelTester):
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[self.batch_size, self.seq_length, self.vocab_size])
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self.check_loss_output(result)
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def create_and_check_albert_for_question_answering(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
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model = AlbertForQuestionAnswering(config=config)
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model.eval()
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loss, start_logits, end_logits = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids,
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start_positions=sequence_labels, end_positions=sequence_labels)
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result = {
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"loss": loss,
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"start_logits": start_logits,
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"end_logits": end_logits,
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}
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self.parent.assertListEqual(
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list(result["start_logits"].size()),
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[self.batch_size, self.seq_length])
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self.parent.assertListEqual(
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list(result["end_logits"].size()),
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[self.batch_size, self.seq_length])
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self.check_loss_output(result)
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def create_and_check_albert_for_sequence_classification(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
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config.num_labels = self.num_labels
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model = AlbertForSequenceClassification(config)
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model.eval()
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loss, logits = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, labels=sequence_labels)
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result = {
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"loss": loss,
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"logits": logits,
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}
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self.parent.assertListEqual(
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list(result["logits"].size()),
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[self.batch_size, self.num_labels])
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self.check_loss_output(result)
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def prepare_config_and_inputs_for_common(self):
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config_and_inputs = self.prepare_config_and_inputs()
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@@ -180,6 +215,14 @@ class AlbertModelTest(CommonTestCases.CommonModelTester):
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config_and_inputs = self.model_tester.prepare_config_and_inputs()
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self.model_tester.create_and_check_albert_for_masked_lm(*config_and_inputs)
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def test_for_question_answering(self):
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config_and_inputs = self.model_tester.prepare_config_and_inputs()
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self.model_tester.create_and_check_albert_for_question_answering(*config_and_inputs)
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def test_for_sequence_classification(self):
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config_and_inputs = self.model_tester.prepare_config_and_inputs()
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self.model_tester.create_and_check_albert_for_sequence_classification(*config_and_inputs)
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@pytest.mark.slow
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def test_model_from_pretrained(self):
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cache_dir = "/tmp/transformers_test/"
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