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- # Copyright (c) Alibaba, Inc. and its affiliates.
-
- import unittest
-
- from modelscope.preprocessors import build_preprocessor, nlp
- from modelscope.utils.constant import Fields, InputFields
- from modelscope.utils.logger import get_logger
-
- logger = get_logger()
-
-
- class NLPPreprocessorTest(unittest.TestCase):
-
- def test_tokenize(self):
- cfg = dict(type='Tokenize', tokenizer_name='bert-base-cased')
- preprocessor = build_preprocessor(cfg, Fields.nlp)
- input = {
- InputFields.text:
- 'Do not meddle in the affairs of wizards, '
- 'for they are subtle and quick to anger.'
- }
- output = preprocessor(input)
- self.assertTrue(InputFields.text in output)
- self.assertEqual(output['input_ids'], [
- 101, 2091, 1136, 1143, 13002, 1107, 1103, 5707, 1104, 16678, 1116,
- 117, 1111, 1152, 1132, 11515, 1105, 3613, 1106, 4470, 119, 102
- ])
- self.assertEqual(
- output['token_type_ids'],
- [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
- self.assertEqual(
- output['attention_mask'],
- [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
-
- def test_token_classification_tokenize_bert(self):
- cfg = dict(
- type='token-cls-tokenizer',
- padding=False,
- label_all_tokens=False,
- model_dir='bert-base-cased',
- label2id={
- 'O': 0,
- 'B': 1,
- 'I': 2
- })
- preprocessor = build_preprocessor(cfg, Fields.nlp)
- input = 'Do not meddle in the affairs of wizards, ' \
- 'for they are subtle and quick to anger.'
- output = preprocessor(input)
- self.assertTrue(InputFields.text in output)
- self.assertEqual(output['input_ids'].tolist()[0], [
- 101, 2091, 1136, 1143, 13002, 1107, 1103, 5707, 1104, 16678, 1116,
- 117, 1111, 1152, 1132, 11515, 1105, 3613, 1106, 4470, 119, 102
- ])
- self.assertEqual(
- output['attention_mask'].tolist()[0],
- [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
- self.assertEqual(output['label_mask'].tolist()[0], [
- False, True, True, True, False, True, True, True, True, True,
- False, True, True, True, True, True, True, True, True, True, True,
- False
- ])
- self.assertEqual(
- output['offset_mapping'].tolist()[0],
- [[0, 2], [3, 6], [7, 13], [14, 16], [17, 20], [21, 28], [29, 31],
- [32, 39], [39, 40], [41, 44], [45, 49], [50, 53], [54, 60],
- [61, 64], [65, 70], [71, 73], [74, 79], [79, 80]])
-
- def test_token_classification_tokenize_roberta(self):
- cfg = dict(
- type='token-cls-tokenizer',
- padding=False,
- label_all_tokens=False,
- model_dir='xlm-roberta-base',
- label2id={
- 'O': 0,
- 'B': 1,
- 'I': 2
- })
- preprocessor = build_preprocessor(cfg, Fields.nlp)
- input = 'Do not meddle in the affairs of wizards, ' \
- 'for they are subtle and quick to anger.'
- output = preprocessor(input)
- self.assertTrue(InputFields.text in output)
- self.assertEqual(output['input_ids'].tolist()[0], [
- 0, 984, 959, 128, 19298, 23, 70, 103086, 7, 111, 6, 44239, 99397,
- 4, 100, 1836, 621, 1614, 17991, 136, 63773, 47, 348, 56, 5, 2
- ])
- self.assertEqual(output['attention_mask'].tolist()[0], [
- 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
- 1, 1, 1, 1
- ])
- self.assertEqual(output['label_mask'].tolist()[0], [
- False, True, True, True, False, True, True, True, False, True,
- True, False, False, False, True, True, True, True, False, True,
- True, True, True, False, False, False
- ])
- self.assertEqual(
- output['offset_mapping'].tolist()[0],
- [[0, 2], [3, 6], [7, 13], [14, 16], [17, 20], [21, 28], [29, 31],
- [32, 40], [41, 44], [45, 49], [50, 53], [54, 60], [61, 64],
- [65, 70], [71, 73], [74, 80]])
-
-
- if __name__ == '__main__':
- unittest.main()
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