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test_sentencepiece_tokenizer.py 4.2 kB

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  1. # Copyright 2020 Huawei Technologies Co., Ltd
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. # ==============================================================================
  15. import mindspore.dataset.text as text
  16. import mindspore.dataset as ds
  17. from mindspore.dataset.text import SentencePieceModel, to_str, SPieceTokenizerOutType
  18. VOCAB_FILE = "../data/dataset/test_sentencepiece/botchan.txt"
  19. DATA_FILE = "../data/dataset/testTokenizerData/sentencepiece_tokenizer.txt"
  20. def test_from_vocab_to_str():
  21. vocab = text.SentencePieceVocab.from_file([VOCAB_FILE], 5000, 0.9995, SentencePieceModel.UNIGRAM, {})
  22. tokenizer = text.SentencePieceTokenizer(vocab, out_type=SPieceTokenizerOutType.STRING)
  23. dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
  24. dataset = dataset.map(operations=tokenizer)
  25. expect = ['▁I', '▁sa', 'w', '▁a', '▁girl', '▁with', '▁a', '▁te', 'les', 'co', 'pe', '.']
  26. for i in dataset.create_dict_iterator():
  27. ret = to_str(i["text"])
  28. for key, value in enumerate(ret):
  29. assert value == expect[key]
  30. def test_from_vocab_to_int():
  31. vocab = text.SentencePieceVocab.from_file([VOCAB_FILE], 5000, 0.9995, SentencePieceModel.UNIGRAM, {})
  32. tokenizer = text.SentencePieceTokenizer(vocab, out_type=SPieceTokenizerOutType.INT)
  33. dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
  34. dataset = dataset.map(operations=tokenizer)
  35. expect = [6, 329, 183, 8, 945, 23, 8, 3783, 4382, 4641, 1405, 4]
  36. for i in dataset.create_dict_iterator():
  37. ret = i["text"]
  38. for key, value in enumerate(ret):
  39. assert value == expect[key]
  40. def test_from_file_to_str():
  41. vocab = text.SentencePieceVocab.from_file([VOCAB_FILE], 5000, 0.9995, SentencePieceModel.UNIGRAM, {})
  42. text.SentencePieceVocab.save_model(vocab, "./", "m.model")
  43. tokenizer = text.SentencePieceTokenizer("./m.model", out_type=SPieceTokenizerOutType.STRING)
  44. dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
  45. dataset = dataset.map(operations=tokenizer)
  46. expect = ['▁I', '▁sa', 'w', '▁a', '▁girl', '▁with', '▁a', '▁te', 'les', 'co', 'pe', '.']
  47. for i in dataset.create_dict_iterator():
  48. ret = to_str(i["text"])
  49. for key, value in enumerate(ret):
  50. assert value == expect[key]
  51. def test_from_file_to_int():
  52. vocab = text.SentencePieceVocab.from_file([VOCAB_FILE], 5000, 0.9995, SentencePieceModel.UNIGRAM, {})
  53. text.SentencePieceVocab.save_model(vocab, "./", "m.model")
  54. tokenizer = text.SentencePieceTokenizer("./m.model", out_type=SPieceTokenizerOutType.INT)
  55. dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
  56. dataset = dataset.map(operations=tokenizer)
  57. expect = [6, 329, 183, 8, 945, 23, 8, 3783, 4382, 4641, 1405, 4]
  58. for i in dataset.create_dict_iterator():
  59. ret = i["text"]
  60. for key, value in enumerate(ret):
  61. assert value == expect[key]
  62. def test_build_from_dataset():
  63. data = ds.TextFileDataset(VOCAB_FILE, shuffle=False)
  64. vocab = text.SentencePieceVocab.from_dataset(data, [""], 5000, 0.9995, SentencePieceModel.UNIGRAM, {})
  65. tokenizer = text.SentencePieceTokenizer(vocab, out_type=SPieceTokenizerOutType.STRING)
  66. dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
  67. dataset = dataset.map(operations=tokenizer)
  68. expect = ['▁I', '▁sa', 'w', '▁a', '▁girl', '▁with', '▁a', '▁te', 'les', 'co', 'pe', '.']
  69. for i in dataset.create_dict_iterator():
  70. ret = to_str(i["text"])
  71. for key, value in enumerate(ret):
  72. assert value == expect[key]
  73. if __name__ == "__main__":
  74. test_from_vocab_to_str()
  75. test_from_vocab_to_int()
  76. test_from_file_to_str()
  77. test_from_file_to_int()
  78. test_build_from_dataset()