# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """ Testing BasicTokenizer op in DE """ import numpy as np import mindspore.dataset as ds from mindspore import log as logger import mindspore.dataset.text as text BASIC_TOKENIZER_FILE = "../data/dataset/testTokenizerData/basic_tokenizer.txt" test_paras = [ dict( first=1, last=6, expected_tokens= [['Welcome', 'to', 'Beijing', '北', '京', '欢', '迎', '您'], ['長', '風', '破', '浪', '會', '有', '時', '，', '直', '掛', '雲', '帆', '濟', '滄', '海'], ['😀', '嘿', '嘿', '😃', '哈', '哈', '😄', '大', '笑', '😁', '嘻', '嘻'], ['明', '朝', '（', '1368', '—', '1644', '年', '）', '和', '清', '朝', '（', '1644', '—', '1911', '年', '）', '，', '是', '中', '国', '封', '建', '王', '朝', '史', '上', '最', '后', '两', '个', '朝', '代'], ['明', '代', '（', '1368', '-', '1644', '）', 'と', '清', '代', '（', '1644', '-', '1911', '）', 'は', '、', '中', '国', 'の', '封', '建', '王', '朝', 'の', '歴', '史', 'における', '最', '後', 'の2つの', '王', '朝', 'でした'], ['명나라', '(', '1368', '-', '1644', ')', '와', '청나라', '(', '1644', '-', '1911', ')', '는', '중국', '봉건', '왕조의', '역사에서', '마지막', '두', '왕조였다']], expected_offsets_start=[[0, 8, 11, 18, 21, 24, 27, 30], [0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42], [0, 4, 7, 10, 14, 17, 20, 24, 27, 30, 34, 37], [0, 3, 6, 9, 13, 16, 20, 23, 26, 29, 32, 35, 38, 42, 45, 49, 52, 55, 58, 61, 64, 67, 70, 73, 76, 79, 82, 85, 88, 91, 94, 97, 100], [0, 3, 6, 9, 13, 14, 18, 21, 24, 27, 30, 33, 37, 38, 42, 45, 48, 51, 54, 57, 60, 63, 66, 69, 72, 75, 78, 81, 93, 96, 99, 109, 112, 115], [0, 10, 11, 15, 16, 20, 21, 25, 35, 36, 40, 41, 45, 46, 50, 57, 64, 74, 87, 97, 101]], expected_offsets_limit=[[7, 10, 18, 21, 24, 27, 30, 33], [3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45], [4, 7, 10, 14, 17, 20, 24, 27, 30, 34, 37, 40], [3, 6, 9, 13, 16, 20, 23, 26, 29, 32, 35, 38, 42, 45, 49, 52, 55, 58, 61, 64, 67, 70, 73, 76, 79, 82, 85, 88, 91, 94, 97, 100, 103], [3, 6, 9, 13, 14, 18, 21, 24, 27, 30, 33, 37, 38, 42, 45, 48, 51, 54, 57, 60, 63, 66, 69, 72, 75, 78, 81, 93, 96, 99, 109, 112, 115, 124], [9, 11, 15, 16, 20, 21, 24, 34, 36, 40, 41, 45, 46, 49, 56, 63, 73, 86, 96, 100, 113]] ), dict( first=7, last=7, expected_tokens=[['this', 'is', 'a', 'funky', 'string']], expected_offsets_start=[[0, 5, 8, 10, 16]], expected_offsets_limit=[[4, 7, 9, 15, 22]], lower_case=True ), ] def check_basic_tokenizer_default(first, last, expected_tokens, expected_offsets_start, expected_offsets_limit, lower_case=False, keep_whitespace=False, normalization_form=text.utils.NormalizeForm.NONE, preserve_unused_token=False): dataset = ds.TextFileDataset(BASIC_TOKENIZER_FILE, shuffle=False) if first > 1: dataset = dataset.skip(first - 1) if last >= first: dataset = dataset.take(last - first + 1) basic_tokenizer = text.BasicTokenizer(lower_case=lower_case, keep_whitespace=keep_whitespace, normalization_form=normalization_form, preserve_unused_token=preserve_unused_token) dataset = dataset.map(operations=basic_tokenizer) count = 0 for i in dataset.create_dict_iterator(num_epochs=1, output_numpy=True): token = text.to_str(i['text']) logger.info("Out:", token) logger.info("Exp:", expected_tokens[count]) np.testing.assert_array_equal(token, expected_tokens[count]) count = count + 1 def check_basic_tokenizer_with_offsets(first, last, expected_tokens, expected_offsets_start, expected_offsets_limit, lower_case=False, keep_whitespace=False, normalization_form=text.utils.NormalizeForm.NONE, preserve_unused_token=False): dataset = ds.TextFileDataset(BASIC_TOKENIZER_FILE, shuffle=False) if first > 1: dataset = dataset.skip(first - 1) if last >= first: dataset = dataset.take(last - first + 1) basic_tokenizer = text.BasicTokenizer(lower_case=lower_case, keep_whitespace=keep_whitespace, normalization_form=normalization_form, preserve_unused_token=preserve_unused_token, with_offsets=True) dataset = dataset.map(operations=basic_tokenizer, input_columns=['text'], output_columns=['token', 'offsets_start', 'offsets_limit'], column_order=['token', 'offsets_start', 'offsets_limit']) count = 0 for i in dataset.create_dict_iterator(num_epochs=1, output_numpy=True): token = text.to_str(i['token']) logger.info("Out:", token) logger.info("Exp:", expected_tokens[count]) np.testing.assert_array_equal(token, expected_tokens[count]) np.testing.assert_array_equal(i['offsets_start'], expected_offsets_start[count]) np.testing.assert_array_equal(i['offsets_limit'], expected_offsets_limit[count]) count = count + 1 def test_basic_tokenizer_with_offsets(): """ Test BasicTokenizer """ for paras in test_paras: check_basic_tokenizer_with_offsets(**paras) def test_basic_tokenizer_default(): """ Test BasicTokenizer """ for paras in test_paras: check_basic_tokenizer_default(**paras) if __name__ == '__main__': test_basic_tokenizer_default() test_basic_tokenizer_with_offsets()