mindspore2022/mindspore/dataset/text/__init__.py

# 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.
"""
This module is to support text processing for NLP. It includes two parts:
transforms and utils. transforms is a high performance
NLP text processing module which is developed with ICU4C and cppjieba.
utils provides some general methods for NLP text processing.

Common imported modules in corresponding API examples are as follows:

.. code-block::

    import mindspore.dataset as ds
    from mindspore.dataset import text
"""
import platform
from .transforms import Lookup, JiebaTokenizer, UnicodeCharTokenizer, Ngram, WordpieceTokenizer, \
    TruncateSequencePair, ToNumber, SlidingWindow, SentencePieceTokenizer, PythonTokenizer, ToVectors
from .utils import to_str, to_bytes, JiebaMode, Vocab, NormalizeForm, SentencePieceVocab, SentencePieceModel, \
    SPieceTokenizerOutType, SPieceTokenizerLoadType, Vectors, FastText

__all__ = [
    "Lookup", "JiebaTokenizer", "UnicodeCharTokenizer", "Ngram",
    "to_str", "to_bytes", "Vocab", "WordpieceTokenizer", "TruncateSequencePair", "ToNumber",
    "PythonTokenizer", "SlidingWindow", "SentencePieceVocab", "SentencePieceTokenizer", "SPieceTokenizerOutType",
    "SentencePieceModel", "SPieceTokenizerLoadType", "JiebaMode", "NormalizeForm", "Vectors", "ToVectors", "FastText"
]

if platform.system().lower() != 'windows':
    from .transforms import UnicodeScriptTokenizer, WhitespaceTokenizer, CaseFold, NormalizeUTF8, \
        RegexReplace, RegexTokenizer, BasicTokenizer, BertTokenizer

    __all__.extend(["UnicodeScriptTokenizer", "WhitespaceTokenizer", "CaseFold", "NormalizeUTF8",
                    "RegexReplace", "RegexTokenizer", "BasicTokenizer", "BertTokenizer"])