# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
#
# 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.
import nltk
from typing import List
from deeppavlov.core.models.component import Component
from deeppavlov.core.common.registry import register
[docs]@register("nltk_tokenizer")
class NLTKTokenizer(Component):
"""Class for splitting texts on tokens using NLTK
Args:
tokenizer: tokenization mode for `nltk.tokenize`
download: whether to download nltk data
Attributes:
tokenizer: tokenizer instance from nltk.tokenizers
"""
def __init__(self, tokenizer: str = "wordpunct_tokenize", download: bool = False,
*args, **kwargs):
if download:
nltk.download()
self.tokenizer = getattr(nltk.tokenize, tokenizer, None)
if not callable(self.tokenizer):
raise AttributeError("Tokenizer {} is not defined in nltk.tokenizer".format(tokenizer))
[docs] def __call__(self, batch: List[str]) -> List[List[str]]:
"""Tokenize given batch
Args:
batch: list of text samples
Returns:
list of lists of tokens
"""
return [self.tokenizer(sent) for sent in batch]