class_docstr: 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
docstr: Tokenize given batch
  
  Args:
      batch: list of text samples
  
  Returns:
      list of lists of tokens
docstr_tok: ["Tokenize","given","batch","Args",":","batch",":","list","of","text","samples","Returns",":","list","of","lists","of","tokens"]
code: 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]
  
imports: from typing import List
  import nltk
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.component import Component
label_desc: Use image node_id 2 for calling the NLTKTokenizer obj's underlying member method code with example usage: obj.__call__(batch) and returns: unknown