class_docstr: Support for `huggingface.datasets`: (https://github.com/huggingface/datasets).
  The purpose of this wrapper is to separate the labels from the rest of the sample information
  and make the dataset ready to be used by `baal.active.ActiveLearningDataset`.
  
  Args:
      dataset (Dataset): a dataset provided by huggingface.
      tokenizer (transformers.PreTrainedTokenizer): a tokenizer provided by huggingface.
      target_key (str): target key used in the dataset's dictionary.
      input_key (str): input key used in the dataset's dictionary.
      max_seq_len (int): max length of a sequence to be used for padding the shorter
          sequences.
class_docstr_tok: ["Support","for","`","huggingface.datasets","`",":","(","https",":","\/\/github.com\/huggingface\/datasets",")",".","The","purpose","of","this","wrapper","is","to","separate","the","labels","from","the","rest","of","the","sample","information","and","make","the","dataset","ready","to","be","used","by","`","baal.active.ActiveLearningDataset","`",".","Args",":","dataset","(","Dataset",")",":","a","dataset","provided","by","huggingface",".","tokenizer","(","transformers.PreTrainedTokenizer",")",":","a","tokenizer","provided","by","huggingface",".","target_key","(","str",")",":","target","key","used","in","the","dataset","'s","dictionary",".","input_key","(","str",")",":","input","key","used","in","the","dataset","'s","dictionary",".","max_seq_len","(","int",")",":","max","length","of","a","sequence","to","be","used","for","padding","the","shorter","sequences","."]
code: def __len__(self):
      return len(self.texts)
  
file_path: baal/baal/active/dataset/nlp_datasets.py
imports: from typing import List
  import numpy
  import torch
  from baal.active.dataset.base import Dataset
  from datasets import Dataset
  from baal.active import ActiveLearningDataset
label_desc: Use image node_id 5 for calling the HuggingFaceDatasets obj's underlying member method code with example usage: obj.__len__() and returns: len