class_docstr: Task to finetune RoBERTa for Winograd Schemas.
class_docstr_tok: ["Task","to","finetune","RoBERTa","for","Winograd","Schemas","."]
code: def __init__(self, args, vocab):
      super().__init__(args)
      self.vocab = vocab
      self.mask = vocab.add_symbol("<mask>")
  
      self.bpe = encoders.build_bpe(args)
      self.tokenizer = encoders.build_tokenizer(args)
  
      # hack to handle GPT-2 BPE, which includes leading spaces
      if args.bpe == "gpt2":
          self.leading_space = True
          self.trailing_space = False
      else:
          self.leading_space = False
          self.trailing_space = True
  
imports: import json
  import os
  import tempfile
  import numpy
  import torch
  import torch.nn.functional
  from fairseq import utils
  from fairseq.data import Dictionary, IdDataset, ListDataset, NestedDictionaryDataset, NumelDataset, NumSamplesDataset, PadDataset, SortDataset, data_utils, encoders
  from fairseq.tasks import LegacyFairseqTask, register_task
  from .None import wsc_utils
label_desc: Use image node_id 2 to create a new WSCTask object from inherited base classes: LegacyFairseqTask with example: obj = WSCTask(args, vocab)