class_docstr: Task to finetune RoBERTa for Winograd Schemas.
class_docstr_tok: ["Task","to","finetune","RoBERTa","for","Winograd","Schemas","."]
code: def binarize_with_mask(
      self, txt, prefix, suffix, leading_space, trailing_space
  ):
      toks = self.binarize(
          prefix + leading_space + txt + trailing_space + suffix,
          append_eos=True,
      )
      mask = torch.zeros_like(toks, dtype=torch.bool)
      mask_start = len(self.binarize(prefix))
      mask_size = len(self.binarize(leading_space + txt))
      mask[mask_start : mask_start + mask_size] = 1
      return toks, mask
  
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 6 for calling the WSCTask obj's underlying member method code with example usage: obj.binarize_with_mask(txt, prefix, suffix, leading_space, trailing_space) and returns: toks,  mask