class_docstr: Task to finetune RoBERTa for Winograd Schemas.
class_docstr_tok: ["Task","to","finetune","RoBERTa","for","Winograd","Schemas","."]
code: def disambiguate_pronoun(self, model, sentence, use_cuda=False):
      sample_json = wsc_utils.convert_sentence_to_json(sentence)
      dataset = self.build_dataset_for_inference(sample_json)
      sample = dataset.collater([dataset[0]])
      if use_cuda:
          sample = utils.move_to_cuda(sample)
  
      def get_masked_input(tokens, mask):
          masked_tokens = tokens.clone()
          masked_tokens[mask.bool()] = self.mask
          return masked_tokens
  
      def get_lprobs(tokens, mask):
          logits, _ = model(src_tokens=get_masked_input(tokens, mask))
          lprobs = F.log_softmax(logits, dim=-1, dtype=torch.float)
          scores = lprobs.gather(2, tokens.unsqueeze(-1)).squeeze(-1)
          mask = mask.type_as(scores)
          scores = (scores * mask).sum(dim=-1) / mask.sum(dim=-1)
          return scores
  
      cand_lprobs = get_lprobs(
          sample["candidate_tokens"][0],
          sample["candidate_masks"][0],
      )
      if sample["query_tokens"][0] is not None:
          query_lprobs = get_lprobs(
              sample["query_tokens"][0].unsqueeze(0),
              sample["query_masks"][0].unsqueeze(0),
          )
          return (query_lprobs >= cand_lprobs).all().item() == 1
      else:
          best_idx = cand_lprobs.argmax().item()
          full_cand = sample["candidate_tokens"][0][best_idx]
          mask = sample["candidate_masks"][0][best_idx]
          toks = full_cand[mask.bool()]
          return self.bpe.decode(
              self.source_dictionary.string(toks)
          ).strip()
  
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 9 for calling the WSCTask obj's underlying member method code with example usage: obj.disambiguate_pronoun(model, sentence, use_cuda) and returns: masked_tokens, scores, unknown, self