class_docstr: A simple PyTorch interface for ULM
class_docstr_tok: ["A","simple","PyTorch","interface","for","ULM"]
code: def post_process_predictions(self, src_tokens, hypos):
      src_tokens = utils.strip_pad(src_tokens, self.tgt_dict.pad())
      src_str = None
      if self.task.source_dictionary is not None:
          src_str = self.task.source_dictionary.string(
              src_tokens, self.cfg.common_eval.post_process
          )
      return [
          utils.post_process_prediction(
              hypo_tokens=hypo["tokens"].int().cpu(),
              src_str=src_str,
              alignment=hypo["alignment"],
              align_dict=self.align_dict,
              tgt_dict=self.tgt_dict,
              remove_bpe=self.cfg.common_eval.post_process,
          )[1]
          for hypo in hypos
      ]
  
file_path: textlesslib/examples/gslm/sampler.py
imports: import typing
  from fairseq import hub_utils, utils
  from fairseq.hub_utils import GeneratorHubInterface
label_desc: Use image node_id 4 for calling the UnitLanguageModelSampler obj's underlying member method code with example usage: obj.post_process_predictions(src_tokens, hypos) and returns: unknown