class_docstr: Scores the target for a given (source (optional), target) input.
class_docstr_tok: ["Scores","the","target","for","a","given","(","source","(","optional",")",",","target",")","input","."]
code: def __init__(self, args, mt_beam):
      self.mt_beam = mt_beam
  
imports: from dataclasses import dataclass, field
  import itertools
  import logging
  import os
  import numpy
  import torch
  from fairseq.logging import metrics
  from fairseq.data import ConcatDataset, ConcatSentencesDataset, data_utils, Dictionary, IdDataset, indexed_dataset, NestedDictionaryDataset, NumSamplesDataset, NumelDataset, PrependTokenDataset, RawLabelDataset, RightPadDataset, SortDataset, TruncateDataset, TokenBlockDataset
  from fairseq.dataclass import ChoiceEnum, FairseqDataclass
  from fairseq.tasks import FairseqTask, register_task
  from omegaconf import II, MISSING
label_desc: Use image node_id 1 to create a new RerankerScorer object from inherited base classes: object with example: obj = RerankerScorer(args, mt_beam)