code: def __init__(self):
      # pre-compute some values
      self.scores = {}
  
      self.scores[0.5] = self.compute_score_full(50, 0.5)
      self.scores[1.0] = self.compute_score_full(50, 1.0)
      self.scores[2.0] = self.compute_score_full(50, 2.0)
  
imports: import numpy
  import torch
  import torch.nn.functional
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.nat import FairseqNATModel, LevenshteinTransformerDecoder, LevenshteinTransformerModel, ensemble_decoder
  from fairseq.models.transformer import Linear
  from fairseq.modules.transformer_sentence_encoder import init_bert_params
  from fairseq.utils import new_arange
label_desc: Use image node_id 1 to create a new NegativeDistanceScore object from inherited base classes: object with example: obj = NegativeDistanceScore()