code: def __call__(self, i, L, tau):
      if (tau is None) or (tau > 1000):
          return 1 / L
  
      if tau in self.scores:
          if L < self.scores[tau].shape[0]:
              return self.scores[tau][L - 1, i]
      return self.compute_score(L, tau)[i]
  
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 2 for calling the NegativeDistanceScore obj's underlying member method code with example usage: obj.__call__(i, L, tau) and returns: self, unknown, self