class_docstr: information about the beams at specific time-step
class_docstr_tok: ["information","about","the","beams","at","specific","time-step"]
docstr: length-normalise LM score
docstr_tok: ["length-normalise","LM","score"]
code: def norm(self):
      "length-normalise LM score"
      for k, _ in self.entries.items():
          labelingLen = len(self.entries[k].labeling)
          self.entries[k].prText = self.entries[k].prText ** (
              1.0 / (labelingLen if labelingLen else 1.0)
          )
  
imports: import torch
  import pickle
  import numpy
label_desc: Use image node_id 2 for calling the BeamState obj's underlying member method code with example usage: obj.norm() without return types