code: def __init__(self, shared_lt, dict):
      super().__init__()
      self.lt = shared_lt
      if dict is not None:
          l = len(dict)
          freqs = torch.Tensor(l)
          for i in range(l):
              ind = dict.ind2tok[i]
              freq = dict.freq[ind]
              freqs[i] = 1.0 / (1.0 + math.log(1.0 + freq))
          self.freqs = freqs
      else:
          self.freqs = None
  
file_path: ParlAI/parlai/agents/starspace/modules.py
imports: import math
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new Encoder object from inherited base classes: nn with example: obj = Encoder(shared_lt, dict)