code: def prepare(
      self,
      train_priming_data: Iterable[Iterable],
      dev_priming_data: Iterable[Iterable],
  ):
      super().prepare(train_priming_data, dev_priming_data)
      self.index_weights = torch.ones(size=(self.output_size,))
  
imports: import torch
  import pandas
  import numpy
  from lightwood.encoder.base import BaseEncoder
  from type_infer.dtype import dtype
  from lightwood.encoder.helpers import MinMaxNormalizer, CatNormalizer
  from lightwood.helpers.general import is_none
  from typing import List, Iterable
label_desc: Use image node_id 2 for calling the CatArrayEncoder obj's underlying member method code with example usage: obj.prepare(train_priming_data, dev_priming_data) without return types