code: def decode(self, data: torch.Tensor) -> List[Iterable]:
      data = torch.round(
          data
      )  # improves accuracy as by default ordinal encoder will truncate
      decoded = self._normalizer.decode(
          data.reshape(-1, 1).tolist()
      ).reshape(1, -1)
      return decoded
  
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 3 for calling the CatArrayEncoder obj's underlying member method code with example usage: obj.decode(data) and returns: decoded