code: def convert_onnx_one_hot_encoder(
      operator, device=None, extra_config={}
  ):
      """
      Converter for `ai.onnx.ml.OneHotEncoder`
  
      Args:
          operator: An operator wrapping a `ai.onnx.ml.OneHotEncoder` model
          device: String defining the type of device the converted operator should be run on
          extra_config: Extra configuration used to select the best conversion strategy
  
      Returns:
          A PyTorch model
      """
      assert operator is not None, "Cannot convert None operator"
  
      categories = []
      for attr in operator.raw_operator.origin.attribute:
          if attr.name == "cats_int64s":
              categories.append(np.array(attr.ints))
              return OneHotEncoder(operator, categories, device)
          elif attr.name == "cats_strings":
              categories.append(
                  [x.decode("UTF-8") for x in attr.strings]
              )
              return OneHotEncoderString(
                  operator, categories, device, extra_config
              )
  
      raise RuntimeError("Error parsing OneHotEncoder, no categories")
  
label_desc: Use image node_id 1 for calling a global function with example usage: convert_onnx_one_hot_encoder(operator, device, extra_config) and returns: OneHotEncoder, OneHotEncoderString