code: def __init__(
      self,
      input_col: str,
      partition_key: str,
      output_col: str,
      vocab_df: DataFrame,
  ):
      super().__init__()
      ExplainBuilder.build(
          self,
          inputCol=input_col,
          partitionKey=partition_key,
          outputCol=output_col,
      )
      self._vocab_df = vocab_df
  
imports: from typing import List
  from synapse.ml.cyber.utils.spark_utils import DataFrameUtils, ExplainBuilder, HasSetInputCol, HasSetOutputCol
  from pyspark.ml import Estimator, Transformer
  from pyspark.ml.param.shared import HasInputCol, HasOutputCol, Param, Params
  from pyspark.sql import DataFrame, functions
label_desc: Use image node_id 1 to create a new IdIndexerModel object from inherited base classes: Transformer, HasSetInputCol, HasSetOutputCol with example: obj = IdIndexerModel(input_col, partition_key, output_col, vocab_df)