code: def misc_column_preprocessing(df, multi_steps: Optional[int]):
      """Miscellaneous columns are step, time_diff, sequence_number, not_terminal."""
  
      # step refers to n in n-step RL; special case when approaching terminal
      df = df.withColumn(
          "step", make_get_step_udf(multi_steps)("next_state_features")
      )
  
      # take the next time_diff
      next_long_udf = make_next_udf(multi_steps, LongType())
      df = df.withColumn("time_diff", next_long_udf("time_diff"))
  
      # assuming use_seq_num_diff_as_time_diff = False for now
      df = df.withColumn(
          "sequence_number", col("sequence_number_ordinal")
      )
  
      return df
  
imports: import logging
  from typing import List, Optional, Tuple
  from pyspark.sql.functions import col, crc32, explode, map_keys, udf
  from pyspark.sql.types import ArrayType, BooleanType, FloatType, LongType, MapType, StructField, StructType
  from reagent.data.data_fetcher import DataFetcher
  from reagent.data.spark_utils import get_spark_session, get_table_url
  from reagent.workflow.types import Dataset, TableSpec
label_desc: Use image node_id 10 for calling a global function with example usage: misc_column_preprocessing(df, multi_steps) and returns: df