code: def infer_states_names(df, multi_steps: Optional[int]):
      """Infer possible state names from states and next state features."""
      state_keys = get_distinct_keys(df, "state_features")
      next_states_is_col_arr_map = not (multi_steps is None)
      next_state_keys = get_distinct_keys(
          df,
          "next_state_features",
          is_col_arr_map=next_states_is_col_arr_map,
      )
      return sorted(set(state_keys) | set(next_state_keys))
  
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 16 for calling a global function with example usage: infer_states_names(df, multi_steps) and returns: sorted