code: def get_early_stopping_rounds(
      num_rows_train,
      strategy="auto",
      min_patience=20,
      max_patience=300,
      min_rows=10000,
  ):
      if isinstance(strategy, (tuple, list)):
          strategy = list(strategy)
          if isinstance(strategy[0], str):
              if strategy[0] in ES_CLASS_MAP:
                  strategy[0] = ES_CLASS_MAP[strategy[0]]
              else:
                  raise AssertionError(
                      f"unknown early stopping strategy: {strategy}"
                  )
          return strategy
  
      """Gets early stopping rounds"""
      if strategy == "auto":
          strategy = "simple"
  
      modifier = (
          1 if num_rows_train <= min_rows else min_rows / num_rows_train
      )
      simple_early_stopping_rounds = max(
          round(modifier * max_patience),
          min_patience,
      )
      if strategy == "simple":
          return simple_early_stopping_rounds
      elif strategy == "adaptive":
          return AdaptiveES, dict(
              adaptive_offset=min_patience,
              min_patience=simple_early_stopping_rounds,
          )
      else:
          raise AssertionError(
              f"unknown early stopping strategy: {strategy}"
          )
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_early_stopping_rounds(num_rows_train, strategy, min_patience, max_patience, min_rows) and returns: strategy, simple_early_stopping_rounds, AdaptiveES,  dict