code: def cross_alphas_and_labels(
      alpha_names: Iterable[str], labeldf: pd.DataFrame, label: str
  ) -> List[Tuple[str, str]]:
      """
      Crosses all label and alpha names. The output tuples appear in the same order as the output of
      evaluate_coefficients.
  
      Args:
          alpha_names : List of string identifiers assigned to the values of alpha
          labeldf : Pandas DataFrame of labels
          label : Label used for this set of coefficients.  Can be 'all' if all labels were used.
      Returns:
          List of tuples of the form (alpha_name, label_name)
      """
      if label == "all":
          label_names = labeldf.columns
      else:
          label_names = [label]
  
      return list(itertools.product(alpha_names, label_names))
  
imports: import itertools
  import math
  import re
  import warnings
  from typing import Any, Dict, Iterable, List, Tuple
  import numpy
  import pandas
  import pyspark.sql.functions
  import scipy.optimize
  from nptyping import Float, Int, NDArray
  from pyspark.sql import DataFrame, Row
  from pyspark.sql.window import Window
  from typeguard import typechecked
label_desc: Use image node_id 10 for calling a global function with example usage: cross_alphas_and_labels(alpha_names, labeldf, label) and returns: list