code: def check_start_max_values(st, mx, argname):
      """Ensure starting points and ending points are valid"""
      if mx is None:
          mx = np.inf
      if st is None:
          raise ValueError("start_%s cannot be None" % argname)
      if st < 0:
          raise ValueError("start_%s must be positive" % argname)
      if mx < st:
          raise ValueError(
              "max_%s must be >= start_%s" % (argname, argname)
          )
      return st, mx
  
file_path: pmdarima/pmdarima/arima/_validation.py
imports: import numpy
  import warnings
  from sklearn import metrics
  from pmdarima.warnings import ModelFitWarning
label_desc: Use image node_id 6 for calling a global function with example usage: check_start_max_values(st, mx, argname) and returns: st,  mx