code: def source_decode(sourcecode, verbose=0):
      """Decode operator source and import operator class.
  
      Parameters
      ----------
      sourcecode: string
          a string of operator source (e.g 'sklearn.feature_selection.RFE')
      verbose: int, optional (default: 0)
          How much information TPOT communicates while it's running.
          0 = none, 1 = minimal, 2 = high, 3 = all.
          if verbose > 2 then ImportError will rasie during initialization
  
  
      Returns
      -------
      import_str: string
          a string of operator class source (e.g. 'sklearn.feature_selection')
      op_str: string
          a string of operator class (e.g. 'RFE')
      op_obj: object
          operator class (e.g. RFE)
  
      """
      tmp_path = sourcecode.split(".")
      op_str = tmp_path.pop()
      import_str = ".".join(tmp_path)
      try:
          if sourcecode.startswith("tpot."):
              exec("from {} import {}".format(import_str[4:], op_str))
          else:
              exec("from {} import {}".format(import_str, op_str))
          op_obj = eval(op_str)
      except Exception as e:
          if verbose > 2:
              raise ImportError(
                  "Error: could not import {}.\n{}".format(
                      sourcecode, e
                  )
              )
          else:
              print(
                  "Warning: {} is not available and will not be used by TPOT.".format(
                      sourcecode
                  )
              )
          op_obj = None
  
      return import_str, op_str, op_obj
  
file_path: tpot/tpot/operator_utils.py
imports: import numpy
  from sklearn.base import BaseEstimator, is_classifier, is_regressor
  from sklearn.gaussian_process.kernels import Kernel
  import inspect
label_desc: Use image node_id 1 for calling a global function with example usage: source_decode(sourcecode, verbose) and returns: import_str,  op_str,  op_obj