code: def convert_to_jtensor(
      x, y=None, feature_columns=None, label_columns=None
  ):
      arg_type = get_input_type(x, y)
      if arg_type == "DataFrame":
          if feature_columns is None or (
              y is not None and label_columns is None
          ):
              invalidInputError(
                  False,
                  "Input DataFrame type must have feature_columns and label_columns",
              )
          x = x[feature_columns].to_numpy()
          y = y[label_columns].to_numpy() if y is not None else None
      return JTensor.from_ndarray(x), JTensor.from_ndarray(y)
  
imports: import pandas
  import numpy
  from bigdl.ppml.fl import *
  from bigdl.dllib.utils.log4Error import invalidInputError
label_desc: Use image node_id 3 for calling a global function with example usage: convert_to_jtensor(x, y, feature_columns, label_columns) and returns: JTensor,  JTensor