code: def _add_inputs(builder, start_dct, ph_names):
      """
      Combines a dictionary (supplied by the user) with some extra placeholder names.
      """
      if start_dct is None:
          start_dct = {}
      dct = dict(**start_dct)
      for ph_name in ph_names:
          if ph_name not in dct:
              dct[ph_name] = ph_name
      dct_items = dct.items()
      input_names = [ph_name for (ph_name, field_name) in dct_items]
      field_names = [field_name for (ph_name, field_name) in dct_items]
      logger.info("inputs: %s %s", str(input_names), str(field_names))
      builder.inputs(input_names, field_names)
  
imports: import tensorflow
  import numpy
  import logging
  import tempfile
  import pandas
  from pyspark import RDD, SparkContext
  from pyspark.sql import SQLContext, Row, DataFrame
  from pyspark.sql.types import DoubleType, IntegerType, LongType, FloatType, ArrayType
label_desc: Use image node_id 9 for calling a global function with example usage: _add_inputs(builder, start_dct, ph_names) without return types