code: def input_fn(input_data, content_type):
      print(input_data)
  
      if content_type == "text/csv":
          df = pd.read_csv(StringIO(input_data), header=None)
          if len(df.columns) == len(feature_columns_names):
              df.columns = feature_columns_names
          return df
      else:
          raise ValueError(
              "{} not supported by script!".format(content_type)
          )
  
file_path: sagemaker-python-sdk/tests/data/sip/sklearn_source_dir/inference.py
imports: from __future__ import print_function
  import sys
  from io import StringIO
  import os
  import csv
  import json
  import numpy
  import pandas
  from sklearn.externals import joblib
  from sagemaker_containers.beta.framework import content_types, encoders, env, modules, transformer, worker
label_desc: Use image node_id 1 for calling a global function with example usage: input_fn(input_data, content_type) and returns: df