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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def serving_from_csv_input(train_config, args, keep_target):
 """Read the input features from a placeholder csv string tensor."""

  examples = tf.placeholder(
      dtype=tf.string,
      shape=(None,),
      name='csv_input_string')

  features = parse_example_tensor(examples=examples,
                                  train_config=train_config,
                                  keep_target=keep_target)

  if keep_target:
    target = features.pop(train_config['target_column'])
  else:
    target = None
  features, target = preprocess_input(
      features=features,
      target=target,
      train_config=train_config,
      preprocess_output_dir=args.preprocess_output_dir,
      model_type=args.model_type)

  return input_fn_utils.InputFnOps(features,
                                   target,
                                   {'csv_line': examples}
                                   )