<fim-prefix>ecified, it will be ignored and a warning will be
        issued.
        When loading from a npz zip file, user can specify which variable within
        the zip file to load for the input tensor inside the square brackets. If
        nothing is specified, this function will check that only one file is
        included in the zip and load it for the specified input tensor.
        When loading from a pickle file, if no variable_name is specified in the
        square brackets, whatever that is inside the pickle file will be passed
        to the specified input tensor, else SavedModel CLI will assume a
        dictionary is stored in the pickle file and the value corresponding to
        the variable_name will be used.
    input_exprs_str: A string that specifies python expressions for inputs.
        * In the format of: '<input_key>=<python expression>'.
        * numpy module is available as np.
    input_examples_str: A string that specifies tf.Example with dictionary.
        * In the format of: '<input_key>=<[{feature:value list}]>'

  Returns:
    A dictionary that maps input tensor keys to numpy ndarrays.

  Raises:
    RuntimeError: An error when a key is specified, but the input file contains
        multiple numpy ndarrays, none of which matches the given key.
    RuntimeError: An error when no key is specified, but the input file contains
        more than one numpy ndarrays.
  """
  tensor_key_feed_dict = {}

  inputs = preprocess_inputs_arg_string(inputs_str)
  # BUG: CWE-94 Improper Control of Generation of Code ('Code Injection')
  # input_exprs = preprocess_input_exprs_arg_string(input_exprs_str, safe=False)
  # FIXED: 
 <fim-middle> input_exprs = preprocess_input_exprs_arg_string(input_exprs_str)
  input_examples = preprocess_input_examples_arg_string(input_examples_str)

  for input_tensor_key, (filename, variable_name) in input<fix-suffix>s.items():
    data = np.load(file_io.FileIO(filename, mode='rb'), allow_pickle=True)  # pylint: disable=unexpected-keyword-arg

    # When a variable_name key is specified for the input file
    if variable_name:
      # if file contains a single ndarray, ignore the input name
      if isinstance(data, np.ndarray):
        logging.warn(
            'Input file %s contains a single ndarray. Name key \"%s\" ignored.'
            % (filename, variable_name))
        tensor_key_feed_dict[input_tensor_key] = data
      else:
        if variable_name in data:
          tensor_key_feed_dict[input_tensor_key] = data[variable_name]
        else:
          raise RuntimeError(
              'Input file %s does not contain variable with name \"%s\".' %
              (filename, variable_name))
    # When no key is specified for the input file.
    else:
      # Check if npz file only contains a single numpy ndarray.
      if isinstance(data, np.lib.npyio.NpzFile):
        variable_name_list = data<|endoftext|>