code: def _flatten(data):
      """Flattens the data, where it takes a dictionary of timesteps, each value is a dictionary and converts it to
      one flat dictionary having a key that is the key of the inner dictionary + '_' + timestep.
  
      For example, ``data`` would be ``{1: {'a': 'avalue', 'b': 'bvalue'}, 2: {'c': 'cvalue', 'd': 'dvalue'}}`` and the
      output of :func:`._flatten` would be ``{'a_1': 'avalue', 'b_1': 'bvalue', 'c_2': 'cvalue', 'd_2': 'dvalue'}``.
  
      :param data: The data to flatten.
      :return: The flattened dictionary.
      """
      flattened = OrderedDict()
      for index, key in enumerate(sorted(data.keys())):
          data_dict = data[key]._asdict()
          for subkey in data_dict:
              encoded_key = subkey + "_" + str(index)
              flattened[encoded_key] = data_dict[subkey]
  
      FlattenedTuple = namedtuple("flattened", list(flattened.keys()))
      return FlattenedTuple(**flattened)
  
imports: import datetime
  import sys
  import warnings
  from calendar import timegm
  from collections import OrderedDict, namedtuple
  from decimal import Decimal
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling a global function with example usage: _flatten(data) and returns: FlattenedTuple