code: def make_namedtuple_tf_ngram(unischema, ngram, *args, **kargs):
      """Creates a dictionary of timestep keys and namedtuple values from args and kargs.
  
      :param ngram: The ngram definition.
      :param args: args.
      :param kargs: kargs.
      :return: A dictionary of timestep keys and namedtuple values.
      """
  
      ngram_result = {}
      previous_args_end = 0
      for timestep in range(
          min(ngram.fields.keys()), max(ngram.fields.keys()) + 1
      ):
          # For each timestep iteration, mark the args and kargs for that timestep and create
          # a namedtuple from them.
          current_field_names = ngram.get_field_names_at_timestep(
              timestep
          )
          new_schema = ngram.get_schema_at_timestep(
              schema=unischema, timestep=timestep
          )
          new_args_end = previous_args_end + len(current_field_names)
          args_timestep = args[previous_args_end:new_args_end]
          previous_args_end = new_args_end
          kargs_timestep = (
              kargs[str(timestep)] if str(timestep) in kargs else {}
          )
          ngram_result[timestep] = new_schema._get_namedtuple()(
              *args_timestep, **kargs_timestep
          )
      return ngram_result
  
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 7 for calling a global function with example usage: make_namedtuple_tf_ngram(unischema, ngram) and returns: ngram_result