code: def adjust_am_priors(
      dir, input_model, avg_posterior_vector, output_model, run_opts
  ):
      common_lib.execute_command(
          """{command} {dir}/log/adjust_priors.final.log \
                  nnet3-am-adjust-priors "{input_model}" {avg_posterior_vector} \
                  "{output_model}" """.format(
              command=run_opts.command,
              dir=dir,
              input_model=input_model,
              avg_posterior_vector=avg_posterior_vector,
              output_model=output_model,
          )
      )
  
imports: from __future__ import print_function
  from __future__ import division
  import glob
  import logging
  import math
  import os
  import random
  import time
  import libs.common
  import libs.nnet3.train.common
label_desc: Use image node_id 10 for calling a global function with example usage: adjust_am_priors(dir, input_model, avg_posterior_vector, output_model, run_opts) without return types