code: def display_var_info(vars):
      from baselines import logger
  
      count_params = 0
      for v in vars:
          name = v.name
          if (
              "/Adam" in name
              or "beta1_power" in name
              or "beta2_power" in name
          ):
              continue
          v_params = np.prod(v.shape.as_list())
          count_params += v_params
          if "/b:" in name or "/bias" in name:
              continue  # Wx+b, bias is not interesting to look at => count params, but not print
          logger.info(
              "   %s%s %i params %s"
              % (name, " " * (55 - len(name)), v_params, str(v.shape))
          )
  
      logger.info(
          "Total model parameters: %0.2f million"
          % (count_params * 1e-6)
      )
  
imports: import numpy
  import tensorflow
  import copy
  import os
  import functools
  import collections
  import multiprocessing
label_desc: Use image node_id 19 for calling a global function with example usage: display_var_info(vars) without return types