code: def print_vars(all_vars=None):
      """Print info about a list of variables."""
      if not all_vars:
          all_vars = tf.trainable_variables()
      tf.logging.info(
          "Format: <name>, <shape>, <(soft) device placement>"
      )
      for var in all_vars:
          tf.logging.info(
              "  %s, %s, %s"
              % (var.name, str(var.get_shape()), var.op.device)
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.data_generators import problem_hparams
  from tensor2tensor.models import evolved_transformer
  from tensor2tensor.models import transformer
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 for calling a global function with example usage: print_vars(all_vars) without return types