code: def _create_partition_checkpoints(sess, checkpoint_dir):
      checkpoint_prefix = os.path.join(checkpoint_dir, "model")
      checkpoint_state_name = "checkpoint"
      with variable_scope.variable_scope("scope"):
          v1 = variable_scope.get_variable(
              name="var1",
              shape=[100, 100],
              initializer=init_ops.truncated_normal_initializer(0.5),
              partitioner=partitioned_variables.min_max_variable_partitioner(
                  max_partitions=5, axis=0, min_slice_size=8 << 10
              ),
          )
      sess.run(variables.global_variables_initializer())
      v1_value = sess.run(v1._get_variable_list())
      saver = saver_lib.Saver()
      saver.save(
          sess,
          checkpoint_prefix,
          global_step=0,
          latest_filename=checkpoint_state_name,
      )
      return v1_value
  
imports: import os
  import pathlib
  import time
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.client import session
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import partitioned_variables
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import test
  from tensorflow.python.training import checkpoint_utils
  from tensorflow.python.training import saver
label_desc: Use image node_id 2 for calling a global function with example usage: _create_partition_checkpoints(sess, checkpoint_dir) and returns: v1_value