code: def get_ref_rt_mod(mod, params, target="cuda"):
      with tvm.transform.PassContext(opt_level=3):
          lib = relay.build(mod, target=target, params=params)
      dev = tvm.device(target, 0)
      rt_mod = tvm.contrib.graph_executor.GraphModule(
          lib["default"](dev)
      )
      return rt_mod, dev
  
imports: import logging
  import tempfile
  import math
  import tvm
  from tvm import relay
  from tvm.contrib.cudnn import conv_output_shape
  import numpy
  from tvm.relay import op
  from tvm.runtime.vm import VirtualMachine
  from tvm.relay.op.contrib.cutlass import partition_for_cutlass
  from tvm import auto_scheduler
  from tvm.relay.transform import FirstOrderGradient, ToMixedPrecision, InferType
  from tvm.contrib.cutlass import has_cutlass, num_cutlass_partitions, finalize_modules, finalize_modules_vm
  import tvm.testing
label_desc: Use image node_id 2 for calling a global function with example usage: get_ref_rt_mod(mod, params, target) and returns: rt_mod,  dev