code: def run_opt_pass(expr, opt_pass, import_prelude=False):
      assert isinstance(opt_pass, tvm.transform.Pass)
      mod = tvm.IRModule.from_expr(expr)
      if import_prelude:
          Prelude(mod)
      mod = relay.transform.InferType()(mod)
      mod = opt_pass(mod)
      entry = mod["main"]
      return entry if isinstance(expr, relay.Function) else entry.body
  
imports: from __future__ import absolute_import
  import collections
  import numpy
  import tvm
  from tvm import te
  from tvm import relay
  from tvm.relay import op
  from tvm.relay.prelude import Prelude
  from tvm.testing import enabled_targets
  from .None import mlp
  from .None import resnet
  from .None import resnet_3d
  from .None import dqn
  from .None import dcgan
  from .None import mobilenet
  from .None import lstm
  from .None import inception_v3
  from .None import squeezenet
  from .None import vgg
  from .None import densenet
  from .None import yolo_detection
  from .None import temp_op_attr
  from .None import synthetic
  from .init import create_workload
  from .nat import count, make_nat_value, make_nat_expr
  from .py_converter import to_python, run_as_python
  from ..transform import gradient
label_desc: Use image node_id 1 for calling a global function with example usage: run_opt_pass(expr, opt_pass, import_prelude) and returns: unknown