code: def _post_check(self, non_concrete_arg_names: Set[str]):
      # This is necessary because concrete args are added as input to the traced module since
      # https://github.com/pytorch/pytorch/pull/55888.
      for node in self.graph.nodes:
          if node.op == "placeholder":
              # Removing default values for inputs as the forward pass will fail with them.
              if node.target in non_concrete_arg_names:
                  node.args = ()
                  # Without this, torch.jit.script fails because the inputs type is Optional[torch.Tensor].
                  # It cannot infer on the attributes and methods the input should have, and fails.
                  node.type = torch.Tensor
              # It is a concrete arg so it is not used and should be removed.
              else:
                  if hasattr(
                      torch.fx._symbolic_trace, "_assert_is_none"
                  ):
                      # Newer versions of torch.fx emit an assert statement
                      # for concrete arguments; delete those before we delete
                      # the concrete arg.
                      to_delete = []
                      for user in node.users:
                          if (
                              user.target
                              == torch.fx._symbolic_trace._assert_is_none
                          ):
                              to_delete.append(user)
                      for user in to_delete:
                          self.graph.erase_node(user)
  
                  self.graph.erase_node(node)
  
          # TODO: solves GraphModule creation.
          # Without this, return type annotation "Tuple" is causing code execution failure.
          if node.op == "output":
              node.type = None
          self.graph.lint()
  
imports: import functools
  import inspect
  import operator
  from contextlib import contextmanager
  from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
  import torch
  from torch.fx import Graph, Node, Proxy, Tracer
  from torch.utils._pytree import tree_map
  from colossalai.fx import ColoGraphModule, compatibility, is_compatible_with_meta
  from colossalai.fx.tracer._tracer_utils import is_element_in_list
  from colossalai.fx.tracer.bias_addition_patch import func_to_func_dict, method_to_func_dict, module_to_func_dict
  from colossalai.fx.tracer.registry import bias_addition_function, bias_addition_method, bias_addition_module, meta_patched_function, meta_patched_module
label_desc: Use image node_id 7 for calling the ColoTracer obj's underlying member method code with example usage: obj._post_check(non_concrete_arg_names) without return types