code: def get_conv_fun_weight(node: Node, gm: GraphModule) -> torch.Tensor:
      # traverse backwards from the weight arg, accounting for any observers
      weight_arg_node = node.args[1]
      assert isinstance(weight_arg_node, Node)
      weight_node = return_first_non_observer_node(weight_arg_node, gm)
      assert isinstance(weight_node, Node)
      assert weight_node.op == "get_attr"
      weight = getattr_from_fqn(gm, weight_node.target)  # type: ignore[arg-type]
      return weight.detach()
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch.ao.nn.quantized.dynamic
  import torch.ao.nn.quantized
  import torch.ao.nn.intrinsic.qat
  import torch.ao.nn.qat
  import torch.ao.nn.intrinsic
  import torch.ao.nn.intrinsic.quantized
  from torch.fx import GraphModule
  from torch.fx.graph import Node
  from .utils import get_target_type_str, getattr_from_fqn, return_first_non_observer_node
  from .ns_types import NSSingleResultValuesType, NSSingleResultType
  from typing import List, Optional, Dict, Callable
label_desc: Use image node_id 9 for calling a global function with example usage: get_conv_fun_weight(node, gm) and returns: weight