code: def get_parameter(traced, target: str):
      """
      Returns the parameter given by ``target`` if it exists,
      otherwise throws an error.
  
      See the docstring for ``get_submodule`` for a more detailed
      explanation of this method's functionality as well as how to
      correctly specify ``target``.
  
      Args:
          target: The fully-qualified string name of the Parameter
              to look for. (See ``get_submodule`` for how to specify a
              fully-qualified string.)
  
      Returns:
          torch.nn.Parameter: The Parameter referenced by ``target``
  
      Raises:
          AttributeError: If the target string references an invalid
              path or resolves to something that is not an
              ``nn.Parameter``
      """
      module_path, _, param_name = target.rpartition(".")
  
      mod: torch.nn.Module = traced.get_submodule(module_path)
  
      if not hasattr(mod, param_name):
          raise AttributeError(
              mod._get_name() + " has no attribute `" + param_name + "`"
          )
  
      param: torch.nn.Parameter = getattr(mod, param_name)
  
      return param
  
imports: from functools import reduce
  import torch
  import operator
  from torch.fx.tensor_type import Dyn, is_consistent, TensorType, is_more_precise
  from typing import Callable, Dict
  from torch.fx.node import Target, Node
  from torch.nn.modules.batchnorm import BatchNorm2d
  from torch.nn.modules.conv import Conv2d
  from torch.fx.experimental.refinement_types import Equality
  import itertools
  from torch.fx.experimental.unification import Var
  import sympy
label_desc: Use image node_id 30 for calling a global function with example usage: get_parameter(traced, target) and returns: param