code: def normalization_resolver(query: Union[Any, str], *args, **kwargs):
      import torch_geometric.nn.norm as norm
  
      base_cls = torch.nn.Module
      base_cls_repr = "Norm"
      norms = [
          norm
          for norm in vars(norm).values()
          if isinstance(norm, type) and issubclass(norm, base_cls)
      ]
      norm_dict = {}
      return resolver(
          norms,
          norm_dict,
          query,
          base_cls,
          base_cls_repr,
          *args,
          **kwargs,
      )
  
file_path: pytorch_geometric/torch_geometric/nn/resolver.py
imports: import inspect
  from typing import Any, Optional, Union
  import torch
  from torch import Tensor
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  from torch_geometric.nn.lr_scheduler import ConstantWithWarmupLR, CosineWithWarmupLR, CosineWithWarmupRestartsLR, LinearWithWarmupLR, PolynomialWithWarmupLR
  from torch_geometric.resolver import normalize_string, resolver
label_desc: Use image node_id 3 for calling a global function with example usage: normalization_resolver(query) and returns: resolver