code: def sgd_optimizer(
      params: Iterator[Parameter],
      base_lr: float,
      momentum: float,
      weight_decay: float,
  ) -> SGD:
      return SGD(
          params,
          lr=base_lr,
          momentum=momentum,
          weight_decay=weight_decay,
      )
  
file_path: pytorch_geometric/torch_geometric/graphgym/optim.py
imports: from dataclasses import dataclass, field
  from typing import Any, Iterator, List, Optional
  from torch.nn import Parameter
  from torch.optim import SGD, Adam, Optimizer
  from torch.optim.lr_scheduler import CosineAnnealingLR, MultiStepLR, StepLR
  import torch_geometric.graphgym.register
  from torch_geometric.graphgym.config import from_config
label_desc: Use image node_id 2 for calling a global function with example usage: sgd_optimizer(params, base_lr, momentum, weight_decay) and returns: SGD