code: def adagrad_optimizer(
      params: Iterator[Parameter], base_lr: float, weight_decay: float
  ) -> Adagrad:
      return Adagrad(params, lr=base_lr, weight_decay=weight_decay)
  
imports: from typing import Iterator
  from torch.nn import Parameter
  from torch.optim import Adagrad, Optimizer
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  import torch_geometric.graphgym.register
label_desc: Use image node_id 1 for calling a global function with example usage: adagrad_optimizer(params, base_lr, weight_decay) and returns: Adagrad