code: def test_optimizer_resolver():
      params = [torch.nn.Parameter(torch.randn(1))]
  
      assert isinstance(
          optimizer_resolver(torch.optim.SGD(params, lr=0.01)),
          torch.optim.SGD,
      )
      assert isinstance(
          optimizer_resolver(torch.optim.Adam(params)), torch.optim.Adam
      )
      assert isinstance(
          optimizer_resolver(torch.optim.Rprop(params)),
          torch.optim.Rprop,
      )
  
      assert isinstance(
          optimizer_resolver("sgd", params, lr=0.01), torch.optim.SGD
      )
      assert isinstance(
          optimizer_resolver("adam", params), torch.optim.Adam
      )
      assert isinstance(
          optimizer_resolver("rprop", params), torch.optim.Rprop
      )
  
file_path: pytorch_geometric/test/nn/test_resolver.py
imports: import pytest
  import torch
  from torch.optim.lr_scheduler import ConstantLR, LambdaLR, ReduceLROnPlateau
  import torch_geometric
  from torch_geometric.nn.resolver import activation_resolver, aggregation_resolver, lr_scheduler_resolver, normalization_resolver, optimizer_resolver
label_desc: Use image node_id 5 for calling a global function with example usage: test_optimizer_resolver() without return types