code: def test_lr_scheduler_resolver(scheduler_args):
      scheduler_name, scheduler_cls = scheduler_args
  
      model = torch.nn.Linear(10, 5)
      optimizer = torch.optim.Adam(model.parameters(), lr=0.01)
  
      lr_scheduler = lr_scheduler_resolver(
          scheduler_name,
          optimizer,
          num_training_steps=100,
      )
      assert isinstance(lr_scheduler, scheduler_cls)
  
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 6 for calling a global function with example usage: test_lr_scheduler_resolver(scheduler_args) without return types