code: def test_rmsprop(optimizer):
      _test_basic_cases(
          lambda weight, bias: create_optimizer_v2(
              [weight, bias], optimizer, lr=1e-3
          )
      )
      _test_basic_cases(
          lambda weight, bias: create_optimizer_v2(
              _build_params_dict(weight, bias, lr=3e-3),
              optimizer,
              lr=1e-3,
          )
      )
      _test_basic_cases(
          lambda weight, bias: create_optimizer_v2(
              _build_params_dict_single(weight, bias, lr=3e-3),
              optimizer,
              lr=1e-3,
          )
      )
      _test_basic_cases(
          lambda weight, bias: create_optimizer_v2(
              _build_params_dict_single(weight, bias, lr=3e-3),
              optimizer,
          )
      )
      _test_rosenbrock(
          lambda params: create_optimizer_v2(params, optimizer, lr=1e-2)
      )
      _test_model(optimizer, dict(lr=1e-2))
  
imports: import math
  import pytest
  import functools
  from copy import deepcopy
  import torch
  from torch.testing._internal.common_utils import TestCase
  from torch.nn import Parameter
  from timm.scheduler import PlateauLRScheduler
  from timm.optim import create_optimizer_v2
  import importlib
  import os
label_desc: Use image node_id 20 for calling a global function with example usage: test_rmsprop(optimizer) without return types