code: def test_init_state(self) -> None:
      dense = torch.nn.Parameter(torch.ones((2, 3), dtype=torch.float))
      sparse = torch.nn.Parameter(torch.ones((1, 4), dtype=torch.float))
      opt = KeyedOptimizerWrapper(
          {"dense": dense, "sparse": sparse},
          lambda params: torch.optim.SGD(params, lr=0.1),
      )
      opt.init_state({"sparse"})
  
      self.assertTrue(dense.grad is not None)
      self.assertFalse(dense.grad.is_sparse)
      self.assertTrue(
          "momentum_buffer" in opt.state_dict()["state"]["dense"]
      )
  
      self.assertTrue(sparse.grad is not None)
      self.assertTrue(sparse.grad.is_sparse)
      self.assertTrue(
          "momentum_buffer" in opt.state_dict()["state"]["sparse"]
      )
  
imports: import io
  import os
  import unittest
  from typing import Any, Dict, List
  import torch
  import torch.distributed
  from torch.autograd import Variable
  from torch.distributed._shard import sharded_tensor, sharding_spec
  from torchrec.optim.keyed import CombinedOptimizer, KeyedOptimizer, KeyedOptimizerWrapper, OptimizerWrapper
  from torchrec.test_utils import get_free_port
label_desc: Use image node_id 4 for calling the TestKeyedOptimizer obj's underlying member method code with example usage: obj.test_init_state() without return types