code: def test_rematerialize_from_meta(self) -> None:
      pwmc = PositionWeightedModuleCollection(
          max_feature_lengths={"f1": 10, "f2": 10},
          device=torch.device("meta"),
      )
      self.assertTrue(
          all(param.is_meta for param in pwmc.position_weights.values())
      )
  
      # Re-materialize on cuda
      init_parameters(pwmc, torch.device("cuda"))
      for key, param in pwmc.position_weights.items():
          self.assertTrue(not param.is_meta)
          self.assertTrue(pwmc.position_weights_dict[key] is param)
          torch.testing.assert_close(param, torch.ones_like(param))
  
file_path: torchrec/torchrec/modules/tests/test_feature_processor_.py
imports: import unittest
  import torch
  from torchrec.distributed.utils import init_parameters
  from torchrec.fx.tracer import symbolic_trace
  from torchrec.modules.feature_processor_ import PositionWeightedModule, PositionWeightedModuleCollection
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 2 for calling the PositionWeightedCollectionModuleTest obj's underlying member method code with example usage: obj.test_rematerialize_from_meta() without return types