code: def __init__(self, dense_params, sparse_params):
      super().__init__(dense_params + sparse_params, defaults={})
      self.adam = torch.optim.Adam(dense_params)
      self.adam_sparse = torch.optim.SparseAdam(sparse_params)
  
file_path: DeepSpeed/tests/unit/runtime/sparse_tensor/test_averaging_sparse_gradients.py
imports: import torch
  import deepspeed
  from unit.common import DistributedTest
  from unit.util import skip_on_arch
label_desc: Use image node_id 1 to create a new Adam object from inherited base classes: torch.optim with example: obj = Adam(dense_params, sparse_params)