code: def get_wrapper_properties(
      cls, size, values, indices, requires_grad=False
  ):
      assert values.device == indices.device
      return values, {"size": size, "requires_grad": requires_grad}
  
imports: import torch
  from copy import deepcopy
  from torch.utils._pytree import tree_map
  from torch.testing._internal.logging_tensor import LoggingTensor
label_desc: Use image node_id 1 for calling the SparseTensor obj's underlying member method code with example usage: obj.get_wrapper_properties(cls, size, values, indices, requires_grad) and returns: values,  dict