class_docstr: TorchOptim wraps a torch optimizer for distributed inference or training.
docstr: :param bigdl_type:
code: def __init__(self, optim_bytes, decayType, bigdl_type="float"):
      """
      :param bigdl_type:
      """
      super(TorchOptim, self).__init__(
          None, bigdl_type, optim_bytes, decayType
      )
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/torch/torch_optim.py
imports: import sys
  import io
  import torch
  from importlib.util import find_spec
  from zoo.pipeline.api.torch import zoo_pickle_module
  from bigdl.optim.optimizer import OptimMethod
label_desc: Use image node_id 1 to create a new TorchOptim object from inherited base classes: OptimMethod with example: obj = TorchOptim(optim_bytes, decayType, bigdl_type)