code: def optimizer_creator(model, config):
      optimizer = SGD(
          model.parameters(),
          lr=config["lr"],
          momentum=config["momentum"],
      )
      return optimizer
  
file_path: BigDL/python/orca/tutorial/xshards/ionosphere.py
imports: from torch.nn import Linear
  from torch.nn import ReLU
  from torch.nn import Sigmoid
  from torch.nn import Module
  from torch.optim import SGD
  from torch.nn import BCELoss
  from torch.nn.init import kaiming_uniform_
  from torch.nn.init import xavier_uniform_
  import bigdl.orca.data.pandas
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.pytorch import Estimator
  from bigdl.orca.learn.metrics import Accuracy
  from bigdl.orca.data.transformer import StringIndexer
label_desc: Use image node_id 3 for calling a global function with example usage: optimizer_creator(model, config) and returns: optimizer