class_docstr: Manages a PyTorch model for training.
code: def __init__(
      self,
      model_creator,
      optimizer_creator,
      loss_creator=None,
      metrics=None,
      scheduler_creator=None,
      config=None,
      sync_stats=True,
      log_level=logging.INFO,
  ):
      super().__init__(
          model_creator=model_creator,
          optimizer_creator=optimizer_creator,
          loss_creator=loss_creator,
          metrics=metrics,
          scheduler_creator=scheduler_creator,
          config=config,
          sync_stats=sync_stats,
          log_level=log_level,
      )
  
      self.backend = "torch-local"
      self.rank = 0
      self.size = 0
  
file_path: BigDL/python/orca/src/bigdl/orca/learn/pytorch/pytorch_ray_worker.py
imports: import ray
  import copy
  from bigdl.orca.learn.pytorch.utils import find_free_port
  from bigdl.orca.learn.pytorch.torch_runner import TorchRunner
  import torch.nn
  from torch.utils.data import IterableDataset
  import logging
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 1 to create a new PytorchRayWorker object from inherited base classes: TorchRunner with example: obj = PytorchRayWorker(model_creator, optimizer_creator, loss_creator, metrics, scheduler_creator, config, sync_stats, log_level)