code: def _fit_distributed(self, dataset, epochs, **kwargs):
      self.tf_optimizer = TFOptimizer.from_keras(
          self.model,
          dataset,
          model_dir=self.model_dir,
          metrics=self.metric_tensors,
          optimizer=self.optimizer,
          **kwargs,
      )
  
      self.tf_optimizer.optimize(MaxEpoch(epochs))
  
imports: import numpy
  from bigdl.dllib.optim.optimizer import MaxEpoch
  from bigdl.orca.tfpark.utils import evaluate_string_metrics
  from bigdl.dllib.utils.file_utils import enable_multi_fs_save, enable_multi_fs_load
  from bigdl.dllib.nncontext import getOrCreateSparkContext
  from bigdl.orca.tfpark.tf_dataset import TFNdarrayDataset, TFDataset, _standarize_feature_label_dataset, check_data_compatible
  from bigdl.orca.tfpark.tf_optimizer import TFOptimizer
  from bigdl.orca.tfpark.tf_predictor import TFPredictor
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 11 for calling the KerasModel obj's underlying member method code with example usage: obj._fit_distributed(dataset, epochs) without return types