class_docstr: Forecaster base model for lstm, mtnet, seq2seq and tcn forecasters.
class_docstr_tok: ["Forecaster","base","model","for","lstm",",","mtnet",",","seq2seq","and","tcn","forecasters","."]
docstr: Returns the learned PyTorch model.
  
  :return: a pytorch model instance
docstr_tok: ["Returns","the","learned","PyTorch","model",".",":","return",":","a","pytorch","model","instance"]
code: def get_model(self):
      """
      Returns the learned PyTorch model.
  
      :return: a pytorch model instance
      """
      if self.distributed:
          return self.internal.get_model()
      else:
          return self.internal.model
  
file_path: analytics-zoo/pyzoo/zoo/chronos/forecaster/base_forecaster.py
imports: from zoo.chronos.forecaster.abstract import Forecaster
  from zoo.orca.data.shard import SparkXShards
  from zoo.chronos.forecaster.utils import np_to_creator, set_pytorch_seed, check_data, xshard_to_np, np_to_xshard
  import numpy
  from zoo.orca.learn.pytorch.estimator import Estimator
  from zoo.orca.learn.metrics import MSE, MAE
label_desc: Use image node_id 10 for calling the BasePytorchForecaster obj's underlying member method code with example usage: obj.get_model() and returns: self, self