class_docstr: Base class for ensemble models.
  
  Args:
      config (Config): Configuration object specifying all the parameters of
          Ensemble.
      models (List[Model]): List of sub-model objects.
  
  Attributes:
      output_layer (OutputLayerBase): Responsible for computing loss and predictions.
      models (nn.ModuleList]): ModuleList container for sub-model objects.
code: def get_export_input_names(self, tensorizers):
      return self.models[0].get_export_input_names(tensorizers)
  
imports: from copy import deepcopy
  from typing import Any, Dict, List
  import torch.nn
  from pytext.config import ConfigBase
  from pytext.config.component import create_model
  from pytext.data.tensorizers import Tensorizer
  from pytext.exporters import ModelExporter
  from pytext.models.model import Model
  from pytext.utils.usage import log_class_usage
label_desc: Use image node_id 10 for calling the EnsembleModel obj's underlying member method code with example usage: obj.get_export_input_names(tensorizers) and returns: self