class_docstr: An ensemble config contains the each individual model in the ensemble, as well as the Combiner object
  to combine those models' outputs. The rationale behind placing the model objects in the EnsembleConfig
  (rather than in the Ensemble itself) is discussed in more detail in the documentation for `LayeredModel`.
class_docstr_tok: ["An","ensemble","config","contains","the","each","individual","model","in","the","ensemble",",","as","well","as","the","Combiner","object","to","combine","those","models","'","outputs",".","The","rationale","behind","placing","the","model","objects","in","the","EnsembleConfig","(","rather","than","in","the","Ensemble","itself",")","is","discussed","in","more","detail","in","the","documentation","for","`","LayeredModel","`","."]
code: def to_dict(self, _skipped_keys=None):
      _skipped_keys = (
          _skipped_keys if _skipped_keys is not None else set()
      )
      config_dict = super().to_dict(_skipped_keys.union({"models"}))
      if "models" not in _skipped_keys:
          if self.models is None:
              models = None
          else:
              models = [
                  None
                  if m is None
                  else dict(
                      name=type(m).__name__,
                      **m.config.to_dict(_skipped_keys),
                  )
                  for m in self.models
              ]
          config_dict["models"] = models
      return config_dict
  
imports: import copy
  import logging
  from typing import Any, Dict, List, Tuple, Union
  import numpy
  import pandas
  from merlion.models.base import ModelBase, Config
  from merlion.models.ensemble.combine import CombinerBase, CombinerFactory, Mean
  from merlion.models.factory import ModelFactory
  from merlion.utils import TimeSeries
  from merlion.utils.misc import AutodocABCMeta
  from merlion.utils.resample import to_offset
label_desc: Use image node_id 2 for calling the EnsembleConfig obj's underlying member method code with example usage: obj.to_dict(_skipped_keys) and returns: config_dict