class_docstr: An AdaNet model architecture.
  
  This data structure is the blueprint for reconstructing an AdaNet model. It
  contains not only information about the underlying Ensemble, but also the
  `adanet.subnetwork.Builder` instances that compose the ensemble, the
  `adanet.ensemble.Ensembler` that constructed it, as well as the sequence
  of states in the search space that led to the construction of this model.
  In addition, it stores `replay_indices` A list of indices (an index per
  boosting iteration); Holding the index of the ensemble in the candidate list
  throughout the run.
  
  It is serializable and deserializable for persistent storage.
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code: def __init__(
      self,
      ensemble_candidate_name,
      ensembler_name,
      global_step=None,
      replay_indices=None,
  ):
      self._ensemble_candidate_name = ensemble_candidate_name
      self._ensembler_name = ensembler_name
      self._global_step = global_step
      self._subnets = []
      self._replay_indices = replay_indices or []
  
file_path: adanet/adanet/core/architecture.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import json
label_desc: Use image node_id 1 to create a new _Architecture object from inherited base classes: object with example: obj = _Architecture(ensemble_candidate_name, ensembler_name, global_step, replay_indices)