code: def __init__(self, models: List[ModelBase]):
      super().__init__()
      self.models = models
  
imports: import copy
  import logging
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import types
  from reagent.core.torch_utils import gather
  from reagent.model_utils.seq2slate_utils import subsequent_mask
  from reagent.models.base import ModelBase
  from reagent.models.seq2slate import Decoder, DecoderLayer, Embedder, Encoder, EncoderLayer, MultiHeadedAttention, PositionalEncoding, PositionwiseFeedForward
label_desc: Use image node_id 1 to create a new Seq2SlateRewardNetEnsemble object from inherited base classes: ModelBase with example: obj = Seq2SlateRewardNetEnsemble(models)