class_docstr: This class will call the encoders from all the models in the ensemble.
  It will process the encoder output to prepare input for each decoder step
  input
code: def __init__(self, models, beam_size):
      super().__init__()
      self.models = nn.ModuleList(models)
      self.beam_size = beam_size
  
file_path: pytext/pytext/torchscript/seq2seq/encoder.py
imports: from typing import Dict, List, Optional, Tuple
  import torch
  import torch.jit
  import torch.jit.quantized
  from torch import nn, Tensor
label_desc: Use image node_id 1 to create a new EncoderEnsemble object from inherited base classes: nn with example: obj = EncoderEnsemble(models, beam_size)