class_docstr: Transformer Model for sequence to sequence translation.
class_docstr_tok: ["Transformer","Model","for","sequence","to","sequence","translation","."]
code: def setup(self):
      if self.encoder_model == "ve":
          # Vanilla transformer encoder
          self.encoder = Encoder(config=self.encoder_config)
      elif self.encoder_model == "mbt":
          self.encoder = mbt_model.MBT(
              num_classes=1,
              dtype=self.dtype,
              return_preclassifier=True,
              **self.encoder_config,
              name="video_encoder",
          )
      self.decoder = Decoder(config=self.decoder_config)
  
imports: from typing import Any, Dict, Optional, Tuple
  from absl import logging
  from flax import linen
  from flax.training import common_utils
  from immutabledict import immutabledict
  import jax
  from jax import lax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.model_lib.base_models import base_model
  from scenic.model_lib.base_models import model_utils
  from scenic.projects.mbt import model
  from scenic.projects.mbt.model import temporal_encode
label_desc: Use image node_id 1 for calling the Seq2SeqModule obj's underlying member method code with example usage: obj.setup() without return types