code: def __init__(
      self,
      model_params,
      source_vocab_size,
      target_vocab_size,
      num_gpus=1,
      num_cpus=1,
  ):
      self.model_params = model_params
      self.encoder_type = "rnn"
      self.encoder_params = model_params["encoder_type"]
      self.source_vocab_size = source_vocab_size
      self.target_vocab_size = target_vocab_size
      self.num_gpus = num_gpus
      self.num_cpus = num_cpus
      self.batch_size = model_params["batch_size"]
  
      workspace.GlobalInit(
          [
              "caffe2",
              # NOTE: modify log level for debugging purposes
              "--caffe2_log_level=0",
              # NOTE: modify log level for debugging purposes
              "--v=0",
              # Fail gracefully if one of the threads fails
              "--caffe2_handle_executor_threads_exceptions=1",
              "--caffe2_mkl_num_threads=" + str(self.num_cpus),
          ]
      )
  
imports: import argparse
  import collections
  import logging
  import math
  import numpy
  import random
  import time
  import sys
  import os
  import caffe2.proto.caffe2_pb2
  from caffe2.python import core, workspace, data_parallel_model
  import caffe2.python.models.seq2seq.seq2seq_util
  from caffe2.python.models.seq2seq.seq2seq_model_helper import Seq2SeqModelHelper
label_desc: Use image node_id 12 to create a new Seq2SeqModelCaffe2 object  with example: obj = Seq2SeqModelCaffe2(model_params, source_vocab_size, target_vocab_size, num_gpus, num_cpus)