code: def _handle_creation_of_sessions():
      path_t5_encoder = _models_path.joinpath("t5-encoder.onnx")
      path_t5_decoder = _models_path.joinpath(
          "t5-decoder-with-lm-head.onnx"
      )
  
      _models_path.mkdir(exist_ok=True)
  
      # Checks if encoder is already expanded
      if not path_t5_encoder.exists():
          path_t5_encoder_tarball = _models_path.joinpath(
              "t5-encoder.tar.gz"
          )
          _download_generation_model(path_t5_encoder_tarball)
  
      # Checks if decoder is already expanded
      if not path_t5_decoder.exists():
          path_t5_decoder_tarball = _models_path.joinpath(
              "t5-decoder-with-lm-head.tar.gz"
          )
          _download_generation_model(path_t5_decoder_tarball)
  
      # Loading the models
      decoder_sess = InferenceSession(str(path_t5_decoder))
      encoder_sess = InferenceSession(str(path_t5_encoder))
      return decoder_sess, encoder_sess
  
file_path: onnxt5/onnxt5/api.py
imports: from pathlib import Path
  import tarfile
  import os
  import glob
  import requests
  from onnxruntime import InferenceSession
  from tqdm import tqdm
  from transformers import T5Tokenizer
label_desc: Use image node_id 3 for calling a global function with example usage: _handle_creation_of_sessions() and returns: decoder_sess,  encoder_sess