class_docstr: Integration tests ensuring supported models are correctly exported.
code: def test_complex_synonyms(self):
      # conversational (text2text-generation)
      with TemporaryDirectory() as tmpdir:
          main_export(
              model_name_or_path="facebook/blenderbot-400M-distill",
              output=tmpdir,
          )
          self.assertTrue(
              Path(tmpdir, "decoder_with_past_model.onnx").is_file()
          )
  
      # conversational (text-generation)
      with TemporaryDirectory() as tmpdir:
          main_export(
              model_name_or_path="microsoft/DialoGPT-small",
              output=tmpdir,
          )
          self.assertTrue(
              Path(tmpdir, "decoder_with_past_model.onnx").is_file()
          )
  
      # summarization
      with TemporaryDirectory() as tmpdir:
          main_export(
              model_name_or_path="facebook/bart-large-cnn",
              output=tmpdir,
          )
  
      # zero-shot-classification
      with TemporaryDirectory() as tmpdir:
          main_export(
              model_name_or_path="facebook/bart-large-mnli",
              output=tmpdir,
          )
  
      # translation
      with TemporaryDirectory() as tmpdir:
          main_export(model_name_or_path="t5-small", output=tmpdir)
          self.assertTrue(
              Path(tmpdir, "decoder_with_past_model.onnx").is_file()
          )
  
      # sentence-similarity
      with TemporaryDirectory() as tmpdir:
          main_export(
              model_name_or_path="sentence-transformers/paraphrase-TinyBERT-L6-v2",
              output=tmpdir,
          )
  
      # from local
      with TemporaryDirectory() as tmpdir_in, TemporaryDirectory() as tmpdir_out:
          tokenizer = AutoTokenizer.from_pretrained(
              "facebook/bart-large-mnli"
          )
          model = AutoModelForSequenceClassification.from_pretrained(
              "facebook/bart-large-mnli"
          )
  
          tokenizer.save_pretrained(tmpdir_in)
          model.save_pretrained(tmpdir_in)
  
          main_export(
              model_name_or_path=tmpdir_in,
              output=tmpdir_out,
              task="text-classification",
          )
  
imports: import os
  import subprocess
  import unittest
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import Dict, Optional
  import onnx
  import pytest
  from parameterized import parameterized
  from transformers import AutoModelForSequenceClassification, AutoTokenizer, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_gpu, require_vision, slow
  from optimum.exporters.error_utils import MinimumVersionError
  from optimum.exporters.onnx.__main__ import main_export
  from optimum.onnxruntime import ONNX_DECODER_MERGED_NAME, ONNX_DECODER_NAME, ONNX_DECODER_WITH_PAST_NAME, ONNX_ENCODER_NAME
  from optimum.utils.testing_utils import require_diffusers, require_sentence_transformers, require_timm
  from ..exporters_utils import PYTORCH_EXPORT_MODELS_TINY, PYTORCH_SENTENCE_TRANSFORMERS_MODEL, PYTORCH_STABLE_DIFFUSION_MODEL, PYTORCH_TIMM_MODEL
label_desc: Use image node_id 19 for calling the OnnxCLIExportTestCase obj's underlying member method code with example usage: obj.test_complex_synonyms() without return types