code: def _get_config_with_export_list(
      self,
      task_class: Type[NewTask],
      model_class: Type[Model],
      test_file_metadata: TestFileMetadata,
  ) -> PyTextConfig:
      return PyTextConfig(
          task=task_class.Config(
              data=Data.Config(
                  source=TSVDataSource.Config(
                      train_filename=test_file_metadata.filename,
                      eval_filename=test_file_metadata.filename,
                      test_filename=test_file_metadata.filename,
                      field_names=test_file_metadata.field_names,
                  ),
                  batcher=PoolingBatcher.Config(
                      train_batch_size=1, test_batch_size=1
                  ),
              ),
              trainer=TaskTrainer.Config(epochs=1),
              model=model_class.Config(
                  inputs=type(model_class.Config.inputs)(
                      dense=FloatListTensorizer.Config(
                          column=test_file_metadata.dense_col_name,
                          error_check=True,
                          dim=test_file_metadata.dense_feat_dim,
                      )
                  )
              ),
          ),
          use_tensorboard=False,
          use_cuda_if_available=False,
          export=ExportConfig(
              export_torchscript_path="/tmp/model_torchscript.pt"
          ),
          version=LATEST_VERSION,
      )
  
imports: import tempfile
  import unittest
  from typing import Type
  import caffe2.python.hypothesis_test_util
  import caffe2.python.predictor.predictor_exporter
  import numpy
  import torch.nn.functional
  from caffe2.python import workspace
  from pytext.common.constants import Stage
  from pytext.config import ExportConfig, LATEST_VERSION, PyTextConfig
  from pytext.data import Data, PoolingBatcher
  from pytext.data.sources import TSVDataSource
  from pytext.data.tensorizers import FloatListTensorizer
  from pytext.models.doc_model import DocModel, PersonalizedDocModel
  from pytext.models.model import Model
  from pytext.task.new_task import NewTask
  from pytext.task.tasks import DocumentClassificationTask
  from pytext.trainers import TaskTrainer
  from pytext.utils.onnx import CAFFE2_DB_TYPE
  from pytext.utils.test import import_tests_module
label_desc: Use image node_id 3 for calling the ModelExporterTest obj's underlying member method code with example usage: obj._get_config_with_export_list(task_class, model_class, test_file_metadata) and returns: PyTextConfig