class_docstr: Integration tests ensuring supported models are correctly exported.
class_docstr_tok: ["Integration","tests","ensuring","supported","models","are","correctly","exported","."]
code: def test_exporters_cli_tflite_int8_quantization_with_custom_dataset(
      self,
      test_name: str,
      model_name: str,
      task: str,
      tflite_config_constructor: "ExportConfigConstructor",
  ):
      # TODO: currently only 4 tasks are supported.
      if task not in TASK_TO_NON_DEFAULT_DATASET:
          return
  
      custom_dataset = TASK_TO_NON_DEFAULT_DATASET[task]["dataset_args"]
      config_name = None
      if isinstance(custom_dataset, dict):
          config_name = custom_dataset.get("name", None)
          custom_dataset = custom_dataset["path"]
  
      data_keys = TASK_TO_NON_DEFAULT_DATASET[task]["dataset_data_keys"]
      kwargs = {
          f"{key_name}_key": value
          for key_name, value in data_keys.items()
      }
  
      self._tflite_export(
          model_name,
          tflite_config_constructor,
          task=task,
          quantization="int8",
          calibration_dataset_name_or_path=custom_dataset,
          calibration_dataset_config_name=config_name,
          num_calibration_samples=3,
          **kwargs,
      )
  
imports: import unittest
  from tempfile import TemporaryDirectory
  from typing import TYPE_CHECKING, Dict, Optional
  import pytest
  from parameterized import parameterized
  from transformers import AutoConfig, is_tf_available
  from transformers.testing_utils import require_tf
  from optimum.utils import DEFAULT_DUMMY_SHAPES
  from ...utils.test_task_processors import TASK_TO_NON_DEFAULT_DATASET
  from ..exporters_utils import PYTORCH_EXPORT_MODELS_TINY
  import subprocess
label_desc: Use image node_id 9 for calling the TFLiteCLIExportTestCase obj's underlying member method code with example usage: obj.test_exporters_cli_tflite_int8_quantization_with_custom_dataset(test_name, model_name, task, tflite_config_constructor) without return types