class_docstr: You can also import this e.g from .test_modeling_tapas import TapasModelTester
code: def prepare_config_and_inputs_for_common(self):
      config_and_inputs = self.prepare_config_and_inputs()
      (
          config,
          input_ids,
          input_mask,
          token_type_ids,
          sequence_labels,
          token_labels,
          labels,
          numeric_values,
          numeric_values_scale,
          float_answer,
          aggregation_labels,
      ) = config_and_inputs
      inputs_dict = {
          "input_ids": input_ids,
          "token_type_ids": token_type_ids,
          "attention_mask": input_mask,
      }
      return config, inputs_dict
  
imports: import copy
  import unittest
  import numpy
  import pandas
  from transformers import MODEL_FOR_CAUSAL_LM_MAPPING, MODEL_FOR_MASKED_LM_MAPPING, MODEL_FOR_MULTIPLE_CHOICE_MAPPING, MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, TapasConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_tensorflow_probability, require_torch, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 8 for calling the TapasModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs_for_common() and returns: config,  inputs_dict