code: def _prepare_for_class(
      self, inputs_dict, model_class, return_labels=True
  ):
      inputs_dict = copy.deepcopy(inputs_dict)
  
      if return_labels:
          if model_class.__name__ == "TvltForAudioVisualClassification":
              inputs_dict["labels"] = torch.zeros(
                  (self.model_tester.batch_size,),
                  dtype=torch.long,
                  device=torch_device,
              )
          elif model_class.__name__ == "TvltForPreTraining":
              inputs_dict["labels"] = torch.zeros(
                  (self.model_tester.batch_size,),
                  dtype=torch.float,
                  device=torch_device,
              )
              inputs_dict["pixel_values_mixed"] = torch.zeros(
                  (
                      self.model_tester.batch_size,
                      self.model_tester.num_frames,
                      self.model_tester.num_image_channels,
                      self.model_tester.image_size,
                      self.model_tester.image_size,
                  ),
                  dtype=torch.float,
                  device=torch_device,
              )
              inputs_dict["pixel_mask_mixed"] = torch.zeros(
                  (
                      self.model_tester.batch_size,
                      self.model_tester.expected_pixel_seq_len,
                  ),
                  dtype=torch.float,
                  device=torch_device,
              )
  
      return inputs_dict
  
imports: import copy
  import inspect
  import unittest
  import numpy
  from huggingface_hub import hf_hub_download
  from transformers import TvltConfig, is_datasets_available, is_speech_available, is_torch_available, is_vision_available
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the TvltModelTest obj's underlying member method code with example usage: obj._prepare_for_class(inputs_dict, model_class, return_labels) and returns: inputs_dict