code: def prepare_config_and_inputs(self):
      input_ids = ids_tensor(
          [self.batch_size, self.input_id_length], self.vocab_size
      )
      attention_mask = random_attention_mask(
          [self.batch_size, self.input_id_length]
      )
      pixel_values = floats_tensor(
          [
              self.batch_size,
              self.num_frames,
              self.num_channels,
              self.max_img_size,
              self.max_img_size,
          ]
      )
  
      config = self.get_config()
  
      return (config, input_ids, pixel_values, attention_mask)
  
imports: import unittest
  from transformers import ResNetConfig, TvpConfig
  from transformers.testing_utils import require_torch, require_vision, torch_device
  from transformers.utils import cached_property, is_torch_available, is_vision_available
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 2 for calling the TVPModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  pixel_values,  attention_mask