code: def prepare_config_and_inputs(self):
      input_features = floats_tensor(
          [self.batch_size, self.num_mel_bins, self.seq_length],
          self.vocab_size,
      )
  
      decoder_input_ids = torch.tensor(
          self.batch_size * [[self.decoder_start_token_id]],
          device=torch_device,
      )
  
      config = self.get_config()
      inputs_dict = prepare_whisper_inputs_dict(
          config,
          attention_mask=None,
          input_features=input_features,
          decoder_input_ids=decoder_input_ids,
      )
      return config, inputs_dict
  
imports: import copy
  import inspect
  import os
  import tempfile
  import unittest
  from transformers import WhisperConfig
  from transformers.testing_utils import is_torch_available, require_torch, require_torchaudio, slow, torch_device
  from transformers.utils import cached_property
  from transformers.utils.import_utils import is_datasets_available
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
label_desc: Use image node_id 2 for calling the WhisperModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  inputs_dict