code: def prepare_config_and_inputs(self):
      input_features = floats_tensor(
          [
              self.batch_size,
              self.seq_length,
              self.input_feat_per_channel,
          ],
          self.vocab_size,
      )
      attention_mask = torch.ones(
          [self.batch_size, self.seq_length],
          dtype=torch.long,
          device=torch_device,
      )
  
      config = self.get_config()
  
      return config, input_features, attention_mask
  
imports: import inspect
  import math
  import unittest
  from datasets import load_dataset
  from transformers import MCTCTConfig, is_torch_available
  from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
  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 MCTCTModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_features,  attention_mask