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,
      )
      decoder_input_ids = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      ).clamp(2)
  
      config = self.get_config()
      inputs_dict = prepare_speech_to_text_inputs_dict(
          config,
          input_features=input_features,
          decoder_input_ids=decoder_input_ids,
          attention_mask=attention_mask,
      )
      return config, inputs_dict
  
imports: import copy
  import inspect
  import os
  import tempfile
  import unittest
  from transformers import Speech2TextConfig
  from transformers.testing_utils import is_torch_available, require_sentencepiece, require_tokenizers, require_torch, require_torch_fp16, require_torchaudio, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 2 for calling the Speech2TextModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  inputs_dict