code: def get_pretrained_model_and_inputs(self):
      model = SpeechEncoderDecoderModel.from_encoder_decoder_pretrained(
          "facebook/s2t-small-librispeech-asr", "bert-base-cased"
      )
      batch_size = 13
      input_features = floats_tensor([batch_size, 7, 80], scale=1.0)
      attention_mask = random_attention_mask([batch_size, 7])
      decoder_input_ids = ids_tensor(
          [batch_size, 4], model.decoder.config.vocab_size
      )
      decoder_attention_mask = random_attention_mask([batch_size, 4])
      inputs = {
          "input_features": input_features,
          "attention_mask": attention_mask,
          "decoder_input_ids": decoder_input_ids,
          "decoder_attention_mask": decoder_attention_mask,
      }
  
      return model, inputs
  
imports: import tempfile
  import unittest
  from transformers import is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
  from ..bert.test_modeling_bert import BertModelTester
  from ..speech_to_text.test_modeling_speech_to_text import Speech2TextModelTester
  from ..speech_to_text_2.test_modeling_speech_to_text_2 import Speech2Text2StandaloneDecoderModelTester
  from ..wav2vec2.test_modeling_wav2vec2 import Wav2Vec2ModelTester
label_desc: Use image node_id 1 for calling the Speech2TextBertModelTest obj's underlying member method code with example usage: obj.get_pretrained_model_and_inputs() and returns: model,  inputs