code: def get_pretrained_model_and_inputs(self):
      model = (
          FlaxSpeechEncoderDecoderModel.from_encoder_decoder_pretrained(
              "facebook/wav2vec2-large-lv60", "bert-large-uncased"
          )
      )
      batch_size = 13
      input_values = floats_tensor(
          [batch_size, 512], model.config.encoder.vocab_size
      )
      attention_mask = random_attention_mask([batch_size, 512])
      decoder_input_ids = ids_tensor(
          [batch_size, 4], model.config.decoder.vocab_size
      )
      decoder_attention_mask = random_attention_mask([batch_size, 4])
      inputs = {
          "inputs": input_values,
          "attention_mask": attention_mask,
          "decoder_input_ids": decoder_input_ids,
          "decoder_attention_mask": decoder_attention_mask,
      }
  
      return model, inputs
  
imports: import tempfile
  import unittest
  import numpy
  from transformers import is_flax_available, is_torch_available
  from transformers.testing_utils import is_pt_flax_cross_test, require_flax, slow, torch_device
  from ...test_modeling_flax_common import floats_tensor, ids_tensor, random_attention_mask
  from ..bart.test_modeling_flax_bart import FlaxBartStandaloneDecoderModelTester
  from ..bert.test_modeling_flax_bert import FlaxBertModelTester
  from ..gpt2.test_modeling_flax_gpt2 import FlaxGPT2ModelTester
  from ..wav2vec2.test_modeling_flax_wav2vec2 import FlaxWav2Vec2ModelTester
label_desc: Use image node_id 1 for calling the FlaxWav2Vec2BertModelTest obj's underlying member method code with example usage: obj.get_pretrained_model_and_inputs() and returns: model,  inputs