def get_inputs(self):
        """get inputs for both feature extractor and tokenizer"""
        ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
        speech_samples = ds.sort("id").select([0])["audio"]
        input_speech = [x["array"] for x in speech_samples][0]
        sampling_rate = [x["sampling_rate"] for x in speech_samples][0]

        feature_extractor_outputs = self.get_feature_extractor()(
            audio=input_speech, sampling_rate=sampling_rate, return_tensors="pt"
        )
        model = Pop2PianoForConditionalGeneration.from_pretrained("sweetcocoa/pop2piano")
        token_ids = model.generate(input_features=feature_extractor_outputs["input_features"], composer="composer1")
        dummy_notes = [
            [
                pretty_midi.Note(start=0.441179, end=2.159456, pitch=70, velocity=77),
                pretty_midi.Note(start=0.673379, end=0.905578, pitch=73, velocity=77),
                pretty_midi.Note(start=0.905578, end=2.159456, pitch=73, velocity=77),
                pretty_midi.Note(start=1.114558, end=2.159456, pitch=78, velocity=77),
                pretty_midi.Note(start=1.323537, end=1.532517, pitch=80, velocity=77),
            ],
            [
                pretty_midi.Note(start=0.441179, end=2.159456, pitch=70, velocity=77),
            ],
        ]

        return input_speech, sampling_rate, token_ids, dummy_notes
get inputs for both feature extractor and tokenizer
dpkd/transformers/tests/models/pop2piano/test_processor_pop2piano.py