code: def data_gen():
      # Generated from following code snippet
      #
      # from transformers import AutoFeatureExtractor, WhisperModel
      # from datasets import load_dataset
  
      # model = WhisperModel.from_pretrained("openai/whisper-base")
      # feature_extractor = AutoFeatureExtractor.from_pretrained("openai/whisper-base")
      # ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
      # inputs = feature_extractor(ds[0]["audio"]["array"], return_tensors="pt")
      # input_features = inputs.input_features
      # decoder_input_ids = torch.tensor([[1, 1]]) * model.config.decoder_start_token_id
  
      input_features = torch.rand(1, 80, 3000)
      decoder_input_ids = torch.tensor([[1, 1]]) * 50258
      return dict(
          input_features=input_features,
          decoder_input_ids=decoder_input_ids,
      )
  
imports: import torch
  import transformers
  from ..registry import ModelAttribute, model_zoo
label_desc: Use image node_id 1 for calling a global function with example usage: data_gen() and returns: dict