code: def test_multi_clone(model, data, backend: str):
      output_dir = str(
          test_root_path / f"hls4mlprj_stream_multi_clone_{backend}"
      )
      hls_config = {
          "Model": {"Precision": "fixed<32,5>", "ReuseFactor": 1}
      }
      model_hls = convert_from_keras_model(
          model,
          backend=backend,
          output_dir=output_dir,
          hls_config=hls_config,
          io_type="io_stream",  # clone only happens with stream io.
      )
      model_hls.compile()
      r_hls = model_hls.predict(data)
      r_keras = model(data).numpy()
  
      assert np.allclose(r_hls, r_keras, atol=1e-5, rtol=0)
  
file_path: hls4ml/test/pytest/test_stream_multi_clone.py
imports: from pathlib import Path
  import numpy
  import pytest
  from keras.layers import Add, Dense
  from tensorflow import keras
  from hls4ml.converters import convert_from_keras_model
label_desc: Use image node_id 3 for calling a global function with example usage: test_multi_clone(model, data, backend) without return types