code: def hls_model(mnist_model, backend, io_type, strategy):
      keras_model = mnist_model
      hls_config = hls4ml.utils.config_from_keras_model(
          keras_model, granularity="name"
      )
      hls_config["Model"]["Strategy"] = strategy
      hls_config["LayerName"]["softmax"]["Strategy"] = "Stable"
      output_dir = str(
          test_root_path
          / f"hls4mlprj_cnn_mnist_qkeras_{backend}_{io_type}_{strategy}"
      )
  
      hls_model = hls4ml.converters.convert_from_keras_model(
          keras_model,
          hls_config=hls_config,
          output_dir=output_dir,
          backend=backend,
          io_type=io_type,
      )
  
      hls_model.compile()
      return hls_model
  
file_path: hls4ml/test/pytest/test_cnn_mnist_qkeras.py
imports: from pathlib import Path
  import numpy
  import pytest
  import tensorflow
  from qkeras.utils import _add_supported_quantized_objects
  from sklearn.metrics import accuracy_score
  from tensorflow.keras.models import model_from_json
  import hls4ml
label_desc: Use image node_id 3 for calling a global function with example usage: hls_model(mnist_model, backend, io_type, strategy) and returns: hls_model