code: def mnist_model():
      model_path = example_model_path / "keras/qkeras_mnist_cnn.json"
      with model_path.open("r") as f:
          jsons = f.read()
      model = model_from_json(jsons, custom_objects=co)
      model.load_weights(
          example_model_path / "keras/qkeras_mnist_cnn_weights.h5"
      )
      return 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 2 for calling a global function with example usage: mnist_model() and returns: model