from keras.wrappers.scikit_learn import KerasClassifier
task = openml.tasks.get_task(3573)  # mnist
model = KerasClassifier(build_fn=your_model_build_function, epochs=8, batch_size=32, verbose=1)
openml.runs.run_model_on_task(model, task)

ValueError                                Traceback (most recent call last)
<ipython-input-6-c3c90f60e704> in <module>()
      2 mnist_task=openml.tasks.get_task(3573)
      3 # Run the Keras model on the task (requires an API key).
----> 4 mnist_lenet_run =openml.runs.run_model_on_task(mnist_task, lenet_model, dataset_format ="array")
      5 # Publish the experiment on OpenML (optional, requires an API key).
      6 #myrun = mnist_lenet_run.publish()

1 frames
/usr/local/lib/python3.7/dist-packages/openml/extensions/functions.py in get_extension_by_model(model, raise_if_no_extension)
     90     if len(candidates) == 0:
     91         if raise_if_no_extension:
---> 92             raise ValueError("No extension registered which can handle model: {}".format(model))
     93         else:
     94             return None

ValueError: No extension registered which can handle model: <tensorflow.python.keras.wrappers.scikit_learn.KerasClassifier object at 0x7f5bfdf6e2d0>