Error when I use Docker, the same requirements as PC.
Out off Docker all is right, but there is problem with optuna’s st.plotly_chart:
Model is LGBM, Binary Classifier, some of features are binarized.
File “/usr/local/lib/python3.8/site-packages/streamlit/scriptrunner/script_runner.py”, line 554, in _run_script
exec(code, module.dict)
File “/app/frontend/main.py”, line 231, in
main()
File “/app/frontend/main.py”, line 227, in main
page_names_to_funcsselected_page
File “/app/frontend/main.py”, line 174, in training
start_training(config=config, endpoint=endpoint)
File “/app/frontend/src/train/training.py”, line 64, in start_training
fig_imp = plot_param_importances(study)
File “/usr/local/lib/python3.8/site-packages/optuna/visualization/_param_importances.py”, line 112, in plot_param_importances
importances = optuna.importance.get_param_importances(
File “/usr/local/lib/python3.8/site-packages/optuna/importance/init.py”, line 93, in get_param_importances
return evaluator.evaluate(study, params=params, target=target)
File “/usr/local/lib/python3.8/site-packages/optuna/importance/_fanova/_evaluator.py”, line 122, in evaluate
evaluator.fit(
File “/usr/local/lib/python3.8/site-packages/optuna/importance/_fanova/_fanova.py”, line 74, in fit
self._trees = [FanovaTree(e.tree, search_spaces) for e in self.forest.estimators]
File “/usr/local/lib/python3.8/site-packages/optuna/importance/_fanova/_fanova.py”, line 74, in
self._trees = [FanovaTree(e.tree, search_spaces) for e in self.forest.estimators]
File “/usr/local/lib/python3.8/site-packages/optuna/importance/_fanova/_tree.py”, line 23, in init
statistics = self._precompute_statistics()
File “/usr/local/lib/python3.8/site-packages/optuna/importance/_fanova/_tree.py”, line 182, in _precompute_statistics
value = numpy.average(child_values, weights=child_weights)
File “<array_function internals>”, line 5, in average
File “/usr/local/lib/python3.8/site-packages/numpy/lib/function_base.py”, line 409, in average
raise ZeroDivisionError(