fd633602af08b199d87d222a8cfb85acea17b55a,optuna/visualization.py,,_get_intermediate_plot,#Any#,52

Before Change

        return go.Figure(data=[], layout=layout)

    target_state = [TrialState.PRUNED, TrialState.COMPLETE, TrialState.RUNNING]
    dst_df = df[df["state"].isin(target_state)]
    dst_df = dst_df[dst_df["intermediate_values"].isnull().all(axis=1) == False]
    traces = []
    for __, row in dst_df.iterrows():
        trace = go.Scatter(

After Change

    trials = study.trials

    if len(trials) == 0:
        logger.warning("Study instance does not contain trials.")
        return go.Figure(data=[], layout=layout)
    if hasattr(trials[0], "intermediate_values") is False:
        logger.warning(
            "You need to set up the pruning feature to utilize plot_intermediate_values()")
        return go.Figure(data=[], layout=layout)

Instances