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

Before Change

        showlegend=False
    )

    try:
        df = study.trials_dataframe()
        df = df.rename(columns={"number": "trial_id"})
    except Exception:  // empty study
        return go.Figure(data=[], layout=layout)

    if "intermediate_values" not in df:
        return go.Figure(data=[], layout=layout)

    target_state = [TrialState.PRUNED, TrialState.COMPLETE, TrialState.RUNNING]

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)

    target_state = [TrialState.PRUNED, TrialState.COMPLETE, TrialState.RUNNING]
    trials = [trial for trial in trials if trial.state in target_state]
    traces = []
    for trial in trials:
        trace = go.Scatter(
            x=tuple(trial.intermediate_values.keys()),
            y=tuple(trial.intermediate_values.values()),
            mode="lines+markers",
            marker={

Instances