(study: Study)
return _get_intermediate_plot(study)
Plot intermediate values of all trials in a study.

    Example:

        The following code snippet shows how to plot intermediate values.

        .. plotly::

            import optuna


            def f(x):
                return (x - 2) ** 2


            def df(x):
                return 2 * x - 4


            def objective(trial):
                lr = trial.suggest_float("lr", 1e-5, 1e-1, log=True)

                x = 3
                for step in range(128):
                    y = f(x)

                    trial.report(y, step=step)
                    if trial.should_prune():
                        raise optuna.TrialPruned()

                    gy = df(x)
                    x -= gy * lr

                return y


            sampler = optuna.samplers.TPESampler(seed=10)
            study = optuna.create_study(sampler=sampler)
            study.optimize(objective, n_trials=16)

            fig = optuna.visualization.plot_intermediate_values(study)
            fig.show()

    Args:
        study:
            A :class:`~optuna.study.Study` object whose trials are plotted for their intermediate
            values.

    Returns:
        A :class:`plotly.graph_objs.Figure` object.
Plot intermediate values of all trials in a study.
Plot intermediate values of all trials in a study .
def plot_intermediate_values(study: Study) -> "go.Figure":
    """Plot intermediate values of all trials in a study.

    Example:

        The following code snippet shows how to plot intermediate values.

        .. plotly::

            import optuna


            def f(x):
                return (x - 2) ** 2


            def df(x):
                return 2 * x - 4


            def objective(trial):
                lr = trial.suggest_float("lr", 1e-5, 1e-1, log=True)

                x = 3
                for step in range(128):
                    y = f(x)

                    trial.report(y, step=step)
                    if trial.should_prune():
                        raise optuna.TrialPruned()

                    gy = df(x)
                    x -= gy * lr

                return y


            sampler = optuna.samplers.TPESampler(seed=10)
            study = optuna.create_study(sampler=sampler)
            study.optimize(objective, n_trials=16)

            fig = optuna.visualization.plot_intermediate_values(study)
            fig.show()

    Args:
        study:
            A :class:`~optuna.study.Study` object whose trials are plotted for their intermediate
            values.

    Returns:
        A :class:`plotly.graph_objs.Figure` object.
    """

    _imports.check()
    return _get_intermediate_plot(study)
def plot_intermediate_values ( study : Study ) -> "go.Figure" : _imports . check ( ) return _get_intermediate_plot ( study )