def plot_hpvm_configs(config_path: PathLike, save_to: PathLike=None, show_qos_loss: bool=True, **fig_kwargs) -> plt.Figure:
    "\n    Plot the QoS-speedup information in an HPVM configuration file.\n    It is recommended to profile the config file first (using `profile_configs`)\n    to obtain real speedup numbers.\n    This function creates a `matplotlib.pyplot.Figure`, plots on it, and returns it.\n\n    :param config_path: Path to the config file (HPVM configuration format).\n    :param save_to: File to save figure into. Default is None: don't save figure (just return it).\n    :param show_qos_loss: Show the loss of QoS on x axis of the figure. Defaults to True.\n        If False, will use (absolute) QoS instead of QoS loss.\n    :param fig_kwargs: Arguments to pass to `plt.subplots`.\n    "
    import numpy as np
    (_, configs) = read_hpvm_configs(config_path)
    get_qos = (lambda c: (c.qos_loss if show_qos_loss else c.qos))
    qos_speedup = np.array([(get_qos(c), c.speedup) for c in configs])
    (qoses, speedups) = qos_speedup.T
    (fig, ax) = plt.subplots(**fig_kwargs)
    ax.scatter(qoses, speedups)
    ax.set_xlabel('QoS Loss')
    ax.set_ylabel('Speedup (X)')
    if save_to:
        fig.savefig(save_to, dpi=300)
    return fig
Plot the QoS-speedup information in an HPVM configuration file.
It is recommended to profile the config file first (using `profile_configs`)
to obtain real speedup numbers.
This function creates a `matplotlib.pyplot.Figure`, plots on it, and returns it.

:param config_path: Path to the config file (HPVM configuration format).
:param save_to: File to save figure into. Default is None: don't save figure (just return it).
:param show_qos_loss: Show the loss of QoS on x axis of the figure. Defaults to True.
    If False, will use (absolute) QoS instead of QoS loss.
:param fig_kwargs: Arguments to pass to `plt.subplots`.
def plot_hpvm_configs(config_path: PathLike, save_to: PathLike=None, show_qos_loss: bool=True, **fig_kwargs) -> plt.Figure:
    "\n    Plot the QoS-speedup information in an HPVM configuration file.\n    It is recommended to profile the config file first (using `profile_configs`)\n    to obtain real speedup numbers.\n    This function creates a `matplotlib.pyplot.Figure`, plots on it, and returns it.\n\n    :param config_path: Path to the config file (HPVM configuration format).\n    :param save_to: File to save figure into. Default is None: don't save figure (just return it).\n    :param show_qos_loss: Show the loss of QoS on x axis of the figure. Defaults to True.\n        If False, will use (absolute) QoS instead of QoS loss.\n    :param fig_kwargs: Arguments to pass to `plt.subplots`.\n    "
    import numpy as np
    (_, configs) = read_hpvm_configs(config_path)
    get_qos = (lambda c: (c.qos_loss if show_qos_loss else c.qos))
    qos_speedup = np.array([(get_qos(c), c.speedup) for c in configs])
    (qoses, speedups) = qos_speedup.T
    (fig, ax) = plt.subplots(**fig_kwargs)
    ax.scatter(qoses, speedups)
    ax.set_xlabel('QoS Loss')
    ax.set_ylabel('Speedup (X)')
    if save_to:
        fig.savefig(save_to, dpi=300)
    return fig