Function plot_tpots

benchmarking/vllm/plot_tpot.py:177–215

(
    df: pd.DataFrame, results_dir: Path, imgs_dir: Path, fmms_name: str, fmt: str = "png"
)

    concurrencies = sorted(all_x)
    ax.set_xlabel("Batch Size")
    ax.set_ylabel(ylabel)
    ax.set_xscale("log")
    ax.set_xticks(concurrencies, labels=[int(x) for x in concurrencies], minor=False)
    ax.set_xticks([], minor=True)
    if hline is not None:
        ax.axhline(hline, color="black", linewidth=0.8, linestyle="--")
    ax.grid(alpha=0.5)


# ---------------------------------------------------------------------------
# Per-model TPOT plots (imgs/tpots/)
# ---------------------------------------------------------------------------


def plot_tpots(
    df: pd.DataFrame, results_dir: Path, imgs_dir: Path, fmms_name: str, fmt: str = "png"
):
    tpots_dir = imgs_dir / "tpots"
    tp = tp_from_dir(results_dir)

    for model in MODELS:
        mdf = df.query("model == @model")
        if mdf.empty:
            continue

        tpots_dir.mkdir(parents=True, exist_ok=True)
        fig, ax = plt.subplots(figsize=TPOT_FIGSIZE)
        series = []
        for variant in [BASELINE_NAME, FI2_NAME, fmms_name]:
            vdf = mdf.query("variant == @variant")
            if not vdf.empty:
                series.append((variant, vdf.rename(columns={"median_tpot_ms": "y"})))
        _plot_scatter_line(
            ax, series=series, x_col="max_concurrency", y_col="y", ylabel="Median TPOT (ms)"
        )
        ax.set_title(f"{model} TP{tp}")
        ax.legend(title="Method")
        ax.annotate(
            "lower is better",
            xy=(0.98, 0.02),
            xycoords="axes fraction",
            ha="right",