paper_note/lynx/end_to_end_mfu.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"font.size\"] = 16\n",
    "\n",
    "g_label_fontsize = 16\n",
    "\n",
    "colors = [\n",
    "    \"#5D7599\",\n",
    "    \"#233142\",\n",
    "    \"#F95959\",\n",
    "]\n",
    "\n",
    "edgecolors = [\n",
    "    \"#FFFFFF\",\n",
    "    \"#FFFFFF\",\n",
    "    \"#FFFFFF\",\n",
    "]\n",
    "\n",
    "hatches = [\"\\\\\\\\\", \"\", \"\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 4200x1050 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(14, 14 / 4), ncols=1, nrows=1, constrained_layout=True, dpi=300\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"ModelA\\n8DP\",\n",
    "    \"ModelA\\n8TP\",\n",
    "    \"ModelB\\n8TP\",  \n",
    "    \"ModelA\\n2DP$\\\\times$4TP\",\n",
    "    \"ModelA\\n2DP$\\\\times$8TP\",\n",
    "    \"ModelA\\n4DP$\\\\times$2TP\",\n",
    "    \"ModelB\\n4DP$\\\\times$2TP\",\n",
    "]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MFU\n",
    "data_a = {\n",
    "    labels_name_a[0]: [41.0, 34.2, 44.4],  # modela 8DP\n",
    "    labels_name_a[1]: [26.2, 36.8, 43.6],  # modela 8TP\n",
    "    labels_name_a[2]: [30.1, 39.6, 49.4],  # modelb 8TP\n",
    "    labels_name_a[3]: [37.1, 30.4, 44.6],  # modela 2DP 4TP\n",
    "    labels_name_a[4]: [39.6, 37.3, 42.6],  # modela 2DP 8TP\n",
    "    labels_name_a[5]: [40.4, 30.5, 44.7],  # modela 4DP 2TP\n",
    "    labels_name_a[6]: [-1, 31.7, 38.0],  # modelb 4DP 2TP\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_width = 0.2\n",
    "group_spaing = 0.15\n",
    "\n",
    "group_positions = {}\n",
    "current_pos = 0\n",
    "\n",
    "x_label_cnt = len(data_a.keys())\n",
    "x_label_group_cnt = 3\n",
    "\n",
    "for idx in range(x_label_cnt):\n",
    "    group_positions[idx] = []\n",
    "    for _ in range(x_label_group_cnt):\n",
    "        group_positions[idx].append(current_pos)\n",
    "        current_pos += bar_width\n",
    "    current_pos += group_spaing\n",
    "\n",
    "group_centers = {}\n",
    "for idx, positions in group_positions.items():\n",
    "    group_centers[idx] = sum(positions) / len(positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(13.333333333333346, 0.5, 'MFU (%)')"
      ]
     },
     "execution_count": 355,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_set = set()\n",
    "for idx, (x_label, y_data) in enumerate(data_a.items()):\n",
    "    positions = group_positions[idx]\n",
    "    tmp = sorted(y_data)[-2]\n",
    "    ax.text(\n",
    "        positions[2],\n",
    "        y_data[2] + 2,\n",
    "        f\"$\\\\times${str(round(y_data[2]/tmp, 2))}\",\n",
    "        ha=\"center\",\n",
    "        fontweight=\"bold\",\n",
    "        color=colors[2],\n",
    "    )\n",
    "    for i, (pos, value, color, edgecolor, hatch, label) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            hatches,\n",
    "            legend_labels,\n",
    "        )\n",
    "    ):\n",
    "        if label in label_set:\n",
    "            local_label = None\n",
    "        else:\n",
    "            local_label = label\n",
    "            label_set.add(local_label)\n",
    "        if value == -1:\n",
    "            ax.text(\n",
    "                pos,\n",
    "                1,\n",
    "                \"$\\\\times$OOM\",\n",
    "                rotation=90,\n",
    "                ha=\"center\",\n",
    "                va=\"bottom\",\n",
    "                color=\"red\",\n",
    "            )\n",
    "        ax.bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            label=local_label,\n",
    "            hatch=hatch,\n",
    "            edgecolor=edgecolor,\n",
    "        )\n",
    "\n",
    "ax.set_xticks(list(group_centers.values()))\n",
    "ax.set_xticklabels(list(data_a.keys()))\n",
    "\n",
    "ax.set_ylim(0, 100)\n",
    "ax.set_yticks([0, 50, 100])\n",
    "ax.set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax.tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax.tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax.set_ylabel(\"MFU (%)\", fontsize=g_label_fontsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa86c90a6f0>"
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.legend(\n",
    "    ncol=3,\n",
    "    loc=\"upper center\",\n",
    "    frameon=False,\n",
    "    shadow=False,\n",
    "    bbox_to_anchor=(0.5, 1.1),\n",
    "    fontsize=g_label_fontsize,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 4200x1050 with 1 Axes>"
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.savefig(\"end_to_end_mfu.pdf\", bbox_inches=\"tight\", dpi=1000)\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}