paper_note/lynx/memory_cost_hybrid.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 37,
   "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": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2100x840 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 14 / 5), ncols=1, nrows=1, constrained_layout=True, dpi=300\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name = [\n",
    "    \"ModelA\\n\" + r\"2DP$\\times $4TP\",\n",
    "    \"ModelA\\n\" + r\"2DP$\\times $8TP\",\n",
    "    \"ModelB\\n\" + r\"2DP$\\times $4TP\",\n",
    "    \"ModelB\\n\" + r\"2DP$\\times $8TP\",\n",
    "    \"ModelC\\n\" + r\"2DP$\\times $4TP\",\n",
    "    \"ModelC\\n\" + r\"2DP$\\times $8TP\",\n",
    "    \"ModelD\\n\" + r\"2DP$\\times $4TP\",\n",
    "    \"ModelD\\n\" + r\"2DP$\\times $8TP\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# memory cost\n",
    "data_a = {\n",
    "    labels_name[0]: [53, 53, 65],  # 22.64\n",
    "    labels_name[1]: [53, 53, 65],  # 22.64\n",
    "    labels_name[2]: [35, 35, 48],  # 37\n",
    "    labels_name[3]: [35, 35, 48],  # 37\n",
    "    labels_name[4]: [53, 53, 65],  # 22.64\n",
    "    labels_name[5]: [53, 53, 65],  # 22.64\n",
    "    labels_name[6]: [53, 53, 65],  # 22.64\n",
    "    labels_name[7]: [53, 53, 65],  # 22.64\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_width = 0.2\n",
    "group_spaing = 0.15\n",
    "\n",
    "group_positions = {}\n",
    "current_pos = 0\n",
    "\n",
    "for x_label, y_data in data_a.items():\n",
    "    group_positions[x_label] = []\n",
    "    for i in range(len(y_data)):\n",
    "        group_positions[x_label].append(current_pos)\n",
    "        current_pos += bar_width\n",
    "    current_pos += group_spaing\n",
    "\n",
    "group_centers = {}\n",
    "for x_label, positions in group_positions.items():\n",
    "    group_centers[x_label] = sum(positions) / len(positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '(b)')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_set = set()\n",
    "\n",
    "for x_label, y_data in data_a.items():\n",
    "    positions = group_positions[x_label]\n",
    "    for i, (pos, value, color, edgecolor, label, hatch) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            legend_labels,\n",
    "            hatches,\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",
    "\n",
    "        ax.bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            edgecolor=edgecolor,\n",
    "            hatch=hatch,\n",
    "            label=local_label,\n",
    "        )\n",
    "\n",
    "\n",
    "ax.set_xticks(list(group_centers.values()))\n",
    "ax.set_xticklabels(list(data_a.keys()))\n",
    "\n",
    "ax.set_ylim(0, 85)\n",
    "ax.set_yticks([0, 40, 80])\n",
    "ax.set_yticklabels([\"0\", \"40\", \"80\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax.tick_params(axis=\"x\", bottom=False, labelsize=11, pad=1)\n",
    "ax.tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax.set_ylabel(\"Peak Memory (GB)\", fontsize=g_label_fontsize)\n",
    "ax.set_title(\"(b)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fee47514ad0>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.legend(\n",
    "    ncol=3,\n",
    "    loc=\"upper center\",\n",
    "    frameon=False,\n",
    "    shadow=False,\n",
    "    fontsize=g_label_fontsize,\n",
    "    bbox_to_anchor=(0.5, 1)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2100x840 with 1 Axes>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.savefig(\"memory_cost_hybrid.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",
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