onnxruntime/docs/python/notebooks/quantization_f8.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c6b4f765",
   "metadata": {},
   "source": [
    "# Quantization\n",
    "\n",
    "The notebooks compare quantization types."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9333e48c",
   "metadata": {},
   "source": [
    "## One matrix\n",
    "\n",
    "Taken from [MobileNet](https://github.com/onnx/models/tree/main/vision/classification/mobilenet)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e26ddb92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "download 'mobilenetv2-12.onnx'\n",
      "done\n",
      "model size 13964571 bytes\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import urllib\n",
    "\n",
    "url = \"https://github.com/onnx/models/raw/main/vision/classification/mobilenet/model/mobilenetv2-12.onnx\"\n",
    "destination = \"mobilenetv2-12.onnx\"\n",
    "\n",
    "if not os.path.exists(destination) or os.stat(destination).st_size < 10000:\n",
    "    print(f\"download {destination!r}\")\n",
    "    g = urllib.request.urlopen(url)\n",
    "    with open(destination, \"wb\") as f:\n",
    "        f.write(g.read())\n",
    "    print(\"done\")\n",
    "else:\n",
    "    print(f\"already downloaded {destination!r}\")\n",
    "print(f\"model size {os.stat(destination).st_size} bytes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f75c988a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model size: 13964571\n"
     ]
    }
   ],
   "source": [
    "from onnx import load\n",
    "\n",
    "with open(destination, \"rb\") as f:\n",
    "    onx = load(f)\n",
    "    print(f\"model size: {len(onx.SerializeToString())}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8581d42",
   "metadata": {},
   "source": [
    "Let's take one of the biggest matrix of coefficients:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "358217f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(614421, '616')\n",
      "(614421, '619')\n",
      "(1228821, '625')\n",
      "(1638421, '628')\n",
      "(5120034, 'classifier.1.weight')\n"
     ]
    }
   ],
   "source": [
    "initializers = []\n",
    "for init in onx.graph.initializer:\n",
    "    initializers.append((len(init.SerializeToString()), init.name, init))\n",
    "\n",
    "initializers.sort()\n",
    "\n",
    "for init in initializers[-5:]:\n",
    "    print(init[:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "3cd9fc33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((160, 960, 1, 1), dtype('float32'))"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from onnx.numpy_helper import to_array\n",
    "\n",
    "coef = to_array(initializers[-5][-1])\n",
    "coef.shape, coef.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b044ce26",
   "metadata": {},
   "source": [
    "## Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "374652c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "cf = coef.ravel()\n",
    "cf01 = cf[(cf >= 0) & (cf <= 0.001)]\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 4))\n",
    "axs[0].hist(cf, bins=2048)\n",
    "axs[0].set_title(\n",
    "    f\"Coefficients Distribution\\nwith {cf.size} éléments\"\n",
    ")\n",
    "axs[1].hist(cf01, bins=2048)\n",
    "axs[1].set_title(f\"Same distribution between 0 et {cf01.max():.4f}\\n{cf01.size} éléments\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "083b75c0",
   "metadata": {},
   "source": [
    "Distribution of float 8."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "544a61de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "254"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy\n",
    "from onnx.numpy_helper import float8e4m3_to_float32\n",
    "\n",
    "float8 = [float8e4m3_to_float32(i) for i in range(0, 256)]\n",
    "no_nan8 = [f for f in float8 if not numpy.isnan(f)]\n",
    "len(no_nan8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "217b5762",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = 3\n",
    "gauss = numpy.random.normal(size=len(no_nan8) * 20)\n",
    "scale1 = numpy.std(no_nan8) / numpy.std(gauss)\n",
    "scalep = numpy.std(no_nan8) / numpy.std(gauss**p)\n",
    "\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(10, 4))\n",
    "axs[0].hist(float8, bins=50, alpha=0.5, label=\"f8\", density=True)\n",
    "axs[0].hist(gauss * scale1, bins=50, alpha=0.5, label=\"N\", density=True)\n",
    "axs[0].hist(gauss**p * scalep, bins=50, alpha=0.5, label=f\"N^{p}\", density=True)\n",
    "axs[0].set_xlim([-200, 200])\n",
    "axs[0].set_title(\"Distribution of float 8 E4M3FN\")\n",
    "axs[0].legend()\n",
    "\n",
    "axs[1].hist(float8, bins=2000, alpha=0.5, label=\"f8\", density=True)\n",
    "axs[1].hist(gauss * scale1, bins=2000, alpha=0.5, label=\"N\", density=True)\n",
    "axs[1].hist(gauss**p * scalep, bins=2000, alpha=0.5, label=f\"N^{p}\", density=True)\n",
    "axs[1].set_xlim([-50, 50])\n",
    "axs[1].set_title(\"Same with more bins\")\n",
    "axs[1].legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbbf27bc",
   "metadata": {},
   "source": [
    "Curve `N^3` is gaussian at power 3. It was added to show that E4M3FN distribution is closer to $X^3$ than $X$ ($X$ is gaussian)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "a64efc70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.004002655570437662, -0.0)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scale_f8p, zero_f8p = estimation_quantization_scale(coef, method=\"power\")\n",
    "scale_f8p, zero_f8p"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c029522",
   "metadata": {},
   "source": [
    "## Scale estimation\n",
    "\n",
    "Very basic:\n",
    "\n",
    "* ratio of standard deviation for float 8\n",
    "* quantile at 5% for uint 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "61dc7741",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0009081294882681465, -0.0)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from onnx import TensorProto\n",
    "\n",
    "\n",
    "def estimation_quantization_scale(\n",
    "    coef: numpy.array, to: int = TensorProto.FLOAT8E4M3FN, method: str = \"naive\"\n",
    ") -> tuple[float, float]:\n",
    "    \"\"\"\n",
    "    Estimates the scale parameter for the quantization to float 8 assuming\n",
    "    the distribution of the coefficients is gaussian.\n",
    "    \"\"\"\n",
    "    if to == TensorProto.FLOAT8E4M3FN:\n",
    "        float8 = [float8e4m3_to_float32(i) for i in range(0, 256)]\n",
    "        quant_float = [f for f in float8 if not numpy.isnan(f)]\n",
    "        if method == \"naive\":\n",
    "            std_coef = numpy.std(coef.ravel())\n",
    "            std_quant = numpy.std(numpy.array(quant_float, dtype=numpy.float32))\n",
    "        elif method == \"power\":\n",
    "            cr = coef.ravel()\n",
    "            ca = numpy.abs(cr)\n",
    "            std_coef = numpy.std(ca ** (1.0 / 3.0) * cr / ca)\n",
    "            std_quant = numpy.std(numpy.array(quant_float, dtype=numpy.float32))\n",
    "        else:\n",
    "            raise ValueError(f\"Unexpected quantization method {method!r}.\")\n",
    "        zero = 0.0\n",
    "        scale = std_quant / std_coef\n",
    "    elif to == TensorProto.UINT8:\n",
    "        uint8 = [i for i in range(0, 256)]\n",
    "        qu = numpy.quantile(coef.ravel(), [1 - 0.99999, 0.99999])\n",
    "        scale = 255 / (qu[1] - qu[0])\n",
    "        zero = qu[0] * scale\n",
    "    else:\n",
    "        raise ValueError(f\"Unexpected quantization type for to={to}.\")\n",
    "\n",
    "    return 1.0 / scale, -zero\n",
    "\n",
    "\n",
    "scale_f8, zero_f8 = estimation_quantization_scale(coef)\n",
    "scale_f8, zero_f8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "2bfef061",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.004002655570437662, -0.0)"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scale_f8p, zero_f8p = estimation_quantization_scale(coef, method=\"power\")\n",
    "scale_f8p, zero_f8p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "e86fa67a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.003963413028773201, 131.88381712385316)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scale_u8, zero_u8 = estimation_quantization_scale(coef, to=TensorProto.UINT8)\n",
    "scale_u8, zero_u8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13ce5145",
   "metadata": {},
   "source": [
    "## QDQ\n",
    "\n",
    "Let's compare the square loss with two operators [QuantizeLinear](https://onnx.ai/onnx/operators/onnx__QuantizeLinear.html) + [DequantizeLinear](https://onnx.ai/onnx/operators/onnx__DequantizeLinear.html) ~ Identity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "04cd02c0",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.05448777,  0.06538533, -0.00590284, ...,  0.01997885,\n",
       "        0.00590284,  0.21795107], dtype=float32)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from onnx.helper import (\n",
    "    make_node,\n",
    "    make_graph,\n",
    "    make_model,\n",
    "    make_tensor_value_info,\n",
    "    make_operatorsetid,\n",
    "    make_tensor,\n",
    ")\n",
    "from onnx.reference import ReferenceEvaluator\n",
    "\n",
    "X = make_tensor_value_info(\"X\", TensorProto.FLOAT, [None])\n",
    "Scale = make_tensor_value_info(\"Scale\", TensorProto.FLOAT, [1])\n",
    "Y = make_tensor_value_info(\"Y\", TensorProto.FLOAT, [None])\n",
    "\n",
    "model_f8 = make_model(\n",
    "    make_graph(\n",
    "        [\n",
    "            make_node(\n",
    "                \"Constant\",\n",
    "                [],\n",
    "                [\"Zero\"],\n",
    "                value=make_tensor(\"Zero\", TensorProto.FLOAT8E4M3FN, [1], [0.0]),\n",
    "            ),\n",
    "            make_node(\"QuantizeLinear\", [\"X\", \"Scale\", \"Zero\"], [\"Q\"], axis=0),\n",
    "            make_node(\"DequantizeLinear\", [\"Q\", \"Scale\"], [\"Y\"], axis=0),\n",
    "        ],\n",
    "        \"quf8\",\n",
    "        [X, Scale],\n",
    "        [Y],\n",
    "    ),\n",
    "    opset_imports=[make_operatorsetid(\"\", 19)],\n",
    ")\n",
    "\n",
    "ref_f8 = ReferenceEvaluator(model_f8)\n",
    "qu_f8 = ref_f8.run(\n",
    "    None, {\"X\": coef.ravel(), \"Scale\": numpy.array([scale_f8], dtype=numpy.float32)}\n",
    ")[0]\n",
    "qu_f8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "459cf5fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.05603718,  0.0720478 , -0.00600398, ...,  0.02001328,\n",
       "        0.00550365,  0.20813808], dtype=float32)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qu_f8p = ref_f8.run(\n",
    "    None, {\"X\": coef.ravel(), \"Scale\": numpy.array([scale_f8p], dtype=numpy.float32)}\n",
    ")[0]\n",
    "qu_f8p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "95fe22fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.05548779,  0.06737802, -0.00396341, ...,  0.01981707,\n",
       "        0.00396341,  0.2140243 ], dtype=float32)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_u8 = make_model(\n",
    "    make_graph(\n",
    "        [\n",
    "            make_node(\n",
    "                \"Constant\",\n",
    "                [],\n",
    "                [\"Zero\"],\n",
    "                value=make_tensor(\"Zero\", TensorProto.UINT8, [1], [int(zero_u8)]),\n",
    "            ),\n",
    "            make_node(\"QuantizeLinear\", [\"X\", \"Scale\", \"Zero\"], [\"Q\"], axis=0),\n",
    "            make_node(\"DequantizeLinear\", [\"Q\", \"Scale\", \"Zero\"], [\"Y\"], axis=0),\n",
    "        ],\n",
    "        \"quu8\",\n",
    "        [X, Scale],\n",
    "        [Y],\n",
    "    ),\n",
    "    opset_imports=[make_operatorsetid(\"\", 19)],\n",
    ")\n",
    "\n",
    "ref_u8 = ReferenceEvaluator(model_u8)\n",
    "qu_u8 = ref_u8.run(\n",
    "    None, {\"X\": coef.ravel(), \"Scale\": numpy.array([scale_u8], dtype=numpy.float32)}\n",
    ")[0]\n",
    "qu_u8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "e9e49f1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6.497171816517831e-06, 6.141178007996629e-06, 3.0187591841210397e-06)"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "err_f8 = ((coef.ravel() - qu_f8) ** 2).sum() ** 0.5 / coef.size\n",
    "err_f8p = ((coef.ravel() - qu_f8p) ** 2).sum() ** 0.5 / coef.size\n",
    "err_u8 = ((coef.ravel() - qu_u8) ** 2).sum() ** 0.5 / coef.size\n",
    "err_f8, err_f8p, err_u8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "797aac3e",
   "metadata": {},
   "source": [
    "Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "ee4b9887",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(4, 3, figsize=(12, 12), sharey=True, sharex=True)\n",
    "for i, bins in [(0, 64), (1, 128), (2, 256), (3, 512)]:\n",
    "    axs[i, 0].set_ylabel(f\"bins={bins}\")\n",
    "    axs[i, 0].hist(coef.ravel(), bins=bins, density=True, label=\"coef\", alpha=0.5)\n",
    "    axs[i, 0].hist(qu_f8, bins=bins, alpha=0.5, label=\"qdq_f8\", density=True)\n",
    "    axs[i, 0].legend()\n",
    "    axs[i, 0].set_title(f\"QDQ E4M3FN (same) - err={err_f8:1.3g}\")\n",
    "\n",
    "    axs[i, 1].hist(coef.ravel(), bins=bins, density=True, label=\"coef\", alpha=0.5)\n",
    "    axs[i, 1].hist(qu_f8p, bins=bins, alpha=0.5, label=\"qdq_f8\", density=True)\n",
    "    axs[i, 1].legend()\n",
    "    axs[i, 1].set_title(f\"QDQ E4M3FN (p3) - err={err_f8p:1.3g}\")\n",
    "\n",
    "    axs[i, 2].hist(coef.ravel(), bins=bins, density=True, label=\"coef\", alpha=0.5)\n",
    "    axs[i, 2].hist(qu_u8, bins=bins, alpha=0.5, label=\"qdq_u8\", density=True)\n",
    "    axs[i, 2].legend()\n",
    "    axs[i, 2].set_title(f\"QDQ uint 8 - err={err_u8:1.3g}\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b9b6aa7",
   "metadata": {},
   "source": [
    "## Other scales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "1efabcbe",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:08<00:00,  1.15it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>scale</th>\n",
       "      <th>err</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.122887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000440</td>\n",
       "      <td>0.025486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000733</td>\n",
       "      <td>0.007755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.001027</td>\n",
       "      <td>0.006265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.001320</td>\n",
       "      <td>0.006142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.001614</td>\n",
       "      <td>0.006165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.001907</td>\n",
       "      <td>0.006151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.002200</td>\n",
       "      <td>0.006154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.002494</td>\n",
       "      <td>0.006152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.002787</td>\n",
       "      <td>0.006161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      scale       err\n",
       "0  0.000147  0.122887\n",
       "1  0.000440  0.025486\n",
       "2  0.000733  0.007755\n",
       "3  0.001027  0.006265\n",
       "4  0.001320  0.006142\n",
       "5  0.001614  0.006165\n",
       "6  0.001907  0.006151\n",
       "7  0.002200  0.006154\n",
       "8  0.002494  0.006152\n",
       "9  0.002787  0.006161"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import DataFrame\n",
    "from tqdm import tqdm\n",
    "\n",
    "a = 0.00014669707383747942\n",
    "h = 0.00014669707383747942 * 2\n",
    "\n",
    "data = []\n",
    "for scale in tqdm([a + h * i for i in range(10)]):\n",
    "    got = ref_f8.run(\n",
    "        None, {\"X\": coef.ravel(), \"Scale\": numpy.array([scale], dtype=numpy.float32)}\n",
    "    )[0]\n",
    "    err = ((coef.ravel() - got) ** 2).sum() ** 0.5 / coef.size\n",
    "    obs = dict(scale=scale, err=err*1000)\n",
    "    data.append(obs)\n",
    "    \n",
    "df = DataFrame(data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "53fbc33d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x=\"scale\", y=\"err\", logy=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7e555ce",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}