WeightWatcher-Full-PyTorchCV.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# WeightWatcher\n",
    "\n",
    "### Analysis of all Models installed from source\n",
    "\n",
    "https://pypi.org/project/pytorchcv/\n",
    "\n",
    "https://github.com/osmr/imgclsmob\n",
    "\n",
    "As of March 2019\n",
    " \n",
    "\n",
    "https://calculationconsulting.com"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-27T00:40:06.579614Z",
     "start_time": "2018-11-27T00:40:06.567687Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Suppress the powerlaw package warnings\n",
    "# \"powerlaw.py:700: RuntimeWarning: divide by zero encountered in true_divide\"\n",
    "# \"powerlaw.py:700: RuntimeWarning: invalid value encountered in true_divide\"\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=RuntimeWarning)\n",
    "\n",
    "# crea\n",
    "import logging\n",
    "logger = logging.getLogger(\"imported_module\")\n",
    "logger.setLevel(logging.CRITICAL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/charleshmartin/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from pytorchcv.model_provider import get_model as ptcv_get_model\n",
    "import torch\n",
    "\n",
    "import weightwatcher as ww"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pytorchcv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 338 Models to examine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "338"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pytorchcv.model_provider._models.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alexnet\n",
      "zfnet\n",
      "zfnet not found\n",
      "vgg11\n",
      "Downloading /Users/charleshmartin/.torch/models/vgg11-1137-8a64fe7a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.109/vgg11-1137-8a64fe7a.pth.zip...\n",
      "vgg13\n",
      "Downloading /Users/charleshmartin/.torch/models/vgg13-1075-24178cab.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.109/vgg13-1075-24178cab.pth.zip...\n",
      "vgg16\n",
      "Downloading /Users/charleshmartin/.torch/models/vgg16-0892-10f44f68.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.109/vgg16-0892-10f44f68.pth.zip...\n",
      "vgg19\n",
      "Downloading /Users/charleshmartin/.torch/models/vgg19-0839-d4e69a0d.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.109/vgg19-0839-d4e69a0d.pth.zip...\n",
      "bn_vgg11\n",
      "bn_vgg11 not found\n",
      "bn_vgg13\n",
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      "bn_vgg16\n",
      "bn_vgg16 not found\n",
      "bn_vgg19\n",
      "bn_vgg19 not found\n",
      "bn_vgg11b\n",
      "Downloading /Users/charleshmartin/.torch/models/bn_vgg11b-1019-98d7e914.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.110/bn_vgg11b-1019-98d7e914.pth.zip...\n",
      "bn_vgg13b\n",
      "Downloading /Users/charleshmartin/.torch/models/bn_vgg13b-0963-cf9352f4.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.110/bn_vgg13b-0963-cf9352f4.pth.zip...\n",
      "bn_vgg16b\n",
      "Downloading /Users/charleshmartin/.torch/models/bn_vgg16b-0874-af4f2d0b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.110/bn_vgg16b-0874-af4f2d0b.pth.zip...\n",
      "bn_vgg19b\n",
      "Downloading /Users/charleshmartin/.torch/models/bn_vgg19b-0840-b6919f7f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.110/bn_vgg19b-0840-b6919f7f.pth.zip...\n",
      "bninception\n",
      "Downloading /Users/charleshmartin/.torch/models/bninception-0804-99ff8708.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.139/bninception-0804-99ff8708.pth.zip...\n",
      "resnet10\n",
      "resnet12\n",
      "resnet14\n",
      "resnet16\n",
      "resnet18_wd4\n",
      "resnet18_wd2\n",
      "resnet18_w3d4\n",
      "resnet18\n",
      "resnet34\n",
      "resnet50\n",
      "Downloading /Users/charleshmartin/.torch/models/resnet50-0658-828686d7.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.147/resnet50-0658-828686d7.pth.zip...\n",
      "resnet50b\n",
      "Downloading /Users/charleshmartin/.torch/models/resnet50b-0645-a53df64c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.146/resnet50b-0645-a53df64c.pth.zip...\n",
      "resnet101\n",
      "resnet101b\n",
      "Downloading /Users/charleshmartin/.torch/models/resnet101b-0561-9fbf0696.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.145/resnet101b-0561-9fbf0696.pth.zip...\n",
      "resnet152\n",
      "Downloading /Users/charleshmartin/.torch/models/resnet152-0550-800b2cb1.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.144/resnet152-0550-800b2cb1.pth.zip...\n",
      "resnet152b\n",
      "Downloading /Users/charleshmartin/.torch/models/resnet152b-0534-e02a8bf7.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.143/resnet152b-0534-e02a8bf7.pth.zip...\n",
      "resnet200\n",
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      "preresnet18\n",
      "Downloading /Users/charleshmartin/.torch/models/preresnet18-0972-5651bc2d.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.140/preresnet18-0972-5651bc2d.pth.zip...\n",
      "preresnet34\n",
      "preresnet50\n",
      "preresnet50b\n",
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      "preresnet152\n",
      "preresnet152b\n",
      "preresnet200\n",
      "preresnet200 not found\n",
      "preresnet200b\n",
      "preresnet269b\n",
      "resnext50_32x4d\n",
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      "resnext101_32x4d\n",
      "resnext101_64x4d\n",
      "seresnet18\n",
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      "seresnet50b\n",
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      "sepreresnet200\n",
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      "sepreresnet200b\n",
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      "seresnext50_32x4d\n",
      "seresnext101_32x4d\n",
      "seresnext101_64x4d\n",
      "seresnext101_64x4d not found\n",
      "senet52\n",
      "senet52 not found\n",
      "senet103\n",
      "senet103 not found\n",
      "senet154\n",
      "ibn_resnet50\n",
      "Downloading /Users/charleshmartin/.torch/models/ibn_resnet50-0641-e48a1fe5.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibn_resnet50-0641-e48a1fe5.pth.zip...\n",
      "ibn_resnet101\n",
      "Downloading /Users/charleshmartin/.torch/models/ibn_resnet101-0561-5279c78a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibn_resnet101-0561-5279c78a.pth.zip...\n",
      "ibn_resnet152\n",
      "ibn_resnet152 not found\n",
      "ibnb_resnet50\n",
      "Downloading /Users/charleshmartin/.torch/models/ibnb_resnet50-0686-e138995e.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibnb_resnet50-0686-e138995e.pth.zip...\n",
      "ibnb_resnet101\n",
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      "ibn_resnext50_32x4d\n",
      "ibn_resnext50_32x4d not found\n",
      "ibn_resnext101_32x4d\n",
      "Downloading /Users/charleshmartin/.torch/models/ibn_resnext101_32x4d-0542-b5233c66.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibn_resnext101_32x4d-0542-b5233c66.pth.zip...\n",
      "ibn_resnext101_64x4d\n",
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      "ibn_densenet121\n",
      "Downloading /Users/charleshmartin/.torch/models/ibn_densenet121-0725-b90b0615.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibn_densenet121-0725-b90b0615.pth.zip...\n",
      "ibn_densenet161\n",
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      "ibn_densenet169\n",
      "Downloading /Users/charleshmartin/.torch/models/ibn_densenet169-0651-96dd755e.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.127/ibn_densenet169-0651-96dd755e.pth.zip...\n",
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      "airnet50_1x64d_r2\n",
      "Downloading /Users/charleshmartin/.torch/models/airnet50_1x64d_r2-0590-3ec42212.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.120/airnet50_1x64d_r2-0590-3ec42212.pth.zip...\n",
      "airnet50_1x64d_r16\n",
      "Downloading /Users/charleshmartin/.torch/models/airnet50_1x64d_r16-0619-090179e7.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.120/airnet50_1x64d_r16-0619-090179e7.pth.zip...\n",
      "airnet101_1x64d_r2\n",
      "airnet101_1x64d_r2 not found\n",
      "airnext50_32x4d_r2\n",
      "Downloading /Users/charleshmartin/.torch/models/airnext50_32x4d_r2-0551-c68156e5.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.120/airnext50_32x4d_r2-0551-c68156e5.pth.zip...\n",
      "airnext101_32x4d_r2\n",
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      "airnext101_32x4d_r16\n",
      "airnext101_32x4d_r16 not found\n",
      "bam_resnet18\n",
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      "bam_resnet50\n",
      "Downloading /Users/charleshmartin/.torch/models/bam_resnet50-0658-96a37c82.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.124/bam_resnet50-0658-96a37c82.pth.zip...\n",
      "bam_resnet101\n",
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      "cbam_resnet50\n",
      "Downloading /Users/charleshmartin/.torch/models/cbam_resnet50-0605-a1172fe6.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.125/cbam_resnet50-0605-a1172fe6.pth.zip...\n",
      "cbam_resnet101\n",
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      "resattnet56\n",
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      "resattnet236\n",
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      "resattnet452\n",
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      "pyramidnet101_a360\n",
      "Downloading /Users/charleshmartin/.torch/models/pyramidnet101_a360-0620-3a24427b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.104/pyramidnet101_a360-0620-3a24427b.pth.zip...\n",
      "diracnet18v2\n",
      "Downloading /Users/charleshmartin/.torch/models/diracnet18v2-1170-e0673770.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.111/diracnet18v2-1170-e0673770.pth.zip...\n",
      "diracnet34v2\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading /Users/charleshmartin/.torch/models/diracnet34v2-0993-a6a661c0.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.111/diracnet34v2-0993-a6a661c0.pth.zip...\n",
      "sharesnet18\n",
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      "sharesnet152\n",
      "sharesnet152 not found\n",
      "sharesnet152b\n",
      "sharesnet152b not found\n",
      "densenet121\n",
      "densenet161\n",
      "densenet169\n",
      "densenet201\n",
      "condensenet74_c4_g4\n",
      "condensenet74_c8_g8\n",
      "sparsenet121\n",
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      "sparsenet201\n",
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      "sparsenet264\n",
      "sparsenet264 not found\n",
      "peleenet\n",
      "Downloading /Users/charleshmartin/.torch/models/peleenet-1151-9c47b802.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.141/peleenet-1151-9c47b802.pth.zip...\n",
      "wrn50_2\n",
      "Downloading /Users/charleshmartin/.torch/models/wrn50_2-0641-83897ab9.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.113/wrn50_2-0641-83897ab9.pth.zip...\n",
      "drnc26\n",
      "Downloading /Users/charleshmartin/.torch/models/drnc26-0755-35405bd5.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnc26-0755-35405bd5.pth.zip...\n",
      "drnc42\n",
      "Downloading /Users/charleshmartin/.torch/models/drnc42-0657-7c99c460.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnc42-0657-7c99c460.pth.zip...\n",
      "drnc58\n",
      "Downloading /Users/charleshmartin/.torch/models/drnc58-0601-70ec1f56.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnc58-0601-70ec1f56.pth.zip...\n",
      "drnd22\n",
      "Downloading /Users/charleshmartin/.torch/models/drnd22-0823-5c2c6a0c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnd22-0823-5c2c6a0c.pth.zip...\n",
      "drnd38\n",
      "Downloading /Users/charleshmartin/.torch/models/drnd38-0695-4630f0fb.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnd38-0695-4630f0fb.pth.zip...\n",
      "drnd54\n",
      "Downloading /Users/charleshmartin/.torch/models/drnd54-0586-bfdc1f88.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnd54-0586-bfdc1f88.pth.zip...\n",
      "drnd105\n",
      "Downloading /Users/charleshmartin/.torch/models/drnd105-0548-a643f4dc.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.116/drnd105-0548-a643f4dc.pth.zip...\n",
      "dpn68\n",
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      "darknet_ref\n",
      "Downloading /Users/charleshmartin/.torch/models/darknet_ref-1718-034595b4.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.64/darknet_ref-1718-034595b4.pth.zip...\n",
      "darknet_tiny\n",
      "Downloading /Users/charleshmartin/.torch/models/darknet_tiny-1784-4561e1ad.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.69/darknet_tiny-1784-4561e1ad.pth.zip...\n",
      "darknet19\n",
      "darknet19 not found\n",
      "darknet53\n",
      "Downloading /Users/charleshmartin/.torch/models/darknet53-0564-b36bef6b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.150/darknet53-0564-b36bef6b.pth.zip...\n",
      "channelnet\n",
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      "dla34\n",
      "Downloading /Users/charleshmartin/.torch/models/dla34-0794-04698d78.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla34-0794-04698d78.pth.zip...\n",
      "dla46c\n",
      "Downloading /Users/charleshmartin/.torch/models/dla46c-1371-cc919179.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla46c-1371-cc919179.pth.zip...\n",
      "dla46xc\n",
      "Downloading /Users/charleshmartin/.torch/models/dla46xc-1302-1161f37b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla46xc-1302-1161f37b.pth.zip...\n",
      "dla60\n",
      "Downloading /Users/charleshmartin/.torch/models/dla60-0669-b2cd6e51.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla60-0669-b2cd6e51.pth.zip...\n",
      "dla60x\n",
      "Downloading /Users/charleshmartin/.torch/models/dla60x-0598-88547d3f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla60x-0598-88547d3f.pth.zip...\n",
      "dla60xc\n",
      "Downloading /Users/charleshmartin/.torch/models/dla60xc-1157-c413bb80.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla60xc-1157-c413bb80.pth.zip...\n",
      "dla102\n",
      "Downloading /Users/charleshmartin/.torch/models/dla102-0605-11df1322.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla102-0605-11df1322.pth.zip...\n",
      "dla102x\n",
      "Downloading /Users/charleshmartin/.torch/models/dla102x-0577-58331655.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla102x-0577-58331655.pth.zip...\n",
      "dla102x2\n",
      "Downloading /Users/charleshmartin/.torch/models/dla102x2-0536-07936111.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla102x2-0536-07936111.pth.zip...\n",
      "dla169\n",
      "Downloading /Users/charleshmartin/.torch/models/dla169-0566-ae0c6a82.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.202/dla169-0566-ae0c6a82.pth.zip...\n",
      "msdnet22\n",
      "msdnet22 not found\n",
      "fishnet99\n",
      "fishnet99 not found\n",
      "fishnet150\n",
      "Downloading /Users/charleshmartin/.torch/models/fishnet150-0604-f5af4873.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.168/fishnet150-0604-f5af4873.pth.zip...\n",
      "espnetv2_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/espnetv2_wd2-2015-d234781f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.238/espnetv2_wd2-2015-d234781f.pth.zip...\n",
      "espnetv2_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/espnetv2_w1-1345-550d5422.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.238/espnetv2_w1-1345-550d5422.pth.zip...\n",
      "espnetv2_w5d4\n",
      "Downloading /Users/charleshmartin/.torch/models/espnetv2_w5d4-1218-85d97b2b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.238/espnetv2_w5d4-1218-85d97b2b.pth.zip...\n",
      "espnetv2_w3d2\n",
      "Downloading /Users/charleshmartin/.torch/models/espnetv2_w3d2-1129-3bbb49ad.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.238/espnetv2_w3d2-1129-3bbb49ad.pth.zip...\n",
      "espnetv2_w2\n",
      "Downloading /Users/charleshmartin/.torch/models/espnetv2_w2-0961-13ba0f72.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.238/espnetv2_w2-0961-13ba0f72.pth.zip...\n",
      "xdensenet121_2\n",
      "xdensenet121_2 not found\n",
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      "xdensenet201_2\n",
      "xdensenet201_2 not found\n",
      "squeezenet_v1_0\n",
      "Downloading /Users/charleshmartin/.torch/models/squeezenet_v1_0-1766-afdbcf1a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.128/squeezenet_v1_0-1766-afdbcf1a.pth.zip...\n",
      "squeezenet_v1_1\n",
      "Downloading /Users/charleshmartin/.torch/models/squeezenet_v1_1-1772-25b77bc3.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.88/squeezenet_v1_1-1772-25b77bc3.pth.zip...\n",
      "squeezeresnet_v1_0\n",
      "Downloading /Users/charleshmartin/.torch/models/squeezeresnet_v1_0-1809-25bfc02e.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.178/squeezeresnet_v1_0-1809-25bfc02e.pth.zip...\n",
      "squeezeresnet_v1_1\n",
      "Downloading /Users/charleshmartin/.torch/models/squeezeresnet_v1_1-1821-c27ed88f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.70/squeezeresnet_v1_1-1821-c27ed88f.pth.zip...\n",
      "sqnxt23_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23_w1-1906-97b74e0c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.171/sqnxt23_w1-1906-97b74e0c.pth.zip...\n",
      "sqnxt23_w3d2\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23_w3d2-1350-c2f21bce.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.210/sqnxt23_w3d2-1350-c2f21bce.pth.zip...\n",
      "sqnxt23_w2\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23_w2-1100-b9bb7302.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.240/sqnxt23_w2-1100-b9bb7302.pth.zip...\n",
      "sqnxt23v5_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23v5_w1-1785-2fe3ad67.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.172/sqnxt23v5_w1-1785-2fe3ad67.pth.zip...\n",
      "sqnxt23v5_w3d2\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23v5_w3d2-1301-c244844b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.212/sqnxt23v5_w3d2-1301-c244844b.pth.zip...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sqnxt23v5_w2\n",
      "Downloading /Users/charleshmartin/.torch/models/sqnxt23v5_w2-1066-229b0d3d.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.216/sqnxt23v5_w2-1066-229b0d3d.pth.zip...\n",
      "shufflenet_g1_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g1_w1-1389-4cfb65a3.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.223/shufflenet_g1_w1-1389-4cfb65a3.pth.zip...\n",
      "shufflenet_g2_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g2_w1-1363-07256203.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.241/shufflenet_g2_w1-1363-07256203.pth.zip...\n",
      "shufflenet_g3_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g3_w1-1348-ce54f64e.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.244/shufflenet_g3_w1-1348-ce54f64e.pth.zip...\n",
      "shufflenet_g4_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g4_w1-1335-e2415f82.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.245/shufflenet_g4_w1-1335-e2415f82.pth.zip...\n",
      "shufflenet_g8_w1\n",
      "shufflenet_g8_w1 not found\n",
      "shufflenet_g1_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g1_w3d4-1711-161cd24a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.218/shufflenet_g1_w3d4-1711-161cd24a.pth.zip...\n",
      "shufflenet_g3_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g3_w3d4-1650-3f3b0aef.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.219/shufflenet_g3_w3d4-1650-3f3b0aef.pth.zip...\n",
      "shufflenet_g1_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g1_wd2-2261-dae4bdad.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.174/shufflenet_g1_wd2-2261-dae4bdad.pth.zip...\n",
      "shufflenet_g3_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g3_wd2-2080-ccaacfc8.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.167/shufflenet_g3_wd2-2080-ccaacfc8.pth.zip...\n",
      "shufflenet_g1_wd4\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g1_wd4-3729-47dbd0f2.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.134/shufflenet_g1_wd4-3729-47dbd0f2.pth.zip...\n",
      "shufflenet_g3_wd4\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenet_g3_wd4-3653-6abdd65e.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.135/shufflenet_g3_wd4-3653-6abdd65e.pth.zip...\n",
      "shufflenetv2_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2_wd2-1865-9c22238b.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.90/shufflenetv2_wd2-1865-9c22238b.pth.zip...\n",
      "shufflenetv2_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2_w1-1163-c71dfb7a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.133/shufflenetv2_w1-1163-c71dfb7a.pth.zip...\n",
      "shufflenetv2_w3d2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2_w3d2-1269-536ad5b1.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.65/shufflenetv2_w3d2-1269-536ad5b1.pth.zip...\n",
      "shufflenetv2_w2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2_w2-1249-b9f9e84c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.84/shufflenetv2_w2-1249-b9f9e84c.pth.zip...\n",
      "shufflenetv2b_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2b_wd2-1822-01d18d6f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.157/shufflenetv2b_wd2-1822-01d18d6f.pth.zip...\n",
      "shufflenetv2b_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2b_w1-1125-6a5d3dc4.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.161/shufflenetv2b_w1-1125-6a5d3dc4.pth.zip...\n",
      "shufflenetv2b_w3d2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2b_w3d2-0911-f2106fee.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.203/shufflenetv2b_w3d2-0911-f2106fee.pth.zip...\n",
      "shufflenetv2b_w2\n",
      "Downloading /Users/charleshmartin/.torch/models/shufflenetv2b_w2-0834-cb36b92c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.242/shufflenetv2b_w2-0834-cb36b92c.pth.zip...\n",
      "menet108_8x1_g3\n",
      "Downloading /Users/charleshmartin/.torch/models/menet108_8x1_g3-2076-6acc82e4.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.89/menet108_8x1_g3-2076-6acc82e4.pth.zip...\n",
      "menet128_8x1_g4\n",
      "Downloading /Users/charleshmartin/.torch/models/menet128_8x1_g4-1959-48fa80fc.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.103/menet128_8x1_g4-1959-48fa80fc.pth.zip...\n",
      "menet160_8x1_g8\n",
      "Downloading /Users/charleshmartin/.torch/models/menet160_8x1_g8-2084-0f4fce43.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.154/menet160_8x1_g8-2084-0f4fce43.pth.zip...\n",
      "menet228_12x1_g3\n",
      "Downloading /Users/charleshmartin/.torch/models/menet228_12x1_g3-1316-5b670c42.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.131/menet228_12x1_g3-1316-5b670c42.pth.zip...\n",
      "menet256_12x1_g4\n",
      "Downloading /Users/charleshmartin/.torch/models/menet256_12x1_g4-1252-14c6c86d.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.152/menet256_12x1_g4-1252-14c6c86d.pth.zip...\n",
      "menet348_12x1_g3\n",
      "Downloading /Users/charleshmartin/.torch/models/menet348_12x1_g3-0958-ad50f635.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.173/menet348_12x1_g3-0958-ad50f635.pth.zip...\n",
      "menet352_12x1_g8\n",
      "Downloading /Users/charleshmartin/.torch/models/menet352_12x1_g8-1200-4ee200c5.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.198/menet352_12x1_g8-1200-4ee200c5.pth.zip...\n",
      "menet456_24x1_g3\n",
      "Downloading /Users/charleshmartin/.torch/models/menet456_24x1_g3-0799-826c0022.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.237/menet456_24x1_g3-0799-826c0022.pth.zip...\n",
      "mobilenet_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenet_w1-0895-7e1d739f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.155/mobilenet_w1-0895-7e1d739f.pth.zip...\n",
      "mobilenet_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenet_w3d4-1076-d801bcae.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.130/mobilenet_w3d4-1076-d801bcae.pth.zip...\n",
      "mobilenet_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenet_wd2-1355-41a21242.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.156/mobilenet_wd2-1355-41a21242.pth.zip...\n",
      "mobilenet_wd4\n",
      "fdmobilenet_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/fdmobilenet_w1-1338-9d026c04.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.162/fdmobilenet_w1-1338-9d026c04.pth.zip...\n",
      "fdmobilenet_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/fdmobilenet_w3d4-1641-5561d58a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.159/fdmobilenet_w3d4-1641-5561d58a.pth.zip...\n",
      "fdmobilenet_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/fdmobilenet_wd2-2015-414dbeed.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.83/fdmobilenet_wd2-2015-414dbeed.pth.zip...\n",
      "fdmobilenet_wd4\n",
      "Downloading /Users/charleshmartin/.torch/models/fdmobilenet_wd4-3098-2b22b709.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.177/fdmobilenet_wd4-3098-2b22b709.pth.zip...\n",
      "mobilenetv2_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenetv2_w1-0887-13a021bc.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.213/mobilenetv2_w1-0887-13a021bc.pth.zip...\n",
      "mobilenetv2_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenetv2_w3d4-1082-8656de5a.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.230/mobilenetv2_w3d4-1082-8656de5a.pth.zip...\n",
      "mobilenetv2_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenetv2_wd2-1493-b82d79f6.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.170/mobilenetv2_wd2-1493-b82d79f6.pth.zip...\n",
      "mobilenetv2_wd4\n",
      "Downloading /Users/charleshmartin/.torch/models/mobilenetv2_wd4-2451-05e1e3a2.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.137/mobilenetv2_wd4-2451-05e1e3a2.pth.zip...\n",
      "igcv3_w1\n",
      "Downloading /Users/charleshmartin/.torch/models/igcv3_w1-0920-12385791.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.243/igcv3_w1-0920-12385791.pth.zip...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "igcv3_w3d4\n",
      "Downloading /Users/charleshmartin/.torch/models/igcv3_w3d4-1140-63f43cf8.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.207/igcv3_w3d4-1140-63f43cf8.pth.zip...\n",
      "igcv3_wd2\n",
      "Downloading /Users/charleshmartin/.torch/models/igcv3_wd2-1732-8c504f44.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.132/igcv3_wd2-1732-8c504f44.pth.zip...\n",
      "igcv3_wd4\n",
      "Downloading /Users/charleshmartin/.torch/models/igcv3_wd4-2871-c9f28301.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.142/igcv3_wd4-2871-c9f28301.pth.zip...\n",
      "mnasnet\n",
      "Downloading /Users/charleshmartin/.torch/models/mnasnet-1174-e8ec017c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.117/mnasnet-1174-e8ec017c.pth.zip...\n",
      "darts\n",
      "Downloading /Users/charleshmartin/.torch/models/darts-0874-74f0c7b6.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.118/darts-0874-74f0c7b6.pth.zip...\n",
      "xception\n",
      "Downloading /Users/charleshmartin/.torch/models/xception-0549-e4f0232c.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.115/xception-0549-e4f0232c.pth.zip...\n",
      "inceptionv3\n",
      "Downloading /Users/charleshmartin/.torch/models/inceptionv3-0565-cf406180.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.92/inceptionv3-0565-cf406180.pth.zip...\n",
      "inceptionv4\n",
      "Downloading /Users/charleshmartin/.torch/models/inceptionv4-0529-5cb7b4e4.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.105/inceptionv4-0529-5cb7b4e4.pth.zip...\n",
      "inceptionresnetv2\n",
      "Downloading /Users/charleshmartin/.torch/models/inceptionresnetv2-0490-1d1b4d18.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.107/inceptionresnetv2-0490-1d1b4d18.pth.zip...\n",
      "polynet\n",
      "Downloading /Users/charleshmartin/.torch/models/polynet-0452-6a1b295d.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.96/polynet-0452-6a1b295d.pth.zip...\n",
      "nasnet_4a1056\n",
      "Downloading /Users/charleshmartin/.torch/models/nasnet_4a1056-0816-d21bbaf5.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.97/nasnet_4a1056-0816-d21bbaf5.pth.zip...\n",
      "nasnet_6a4032\n",
      "Downloading /Users/charleshmartin/.torch/models/nasnet_6a4032-0421-f354d28f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.101/nasnet_6a4032-0421-f354d28f.pth.zip...\n",
      "pnasnet5large\n",
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      "Downloading /Users/charleshmartin/.torch/models/resnet164bn_cifar100-2044-8fa07b72.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.182/resnet164bn_cifar100-2044-8fa07b72.pth.zip...\n",
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     ]
    },
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     ]
    },
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      "shakeshakeresnet20_2x16d_cifar100\n",
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      "shakeshakeresnet26_2x32d_cifar10\n",
      "Downloading /Users/charleshmartin/.torch/models/shakeshakeresnet26_2x32d_cifar10-0317-ecd1f833.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.217/shakeshakeresnet26_2x32d_cifar10-0317-ecd1f833.pth.zip...\n",
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      "Downloading /Users/charleshmartin/.torch/models/shakeshakeresnet26_2x32d_cifar100-1880-b47e371f.pth.zip from https://github.com/osmr/imgclsmob/releases/download/v0.0.222/shakeshakeresnet26_2x32d_cifar100-1880-b47e371f.pth.zip...\n",
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      "isqrtcovresnet101 not found\n",
      "isqrtcovresnet101b\n",
      "isqrtcovresnet101b not found\n"
     ]
    }
   ],
   "source": [
    "data = {}\n",
    "for modelname in pytorchcv.model_provider._models.keys():\n",
    "    print(modelname)\n",
    "    try:\n",
    "        model = ptcv_get_model(modelname, pretrained=True)\n",
    "        watcher = ww.WeightWatcher(model=model, logger=logger)\n",
    "        results = watcher.analyze(compute_alphas=True)\n",
    "\n",
    "        data[modelname]=watcher.get_summary()\n",
    "    except:\n",
    "        print(\"{} not found\".format(modelname))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### HTML Tables\n",
    "\n",
    "- tables[0]:  ImageNet-1K\n",
    "- tables[1]:  CIFAR-10\n",
    "- tables[2]:  CIFAR-100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "tables = pd.read_html(\"pytorchcv.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "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>Model</th>\n",
       "      <th>Top1</th>\n",
       "      <th>Top5</th>\n",
       "      <th>Params</th>\n",
       "      <th>FLOPs/2</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AlexNet</td>\n",
       "      <td>43.48</td>\n",
       "      <td>20.93</td>\n",
       "      <td>61100840</td>\n",
       "      <td>714.83M</td>\n",
       "      <td>From dmlc/gluon-cv (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>VGG-11</td>\n",
       "      <td>30.98</td>\n",
       "      <td>11.37</td>\n",
       "      <td>132863336</td>\n",
       "      <td>7,615.87M</td>\n",
       "      <td>From dmlc/gluon-cv (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>VGG-13</td>\n",
       "      <td>30.07</td>\n",
       "      <td>10.75</td>\n",
       "      <td>133047848</td>\n",
       "      <td>11,317.65M</td>\n",
       "      <td>From dmlc/gluon-cv (log)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Model   Top1   Top5     Params     FLOPs/2                   Remarks\n",
       "0  AlexNet  43.48  20.93   61100840     714.83M  From dmlc/gluon-cv (log)\n",
       "1   VGG-11  30.98  11.37  132863336   7,615.87M  From dmlc/gluon-cv (log)\n",
       "2   VGG-13  30.07  10.75  133047848  11,317.65M  From dmlc/gluon-cv (log)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tables[0].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "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>Model</th>\n",
       "      <th>Error, %</th>\n",
       "      <th>Params</th>\n",
       "      <th>FLOPs/2</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NIN</td>\n",
       "      <td>7.43</td>\n",
       "      <td>966986</td>\n",
       "      <td>222.97M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ResNet-20</td>\n",
       "      <td>5.97</td>\n",
       "      <td>272474</td>\n",
       "      <td>41.29M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ResNet-56</td>\n",
       "      <td>4.52</td>\n",
       "      <td>855770</td>\n",
       "      <td>127.06M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Model  Error, %  Params  FLOPs/2                        Remarks\n",
       "0        NIN      7.43  966986  222.97M  Converted from GL model (log)\n",
       "1  ResNet-20      5.97  272474   41.29M  Converted from GL model (log)\n",
       "2  ResNet-56      4.52  855770  127.06M  Converted from GL model (log)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tables[1].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "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>Model</th>\n",
       "      <th>Error, %</th>\n",
       "      <th>Params</th>\n",
       "      <th>FLOPs/2</th>\n",
       "      <th>Remarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NIN</td>\n",
       "      <td>28.39</td>\n",
       "      <td>984356</td>\n",
       "      <td>224.08M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ResNet-20</td>\n",
       "      <td>29.64</td>\n",
       "      <td>278324</td>\n",
       "      <td>41.30M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ResNet-56</td>\n",
       "      <td>24.88</td>\n",
       "      <td>861620</td>\n",
       "      <td>127.06M</td>\n",
       "      <td>Converted from GL model (log)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Model  Error, %  Params  FLOPs/2                        Remarks\n",
       "0        NIN     28.39  984356  224.08M  Converted from GL model (log)\n",
       "1  ResNet-20     29.64  278324   41.30M  Converted from GL model (log)\n",
       "2  ResNet-56     24.88  861620  127.06M  Converted from GL model (log)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tables[2].head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert data to Pandas Array for serialization\n",
    "\n",
    "- Notice:  we only found 212 of the potential 338 models  ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "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>alpha</th>\n",
       "      <th>alpha_compound</th>\n",
       "      <th>alpha_weighted</th>\n",
       "      <th>alpha_weighted_compound</th>\n",
       "      <th>lognorm</th>\n",
       "      <th>lognorm_compound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alexnet</th>\n",
       "      <td>2.800692</td>\n",
       "      <td>2.798364</td>\n",
       "      <td>1.709370</td>\n",
       "      <td>2.892666</td>\n",
       "      <td>0.842619</td>\n",
       "      <td>1.204102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vgg11</th>\n",
       "      <td>2.572493</td>\n",
       "      <td>2.537005</td>\n",
       "      <td>1.843995</td>\n",
       "      <td>2.458193</td>\n",
       "      <td>0.947488</td>\n",
       "      <td>1.138577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vgg13</th>\n",
       "      <td>2.689696</td>\n",
       "      <td>2.628755</td>\n",
       "      <td>1.645383</td>\n",
       "      <td>2.192308</td>\n",
       "      <td>0.864038</td>\n",
       "      <td>1.040831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vgg16</th>\n",
       "      <td>2.946330</td>\n",
       "      <td>2.851386</td>\n",
       "      <td>1.518843</td>\n",
       "      <td>1.960292</td>\n",
       "      <td>0.851659</td>\n",
       "      <td>0.992327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vgg19</th>\n",
       "      <td>3.050589</td>\n",
       "      <td>2.916136</td>\n",
       "      <td>1.282423</td>\n",
       "      <td>1.601416</td>\n",
       "      <td>0.828279</td>\n",
       "      <td>0.945530</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            alpha  alpha_compound  alpha_weighted  alpha_weighted_compound  \\\n",
       "alexnet  2.800692        2.798364        1.709370                 2.892666   \n",
       "vgg11    2.572493        2.537005        1.843995                 2.458193   \n",
       "vgg13    2.689696        2.628755        1.645383                 2.192308   \n",
       "vgg16    2.946330        2.851386        1.518843                 1.960292   \n",
       "vgg19    3.050589        2.916136        1.282423                 1.601416   \n",
       "\n",
       "          lognorm  lognorm_compound  \n",
       "alexnet  0.842619          1.204102  \n",
       "vgg11    0.947488          1.138577  \n",
       "vgg13    0.864038          1.040831  \n",
       "vgg16    0.851659          0.992327  \n",
       "vgg19    0.828279          0.945530  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddf = pd.DataFrame.from_dict(data).transpose()\n",
    "ddf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddf.to_csv(\"alpha_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "212"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ddf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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