EvenMore-pytorch-models-OSMR-Weighted-Alphas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Even More pretrained models in PyTorch from OSMR with Weighted ALphas\n",
    "\n",
    "https://github.com/osmr/imgclsmob\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:07:27.516429Z",
     "start_time": "2018-10-15T23:07:22.449981Z"
    }
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import torchvision.models as models\n",
    "import torchvision.transforms as transforms\n",
    "import torch.nn as nn\n",
    "\n",
    "import re, sys\n",
    "import pandas as pd\n",
    "from sklearn.decomposition import TruncatedSVD\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import powerlaw\n",
    "\n",
    "from tqdm import tqdm_notebook as tqdm\n",
    "\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:07:39.093486Z",
     "start_time": "2018-10-15T23:07:39.077014Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = [5,5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:08:56.821400Z",
     "start_time": "2018-10-15T23:08:56.801810Z"
    }
   },
   "outputs": [],
   "source": [
    "import pytorchcv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:09:11.756212Z",
     "start_time": "2018-10-15T23:09:02.106460Z"
    }
   },
   "outputs": [],
   "source": [
    "from pytorchcv.model_provider import get_model as ptcv_get_model\n",
    "import torch\n",
    "from torch.autograd import Variable\n",
    "\n",
    "net = ptcv_get_model(\"resnet18\", pretrained=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:11:28.315021Z",
     "start_time": "2018-10-15T23:11:28.293029Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method Module.modules of ResNet(\n",
       "  (features): Sequential(\n",
       "    (init_block): ResInitBlock(\n",
       "      (conv): ResConv(\n",
       "        (conv): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n",
       "        (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "      (pool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n",
       "    )\n",
       "    (stage1): Sequential(\n",
       "      (unit1): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "      (unit2): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "    )\n",
       "    (stage2): Sequential(\n",
       "      (unit1): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (identity_conv): ResConv(\n",
       "          (conv): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "          (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "      (unit2): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "    )\n",
       "    (stage3): Sequential(\n",
       "      (unit1): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (identity_conv): ResConv(\n",
       "          (conv): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "          (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "      (unit2): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "    )\n",
       "    (stage4): Sequential(\n",
       "      (unit1): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (identity_conv): ResConv(\n",
       "          (conv): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "          (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "      (unit2): ResUnit(\n",
       "        (body): ResBlock(\n",
       "          (conv1): ResConv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "            (activ): ReLU(inplace)\n",
       "          )\n",
       "          (conv2): ResConv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "            (bn): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "          )\n",
       "        )\n",
       "        (activ): ReLU(inplace)\n",
       "      )\n",
       "    )\n",
       "    (final_pool): AvgPool2d(kernel_size=7, stride=1, padding=0)\n",
       "  )\n",
       "  (output): Linear(in_features=512, out_features=1000, bias=True)\n",
       ")>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:59:58.621449Z",
     "start_time": "2018-10-15T23:59:58.603150Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pytorchcv.models.resnet.ResNet"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(net)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-16T00:09:35.638512Z",
     "start_time": "2018-10-16T00:09:33.907000Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object Module.modules at 0x1031a53b8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = models.resnet18(True)\n",
    "model.modules()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_conv2D_Wmats(Wtensor):\n",
    "    \"\"\"Extract W slices from a 4 index conv2D tensor of shape: (N,M,i,j) or (M,N,i,j).  Return ij (N x M) matrices\"\"\"\n",
    "    Wmats = []\n",
    "    s = Wtensor.shape\n",
    "    N, M, imax, jmax = s[0],s[1],s[2],s[3]\n",
    "    #print(\"tensor shape\", N,M,imax,jmax)\n",
    "    for i in range(imax):\n",
    "        for j in range(jmax):\n",
    "            W = Wtensor[:,:,i,j]\n",
    "            if N < M:\n",
    "                W = W.T\n",
    "            Wmats.append(W)\n",
    "    return Wmats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:45:10.955212Z",
     "start_time": "2018-10-15T23:45:10.821512Z"
    }
   },
   "outputs": [],
   "source": [
    "MIN_DIM=50\n",
    "def iter_pytorch_layers(model, min_dim=MIN_DIM):\n",
    "    \"\"\"Iterate over a pytorch layers and  weight matrix.  \n",
    "    Supports linear, conv2d, and conv2d-slices\"\"\"\n",
    "    for im, m in enumerate(model.modules()):\n",
    "        if isinstance(m, nn.Linear):     \n",
    "            W = np.array(m.weight.data.clone().cpu())\n",
    "            if W is not None:\n",
    "                yield W\n",
    "        elif isinstance(m, nn.Conv2d):\n",
    "            Wtensor = np.array(m.weight.data.clone().cpu())\n",
    "            Wmats = get_conv2D_Wmats(Wtensor)\n",
    "            for W in Wmats:\n",
    "                if (np.min(W.shape) >= min_dim):\n",
    "                    yield W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T23:12:51.434077Z",
     "start_time": "2018-10-15T23:12:51.417183Z"
    }
   },
   "outputs": [],
   "source": [
    "def num_layers(net):\n",
    "    cnt = 0\n",
    "    for W in iter_pytorch_layers(net):\n",
    "        cnt+=1\n",
    "    return cnt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../imgclsmob/osmr_modelnames\r\n"
     ]
    }
   ],
   "source": [
    "!ls  ../imgclsmob/osmr_modelnames "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "osmr = pd.read_csv(\"osmr_modelnames\", delimiter=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fixname(modelname):\n",
    "    fixedname = modelname\n",
    "    # condensenet\n",
    "    fixedname = fixedname.replace(' (C=G=4)','_c4_g4')\n",
    "    fixedname = fixedname.replace(' (C=G=8)','_c8_g8')\n",
    "    # resnet , mobilenetv2, shuffleney\n",
    "    fixedname = fixedname.replace(' x0.25','_wd4')\n",
    "    fixedname = fixedname.replace(' x0.5','_wd2')\n",
    "    fixedname = fixedname.replace(' x0.75','_w3d4')\n",
    "    fixedname = fixedname.replace(' x1.0','_w1')\n",
    "    fixedname = fixedname.replace(' x1.5','_w3d2')\n",
    "\n",
    "    \n",
    "    # menet TODO: FIX\n",
    "    fixedname = fixedname.replace(' (g=','_g')\n",
    "    # darkent\n",
    "    fixedname = fixedname.replace(' Ref','_ref')\n",
    "    fixedname = fixedname.replace(' Tiny','_tiny')\n",
    "    # squeezenet\n",
    "    fixedname = fixedname.replace(' v1.','_v1_')\n",
    "    fixedname = fixedname.replace(' V1.','_v1_')\n",
    "    fixedname = fixedname.replace(' V2.','_v2_')\n",
    "\n",
    "\n",
    "    fixedname = fixedname.replace('-','').replace(' ','')\n",
    "    fixedname = fixedname.replace('(','_').replace(')','')\n",
    "    fixedname = fixedname.lower()\n",
    "\n",
    "    if 'menet' in fixedname:\n",
    "        fixedname = \"menet\"+(fixedname.replace('menet','_'))\n",
    "    \n",
    "    return fixedname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ResNet-10 -->   resnet10\n",
      "76\n",
      "ResNet-12 -->   resnet12\n",
      "94\n",
      "ResNet-14 -->   resnet14\n",
      "112\n",
      "ResNet-16 -->   resnet16\n",
      "130\n",
      "ResNet-18 x0.25 -->   resnet18_wd4\n",
      "65\n",
      "ResNet-18 x0.5 -->   resnet18_wd2\n",
      "102\n",
      "ResNet-18 x0.75 -->   resnet18_w3d4\n",
      "102\n",
      "ResNet-18 -->   resnet18\n",
      "148\n",
      "ResNet-34 -->   resnet34\n",
      "292\n",
      "ResNet-50 -->   resnet50\n",
      "181\n",
      "ResNet-50b -->   resnet50b\n",
      "181\n",
      "ResNet-101 -->   resnet101\n",
      "368\n",
      "ResNet-101b -->   resnet101b\n",
      "368\n",
      "ResNet-152 -->   resnet152\n",
      "555\n",
      "ResNet-152b -->   resnet152b\n",
      "555\n",
      "PreResNet-18 -->   preresnet18\n",
      "148\n",
      "PreResNet-34 -->   preresnet34\n",
      "292\n",
      "PreResNet-50 -->   preresnet50\n",
      "181\n",
      "PreResNet-50b -->   preresnet50b\n",
      "181\n",
      "PreResNet-101 -->   preresnet101\n",
      "368\n",
      "PreResNet-101b -->   preresnet101b\n",
      "368\n",
      "PreResNet-152 -->   preresnet152\n",
      "555\n",
      "PreResNet-152b -->   preresnet152b\n",
      "555\n",
      "PreResNet-200b -->   preresnet200b\n",
      "731\n",
      "ResNeXt-101 (32x4d) -->   resnext101_32x4d\n",
      "71\n",
      "ResNeXt-101 (64x4d) -->   resnext101_64x4d\n",
      "71\n",
      "SE-ResNet-50 -->   seresnet50\n",
      "199\n",
      "SE-ResNet-101 -->   seresnet101\n",
      "420\n",
      "SE-ResNet-152 -->   seresnet152\n",
      "633\n",
      "SE-ResNeXt-50 (32x4d) -->   seresnext50_32x4d\n",
      "55\n",
      "SE-ResNeXt-101 (32x4d) -->   seresnext101_32x4d\n",
      "123\n",
      "SENet-154 -->   senet154\n",
      "225\n",
      "DenseNet-121 -->   densenet121\n",
      "62\n",
      "DenseNet-161 -->   densenet161\n",
      "82\n",
      "DenseNet-169 -->   densenet169\n",
      "86\n",
      "DenseNet-201 -->   densenet201\n",
      "102\n",
      "CondenseNet-74 (C=G=4) -->   condensenet74_c4_g4\n",
      "187\n",
      "CondenseNet-74 (C=G=8) -->   condensenet74_c8_g8\n",
      "91\n",
      "DPN-68 -->   dpn68\n",
      "47\n",
      "DPN-98 -->   dpn98\n",
      "69\n",
      "DPN-131 -->   dpn131\n",
      "91\n",
      "DarkNet Tiny -->   darknet_tiny\n",
      "22\n",
      "DarkNet Ref -->   darknet_ref\n",
      "Pretrained model for darknet_ref is not available.\n",
      "SqueezeNet v1.0 -->   squeezenet_v1_0\n",
      "23\n",
      "SqueezeNet v1.1 -->   squeezenet_v1_1\n",
      "23\n",
      "ShuffleNetV2 x0.5 -->   shufflenetv2_wd2\n",
      "11\n",
      "ShuffleNetV2 x1.0 -->   shufflenetv2_w1\n",
      "35\n",
      "ShuffleNetV2 x1.5 -->   shufflenetv2_w3d2\n",
      "Pretrained model for shufflenetv2_w3d2 is not available.\n",
      "108-MENet-8x1 (g=3) -->   menet108_8x1_g3\n",
      "12\n",
      "128-MENet-8x1 (g=4) -->   menet128_8x1_g4\n",
      "12\n",
      "228-MENet-12x1 (g=3) -->   menet228_12x1_g3\n",
      "20\n",
      "256-MENet-12x1 (g=4) -->   menet256_12x1_g4\n",
      "20\n",
      "348-MENet-12x1 (g=3) -->   menet348_12x1_g3\n",
      "28\n",
      "352-MENet-12x1 (g=8) -->   menet352_12x1_g8\n",
      "12\n",
      "456-MENet-24x1 (g=3) -->   menet456_24x1_g3\n",
      "28\n",
      "MobileNet x0.25 -->   mobilenet_wd4\n",
      "10\n",
      "MobileNet x0.5 -->   mobilenet_wd2\n",
      "12\n",
      "MobileNet x0.75 -->   mobilenet_w3d4\n",
      "12\n",
      "MobileNet x1.0 -->   mobilenet_w1\n",
      "13\n",
      "FD-MobileNet x0.25 -->   fdmobilenet_wd4\n",
      "8\n",
      "FD-MobileNet x0.5 -->   fdmobilenet_wd2\n",
      "10\n",
      "FD-MobileNet x1.0 -->   fdmobilenet_w1\n",
      "11\n",
      "MobileNetV2 x0.25 -->   mobilenetv2_wd4\n",
      "3\n",
      "MobileNetV2 x0.5 -->   mobilenetv2_wd2\n",
      "9\n",
      "MobileNetV2 x0.75 -->   mobilenetv2_w3d4\n",
      "15\n",
      "MobileNetV2 x1.0 -->   mobilenetv2_w1\n",
      "23\n",
      "SNet-A-Mobile -->   snetamobile\n",
      "Unsupported model: snetamobile\n"
     ]
    }
   ],
   "source": [
    "unsupported = []\n",
    "for modelname in osmr['model'].values:\n",
    "    \n",
    "    fixedname = fixname(modelname)\n",
    "    print(modelname, \"-->  \", fixedname)\n",
    "    try:\n",
    "        net = ptcv_get_model(fixedname, pretrained=True)\n",
    "        print(num_layers(net))\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        unsupported.append(fixedname)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['darknet_ref', 'shufflenetv2_w3d2', 'snetamobile']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unsupported"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "osmr['fixedname'] = osmr['model'].apply(lambda x: fixname(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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</th>\n",
       "      <th>fixedname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ResNet-10</td>\n",
       "      <td>37.46</td>\n",
       "      <td>15.85</td>\n",
       "      <td>5,418,792</td>\n",
       "      <td>892.62M</td>\n",
       "      <td>resnet10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ResNet-12</td>\n",
       "      <td>36.18</td>\n",
       "      <td>14.80</td>\n",
       "      <td>5,492,776</td>\n",
       "      <td>1,124.23M</td>\n",
       "      <td>resnet12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ResNet-14</td>\n",
       "      <td>33.17</td>\n",
       "      <td>12.71</td>\n",
       "      <td>5,788,200</td>\n",
       "      <td>1,355.64M</td>\n",
       "      <td>resnet14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ResNet-16</td>\n",
       "      <td>30.90</td>\n",
       "      <td>11.38</td>\n",
       "      <td>6,968,872</td>\n",
       "      <td>1,586.95M</td>\n",
       "      <td>resnet16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ResNet-18 x0.25</td>\n",
       "      <td>49.50</td>\n",
       "      <td>24.83</td>\n",
       "      <td>831,096</td>\n",
       "      <td>136.64M</td>\n",
       "      <td>resnet18_wd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ResNet-18 x0.5</td>\n",
       "      <td>37.04</td>\n",
       "      <td>15.38</td>\n",
       "      <td>3,055,880</td>\n",
       "      <td>485.22M</td>\n",
       "      <td>resnet18_wd2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ResNet-18 x0.75</td>\n",
       "      <td>33.61</td>\n",
       "      <td>12.85</td>\n",
       "      <td>6,675,352</td>\n",
       "      <td>1,045.75M</td>\n",
       "      <td>resnet18_w3d4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ResNet-18</td>\n",
       "      <td>29.52</td>\n",
       "      <td>10.21</td>\n",
       "      <td>11,689,512</td>\n",
       "      <td>1,818.21M</td>\n",
       "      <td>resnet18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ResNet-34</td>\n",
       "      <td>25.66</td>\n",
       "      <td>8.18</td>\n",
       "      <td>21,797,672</td>\n",
       "      <td>3,669.16M</td>\n",
       "      <td>resnet34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ResNet-50</td>\n",
       "      <td>23.79</td>\n",
       "      <td>7.05</td>\n",
       "      <td>25,557,032</td>\n",
       "      <td>3,868.96M</td>\n",
       "      <td>resnet50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ResNet-50b</td>\n",
       "      <td>23.05</td>\n",
       "      <td>6.65</td>\n",
       "      <td>25,557,032</td>\n",
       "      <td>4,100.70M</td>\n",
       "      <td>resnet50b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ResNet-101</td>\n",
       "      <td>21.90</td>\n",
       "      <td>6.22</td>\n",
       "      <td>44,549,160</td>\n",
       "      <td>7,586.30M</td>\n",
       "      <td>resnet101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ResNet-101b</td>\n",
       "      <td>21.45</td>\n",
       "      <td>5.81</td>\n",
       "      <td>44,549,160</td>\n",
       "      <td>7,818.04M</td>\n",
       "      <td>resnet101b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ResNet-152</td>\n",
       "      <td>21.26</td>\n",
       "      <td>5.82</td>\n",
       "      <td>60,192,808</td>\n",
       "      <td>11,304.85M</td>\n",
       "      <td>resnet152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ResNet-152b</td>\n",
       "      <td>20.74</td>\n",
       "      <td>5.50</td>\n",
       "      <td>60,192,808</td>\n",
       "      <td>11,536.58M</td>\n",
       "      <td>resnet152b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>PreResNet-18</td>\n",
       "      <td>29.09</td>\n",
       "      <td>10.18</td>\n",
       "      <td>11,687,848</td>\n",
       "      <td>1,818.41M</td>\n",
       "      <td>preresnet18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>PreResNet-34</td>\n",
       "      <td>26.23</td>\n",
       "      <td>8.41</td>\n",
       "      <td>21,796,008</td>\n",
       "      <td>3,669.36M</td>\n",
       "      <td>preresnet34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PreResNet-50</td>\n",
       "      <td>23.70</td>\n",
       "      <td>6.85</td>\n",
       "      <td>25,549,480</td>\n",
       "      <td>3,869.16M</td>\n",
       "      <td>preresnet50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>PreResNet-50b</td>\n",
       "      <td>23.33</td>\n",
       "      <td>6.87</td>\n",
       "      <td>25,549,480</td>\n",
       "      <td>4,100.90M</td>\n",
       "      <td>preresnet50b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>PreResNet-101</td>\n",
       "      <td>21.74</td>\n",
       "      <td>5.91</td>\n",
       "      <td>44,541,608</td>\n",
       "      <td>7,586.50M</td>\n",
       "      <td>preresnet101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PreResNet-101b</td>\n",
       "      <td>21.95</td>\n",
       "      <td>6.03</td>\n",
       "      <td>44,541,608</td>\n",
       "      <td>7,818.24M</td>\n",
       "      <td>preresnet101b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>PreResNet-152</td>\n",
       "      <td>20.94</td>\n",
       "      <td>5.55</td>\n",
       "      <td>60,185,256</td>\n",
       "      <td>11,305.05M</td>\n",
       "      <td>preresnet152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>PreResNet-152b</td>\n",
       "      <td>21.34</td>\n",
       "      <td>5.91</td>\n",
       "      <td>60,185,256</td>\n",
       "      <td>11,536.78M</td>\n",
       "      <td>preresnet152b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>PreResNet-200b</td>\n",
       "      <td>21.33</td>\n",
       "      <td>5.88</td>\n",
       "      <td>64,666,280</td>\n",
       "      <td>15,040.27M</td>\n",
       "      <td>preresnet200b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ResNeXt-101 (32x4d)</td>\n",
       "      <td>21.81</td>\n",
       "      <td>6.11</td>\n",
       "      <td>44,177,704</td>\n",
       "      <td>7,991.62M</td>\n",
       "      <td>resnext101_32x4d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ResNeXt-101 (64x4d)</td>\n",
       "      <td>21.04</td>\n",
       "      <td>5.75</td>\n",
       "      <td>83,455,272</td>\n",
       "      <td>15,491.88M</td>\n",
       "      <td>resnext101_64x4d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>SE-ResNet-50</td>\n",
       "      <td>22.47</td>\n",
       "      <td>6.40</td>\n",
       "      <td>28,088,024</td>\n",
       "      <td>3,877.01M</td>\n",
       "      <td>seresnet50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SE-ResNet-101</td>\n",
       "      <td>21.88</td>\n",
       "      <td>5.89</td>\n",
       "      <td>49,326,872</td>\n",
       "      <td>7,600.01M</td>\n",
       "      <td>seresnet101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>SE-ResNet-152</td>\n",
       "      <td>21.48</td>\n",
       "      <td>5.76</td>\n",
       "      <td>66,821,848</td>\n",
       "      <td>11,324.62M</td>\n",
       "      <td>seresnet152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>SE-ResNeXt-50 (32x4d)</td>\n",
       "      <td>21.00</td>\n",
       "      <td>5.54</td>\n",
       "      <td>27,559,896</td>\n",
       "      <td>4,253.33M</td>\n",
       "      <td>seresnext50_32x4d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>CondenseNet-74 (C=G=8)</td>\n",
       "      <td>28.93</td>\n",
       "      <td>10.06</td>\n",
       "      <td>2,935,416</td>\n",
       "      <td>278.55M</td>\n",
       "      <td>condensenet74_c8_g8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>DPN-68</td>\n",
       "      <td>24.17</td>\n",
       "      <td>7.27</td>\n",
       "      <td>12,611,602</td>\n",
       "      <td>2,338.71M</td>\n",
       "      <td>dpn68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>DPN-98</td>\n",
       "      <td>20.81</td>\n",
       "      <td>5.53</td>\n",
       "      <td>61,570,728</td>\n",
       "      <td>11,702.80M</td>\n",
       "      <td>dpn98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>DPN-131</td>\n",
       "      <td>20.54</td>\n",
       "      <td>5.48</td>\n",
       "      <td>79,254,504</td>\n",
       "      <td>16,056.22M</td>\n",
       "      <td>dpn131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>DarkNet Tiny</td>\n",
       "      <td>43.65</td>\n",
       "      <td>19.80</td>\n",
       "      <td>1,042,104</td>\n",
       "      <td>496.34M</td>\n",
       "      <td>darknet_tiny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>DarkNet Ref</td>\n",
       "      <td>38.58</td>\n",
       "      <td>17.18</td>\n",
       "      <td>7,319,416</td>\n",
       "      <td>365.55M</td>\n",
       "      <td>darknet_ref</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>SqueezeNet v1.0</td>\n",
       "      <td>41.31</td>\n",
       "      <td>19.32</td>\n",
       "      <td>1,248,424</td>\n",
       "      <td>828.30M</td>\n",
       "      <td>squeezenet_v1_0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>SqueezeNet v1.1</td>\n",
       "      <td>41.82</td>\n",
       "      <td>19.38</td>\n",
       "      <td>1,235,496</td>\n",
       "      <td>354.88M</td>\n",
       "      <td>squeezenet_v1_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ShuffleNetV2 x0.5</td>\n",
       "      <td>41.48</td>\n",
       "      <td>19.02</td>\n",
       "      <td>1,366,792</td>\n",
       "      <td>42.34M</td>\n",
       "      <td>shufflenetv2_wd2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>ShuffleNetV2 x1.0</td>\n",
       "      <td>34.39</td>\n",
       "      <td>13.78</td>\n",
       "      <td>2,278,604</td>\n",
       "      <td>147.92M</td>\n",
       "      <td>shufflenetv2_w1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>ShuffleNetV2 x1.5</td>\n",
       "      <td>32.82</td>\n",
       "      <td>12.69</td>\n",
       "      <td>4,406,098</td>\n",
       "      <td>318.61M</td>\n",
       "      <td>shufflenetv2_w3d2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>108-MENet-8x1 (g=3)</td>\n",
       "      <td>43.92</td>\n",
       "      <td>20.76</td>\n",
       "      <td>654,516</td>\n",
       "      <td>40.64M</td>\n",
       "      <td>menet108_8x1_g3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>128-MENet-8x1 (g=4)</td>\n",
       "      <td>43.95</td>\n",
       "      <td>20.62</td>\n",
       "      <td>750,796</td>\n",
       "      <td>43.58M</td>\n",
       "      <td>menet128_8x1_g4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>228-MENet-12x1 (g=3)</td>\n",
       "      <td>33.57</td>\n",
       "      <td>13.28</td>\n",
       "      <td>1,806,568</td>\n",
       "      <td>148.93M</td>\n",
       "      <td>menet228_12x1_g3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>256-MENet-12x1 (g=4)</td>\n",
       "      <td>33.41</td>\n",
       "      <td>13.26</td>\n",
       "      <td>1,888,240</td>\n",
       "      <td>146.11M</td>\n",
       "      <td>menet256_12x1_g4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>348-MENet-12x1 (g=3)</td>\n",
       "      <td>30.10</td>\n",
       "      <td>10.92</td>\n",
       "      <td>3,368,128</td>\n",
       "      <td>306.31M</td>\n",
       "      <td>menet348_12x1_g3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>352-MENet-12x1 (g=8)</td>\n",
       "      <td>33.31</td>\n",
       "      <td>13.08</td>\n",
       "      <td>2,272,872</td>\n",
       "      <td>151.03M</td>\n",
       "      <td>menet352_12x1_g8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>456-MENet-24x1 (g=3)</td>\n",
       "      <td>28.40</td>\n",
       "      <td>9.93</td>\n",
       "      <td>5,304,784</td>\n",
       "      <td>560.72M</td>\n",
       "      <td>menet456_24x1_g3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>MobileNet x0.25</td>\n",
       "      <td>46.26</td>\n",
       "      <td>22.49</td>\n",
       "      <td>470,072</td>\n",
       "      <td>42.30M</td>\n",
       "      <td>mobilenet_wd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>MobileNet x0.5</td>\n",
       "      <td>36.30</td>\n",
       "      <td>15.14</td>\n",
       "      <td>1,331,592</td>\n",
       "      <td>152.04M</td>\n",
       "      <td>mobilenet_wd2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>MobileNet x0.75</td>\n",
       "      <td>33.54</td>\n",
       "      <td>12.85</td>\n",
       "      <td>2,585,560</td>\n",
       "      <td>329.22M</td>\n",
       "      <td>mobilenet_w3d4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>MobileNet x1.0</td>\n",
       "      <td>29.86</td>\n",
       "      <td>10.36</td>\n",
       "      <td>4,231,976</td>\n",
       "      <td>573.83M</td>\n",
       "      <td>mobilenet_w1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>FD-MobileNet x0.25</td>\n",
       "      <td>55.77</td>\n",
       "      <td>31.32</td>\n",
       "      <td>383,160</td>\n",
       "      <td>12.44M</td>\n",
       "      <td>fdmobilenet_wd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>FD-MobileNet x0.5</td>\n",
       "      <td>43.85</td>\n",
       "      <td>20.72</td>\n",
       "      <td>993,928</td>\n",
       "      <td>40.93M</td>\n",
       "      <td>fdmobilenet_wd2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>FD-MobileNet x1.0</td>\n",
       "      <td>34.70</td>\n",
       "      <td>14.05</td>\n",
       "      <td>2,901,288</td>\n",
       "      <td>146.08M</td>\n",
       "      <td>fdmobilenet_w1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>MobileNetV2 x0.25</td>\n",
       "      <td>49.72</td>\n",
       "      <td>25.87</td>\n",
       "      <td>1,516,392</td>\n",
       "      <td>32.22M</td>\n",
       "      <td>mobilenetv2_wd4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>MobileNetV2 x0.5</td>\n",
       "      <td>36.54</td>\n",
       "      <td>15.19</td>\n",
       "      <td>1,964,736</td>\n",
       "      <td>95.62M</td>\n",
       "      <td>mobilenetv2_wd2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>MobileNetV2 x0.75</td>\n",
       "      <td>31.89</td>\n",
       "      <td>11.76</td>\n",
       "      <td>2,627,592</td>\n",
       "      <td>191.61M</td>\n",
       "      <td>mobilenetv2_w3d4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>MobileNetV2 x1.0</td>\n",
       "      <td>29.31</td>\n",
       "      <td>10.39</td>\n",
       "      <td>3,504,960</td>\n",
       "      <td>320.19M</td>\n",
       "      <td>mobilenetv2_w1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>SNet-A-Mobile</td>\n",
       "      <td>25.68</td>\n",
       "      <td>8.16</td>\n",
       "      <td>5,289,978</td>\n",
       "      <td>587.29M</td>\n",
       "      <td>snetamobile</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     model   top1   top5      params       flops  \\\n",
       "0                ResNet-10  37.46  15.85   5,418,792     892.62M   \n",
       "1                ResNet-12  36.18  14.80   5,492,776   1,124.23M   \n",
       "2                ResNet-14  33.17  12.71   5,788,200   1,355.64M   \n",
       "3                ResNet-16  30.90  11.38   6,968,872   1,586.95M   \n",
       "4          ResNet-18 x0.25  49.50  24.83     831,096     136.64M   \n",
       "5           ResNet-18 x0.5  37.04  15.38   3,055,880     485.22M   \n",
       "6          ResNet-18 x0.75  33.61  12.85   6,675,352   1,045.75M   \n",
       "7                ResNet-18  29.52  10.21  11,689,512   1,818.21M   \n",
       "8                ResNet-34  25.66   8.18  21,797,672   3,669.16M   \n",
       "9                ResNet-50  23.79   7.05  25,557,032   3,868.96M   \n",
       "10              ResNet-50b  23.05   6.65  25,557,032   4,100.70M   \n",
       "11              ResNet-101  21.90   6.22  44,549,160   7,586.30M   \n",
       "12             ResNet-101b  21.45   5.81  44,549,160   7,818.04M   \n",
       "13              ResNet-152  21.26   5.82  60,192,808  11,304.85M   \n",
       "14             ResNet-152b  20.74   5.50  60,192,808  11,536.58M   \n",
       "15            PreResNet-18  29.09  10.18  11,687,848   1,818.41M   \n",
       "16            PreResNet-34  26.23   8.41  21,796,008   3,669.36M   \n",
       "17            PreResNet-50  23.70   6.85  25,549,480   3,869.16M   \n",
       "18           PreResNet-50b  23.33   6.87  25,549,480   4,100.90M   \n",
       "19           PreResNet-101  21.74   5.91  44,541,608   7,586.50M   \n",
       "20          PreResNet-101b  21.95   6.03  44,541,608   7,818.24M   \n",
       "21           PreResNet-152  20.94   5.55  60,185,256  11,305.05M   \n",
       "22          PreResNet-152b  21.34   5.91  60,185,256  11,536.78M   \n",
       "23          PreResNet-200b  21.33   5.88  64,666,280  15,040.27M   \n",
       "24     ResNeXt-101 (32x4d)  21.81   6.11  44,177,704   7,991.62M   \n",
       "25     ResNeXt-101 (64x4d)  21.04   5.75  83,455,272  15,491.88M   \n",
       "26            SE-ResNet-50  22.47   6.40  28,088,024   3,877.01M   \n",
       "27           SE-ResNet-101  21.88   5.89  49,326,872   7,600.01M   \n",
       "28           SE-ResNet-152  21.48   5.76  66,821,848  11,324.62M   \n",
       "29   SE-ResNeXt-50 (32x4d)  21.00   5.54  27,559,896   4,253.33M   \n",
       "..                     ...    ...    ...         ...         ...   \n",
       "37  CondenseNet-74 (C=G=8)  28.93  10.06   2,935,416     278.55M   \n",
       "38                  DPN-68  24.17   7.27  12,611,602   2,338.71M   \n",
       "39                  DPN-98  20.81   5.53  61,570,728  11,702.80M   \n",
       "40                 DPN-131  20.54   5.48  79,254,504  16,056.22M   \n",
       "41            DarkNet Tiny  43.65  19.80   1,042,104     496.34M   \n",
       "42             DarkNet Ref  38.58  17.18   7,319,416     365.55M   \n",
       "43         SqueezeNet v1.0  41.31  19.32   1,248,424     828.30M   \n",
       "44         SqueezeNet v1.1  41.82  19.38   1,235,496     354.88M   \n",
       "45       ShuffleNetV2 x0.5  41.48  19.02   1,366,792      42.34M   \n",
       "46       ShuffleNetV2 x1.0  34.39  13.78   2,278,604     147.92M   \n",
       "47       ShuffleNetV2 x1.5  32.82  12.69   4,406,098     318.61M   \n",
       "48     108-MENet-8x1 (g=3)  43.92  20.76     654,516      40.64M   \n",
       "49     128-MENet-8x1 (g=4)  43.95  20.62     750,796      43.58M   \n",
       "50    228-MENet-12x1 (g=3)  33.57  13.28   1,806,568     148.93M   \n",
       "51    256-MENet-12x1 (g=4)  33.41  13.26   1,888,240     146.11M   \n",
       "52    348-MENet-12x1 (g=3)  30.10  10.92   3,368,128     306.31M   \n",
       "53    352-MENet-12x1 (g=8)  33.31  13.08   2,272,872     151.03M   \n",
       "54    456-MENet-24x1 (g=3)  28.40   9.93   5,304,784     560.72M   \n",
       "55         MobileNet x0.25  46.26  22.49     470,072      42.30M   \n",
       "56          MobileNet x0.5  36.30  15.14   1,331,592     152.04M   \n",
       "57         MobileNet x0.75  33.54  12.85   2,585,560     329.22M   \n",
       "58          MobileNet x1.0  29.86  10.36   4,231,976     573.83M   \n",
       "59      FD-MobileNet x0.25  55.77  31.32     383,160      12.44M   \n",
       "60       FD-MobileNet x0.5  43.85  20.72     993,928      40.93M   \n",
       "61       FD-MobileNet x1.0  34.70  14.05   2,901,288     146.08M   \n",
       "62       MobileNetV2 x0.25  49.72  25.87   1,516,392      32.22M   \n",
       "63        MobileNetV2 x0.5  36.54  15.19   1,964,736      95.62M   \n",
       "64       MobileNetV2 x0.75  31.89  11.76   2,627,592     191.61M   \n",
       "65        MobileNetV2 x1.0  29.31  10.39   3,504,960     320.19M   \n",
       "66           SNet-A-Mobile  25.68   8.16   5,289,978     587.29M   \n",
       "\n",
       "              fixedname  \n",
       "0              resnet10  \n",
       "1              resnet12  \n",
       "2              resnet14  \n",
       "3              resnet16  \n",
       "4          resnet18_wd4  \n",
       "5          resnet18_wd2  \n",
       "6         resnet18_w3d4  \n",
       "7              resnet18  \n",
       "8              resnet34  \n",
       "9              resnet50  \n",
       "10            resnet50b  \n",
       "11            resnet101  \n",
       "12           resnet101b  \n",
       "13            resnet152  \n",
       "14           resnet152b  \n",
       "15          preresnet18  \n",
       "16          preresnet34  \n",
       "17          preresnet50  \n",
       "18         preresnet50b  \n",
       "19         preresnet101  \n",
       "20        preresnet101b  \n",
       "21         preresnet152  \n",
       "22        preresnet152b  \n",
       "23        preresnet200b  \n",
       "24     resnext101_32x4d  \n",
       "25     resnext101_64x4d  \n",
       "26           seresnet50  \n",
       "27          seresnet101  \n",
       "28          seresnet152  \n",
       "29    seresnext50_32x4d  \n",
       "..                  ...  \n",
       "37  condensenet74_c8_g8  \n",
       "38                dpn68  \n",
       "39                dpn98  \n",
       "40               dpn131  \n",
       "41         darknet_tiny  \n",
       "42          darknet_ref  \n",
       "43      squeezenet_v1_0  \n",
       "44      squeezenet_v1_1  \n",
       "45     shufflenetv2_wd2  \n",
       "46      shufflenetv2_w1  \n",
       "47    shufflenetv2_w3d2  \n",
       "48      menet108_8x1_g3  \n",
       "49      menet128_8x1_g4  \n",
       "50     menet228_12x1_g3  \n",
       "51     menet256_12x1_g4  \n",
       "52     menet348_12x1_g3  \n",
       "53     menet352_12x1_g8  \n",
       "54     menet456_24x1_g3  \n",
       "55        mobilenet_wd4  \n",
       "56        mobilenet_wd2  \n",
       "57       mobilenet_w3d4  \n",
       "58         mobilenet_w1  \n",
       "59      fdmobilenet_wd4  \n",
       "60      fdmobilenet_wd2  \n",
       "61       fdmobilenet_w1  \n",
       "62      mobilenetv2_wd4  \n",
       "63      mobilenetv2_wd2  \n",
       "64     mobilenetv2_w3d4  \n",
       "65       mobilenetv2_w1  \n",
       "66          snetamobile  \n",
       "\n",
       "[67 rows x 6 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "osmr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_model_weighted_alphas(model):\n",
    "    try:\n",
    "        w_alphas = []\n",
    "\n",
    "        for W in tqdm(iter_pytorch_layers(model)):\n",
    "            M, N = np.min(W.shape), np.max(W.shape)\n",
    "            \n",
    "            # we do NOT normalize by N here...\n",
    "            # probably should uses tructaed ZSVD for speed\n",
    "            #X=np.dot(W.T,W)#/N\n",
    "            #evals = np.linalg.eigvals(X)\n",
    "            \n",
    "            # orders of magnitude faster, even if we are missing very small 1 SV\n",
    "            svd = TruncatedSVD(n_components=M-1, n_iter=7, random_state=42)\n",
    "            svd.fit(W) \n",
    "            sv = svd.singular_values_\n",
    "            evals = sv*sv\n",
    "\n",
    "            l_max, l_min = np.max(evals), np.min(evals)\n",
    "        \n",
    "            fit = powerlaw.Fit(evals, xmax=l_max, verbose=False)\n",
    "            w_alphas.append(fit.alpha*np.log10(l_max))\n",
    "            \n",
    "\n",
    "    except Exception as e: \n",
    "\n",
    "        print(\"skipping \", fixedname)\n",
    "        print(e)\n",
    "\n",
    "        pass\n",
    "    \n",
    "    return w_alphas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick check the model loads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9dde4183f931472185df13c5d42bce17",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(64, 64)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#model = ptcv_get_model('resnet50', pretrained=True)\n",
    "fixedname=\"resnet10\"\n",
    "model = ptcv_get_model(fixedname, pretrained=True)\n",
    "for W in tqdm(iter_pytorch_layers(model)):\n",
    "    print(W.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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</th>\n",
       "      <th>fixedname</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ResNet-10</td>\n",
       "      <td>37.46</td>\n",
       "      <td>15.85</td>\n",
       "      <td>5,418,792</td>\n",
       "      <td>892.62M</td>\n",
       "      <td>resnet10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       model   top1   top5     params    flops fixedname\n",
       "0  ResNet-10  37.46  15.85  5,418,792  892.62M  resnet10"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "osmr.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "resnet10\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7192f879e9ff468fac667286acb162cb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/charleshmartin/anaconda3/lib/python3.6/site-packages/powerlaw.py:700: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  (Theoretical_CDF * (1 - Theoretical_CDF))\n",
      "/Users/charleshmartin/anaconda3/lib/python3.6/site-packages/powerlaw.py:700: RuntimeWarning: invalid value encountered in true_divide\n",
      "  (Theoretical_CDF * (1 - Theoretical_CDF))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "resnet12\n"
     ]
    },
    {
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "resnet14\n"
     ]
    },
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "resnet16\n"
     ]
    },
    {
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       "model_id": "5e5d490c662442fc8ea60b20aabf1cdd",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "resnet18_wd4\n"
     ]
    },
    {
     "data": {
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "resnet18_wd2\n"
     ]
    },
    {
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      "Pretrained model for darknet_ref is not available.\n",
      "squeezenet_v1_0\n"
     ]
    },
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "squeezenet_v1_1\n"
     ]
    },
    {
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "shufflenetv2_wd2\n"
     ]
    },
    {
     "data": {
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       "model_id": "84b4b1f0dc5a47bb8bc110aea411427e",
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       "version_minor": 0
      },
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "shufflenetv2_w1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a57ef1f823c4e8c855b9191bd0520c8",
       "version_major": 2,
       "version_minor": 0
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "shufflenetv2_w3d2\n",
      "Pretrained model for shufflenetv2_w3d2 is not available.\n",
      "menet108_8x1_g3\n"
     ]
    },
    {
     "data": {
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       "model_id": "b513a574eceb4a6f83713ca4812cad5c",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet128_8x1_g4\n"
     ]
    },
    {
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       "model_id": "c6e1d9e10c8f40bb9e6831b574f177ed",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet228_12x1_g3\n"
     ]
    },
    {
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       "model_id": "6fb3b75cfe4b464586e4c6e0b5090e46",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet256_12x1_g4\n"
     ]
    },
    {
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       "model_id": "ab11d0049ad549b181aeec8dd2629427",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet348_12x1_g3\n"
     ]
    },
    {
     "data": {
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       "model_id": "a51c52597ae844229d4a96fec223c729",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet352_12x1_g8\n"
     ]
    },
    {
     "data": {
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       "model_id": "f1720616b1e7413690a4385e9dfb2f55",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "menet456_24x1_g3\n"
     ]
    },
    {
     "data": {
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       "model_id": "ec1c1b618e2e4bf985977a8c1eca59ce",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenet_wd4\n"
     ]
    },
    {
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       "model_id": "2ac21b4dcc4e4399bcedc6284b695892",
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenet_wd2\n"
     ]
    },
    {
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       "model_id": "a6c59157772746b6958f6ded22e718cf",
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenet_w3d4\n"
     ]
    },
    {
     "data": {
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       "model_id": "503e04dc3dbc462eb46446d431bb1198",
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenet_w1\n"
     ]
    },
    {
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       "model_id": "20a34bc78ffd4bd69733e5456750aa26",
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "fdmobilenet_wd4\n"
     ]
    },
    {
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       "model_id": "8e9206ea1b2d42a1bd1d704b50d2c2f6",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "fdmobilenet_wd2\n"
     ]
    },
    {
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       "model_id": "6cd0eb24538f4f59b860e56ffa65fc1f",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "fdmobilenet_w1\n"
     ]
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenetv2_wd4\n"
     ]
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       "model_id": "6be907b58cd54e3c88f3a79ac54491e1",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenetv2_wd2\n"
     ]
    },
    {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenetv2_w3d4\n"
     ]
    },
    {
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       "model_id": "86618cad79e24835b21663dd85ff3600",
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mobilenetv2_w1\n"
     ]
    },
    {
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       "model_id": "da1f6faa55b249d2a2a363b0e8248d44",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "snetamobile\n",
      "Unsupported model: snetamobile\n"
     ]
    }
   ],
   "source": [
    "\n",
    "alphas_4model = {}\n",
    "for fixedname in osmr['fixedname'].values:\n",
    "    print(fixedname)\n",
    "    try:\n",
    "        model = ptcv_get_model(fixedname, pretrained=True)\n",
    "        alphas_4model[fixedname]=calc_model_weighted_alphas(model)\n",
    "\n",
    "\n",
    "    except Exception as e:\n",
    "        print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-16T00:27:41.987680Z",
     "start_time": "2018-10-16T00:27:41.727075Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_top_errors(title, fixednames=None, lognorm=True, tops=[\"top1\"], small=True):\n",
    "    \n",
    "    if small:\n",
    "        plt.rcParams['figure.figsize'] = [10,10]\n",
    "        matplotlib.rcParams.update({'font.size': 24})\n",
    "        legend_prop={'size':20}\n",
    "        marker_size = 75\n",
    "    else:\n",
    "        plt.rcParams['figure.figsize'] = [12,12]\n",
    "        matplotlib.rcParams.update({'font.size': 26})\n",
    "        legend_prop={'size':20}\n",
    "        marker_size = 75\n",
    "\n",
    "    for top in tops:\n",
    "        \n",
    "        if fixednames is None:\n",
    "            fixednames = []\n",
    "            startstr = title.lower()\n",
    "\n",
    "            for fname in alphas_4model:\n",
    "                if fname.startswith(startstr):\n",
    "                    fixednames.append(fname)\n",
    "        \n",
    "        for fname in fixednames:\n",
    "                try:\n",
    "                    top1 = osmr[osmr['fixedname']==fname][top].values[0]\n",
    "                    avga = np.average(alphas_4model[fname])\n",
    "                    \n",
    "                    plt.scatter(100.0-top1, avga, label=\"ln \"+fname, s=marker_size)\n",
    "\n",
    "                except:\n",
    "                    pass\n",
    "\n",
    "\n",
    "        plt.ylabel(\"{} Test Acuracy\".format(top))\n",
    "        #if lognorm:\n",
    "        plt.title(r\"Test Accuracy vs Universal metric $\\hat{\\alpha}$\"+\"\\n Pretrained {} Models\".format(title))\n",
    "        plt.ylabel(r'$\\hat{\\alpha}$')\n",
    "        #else:\n",
    "        #    plt.title(r\"Top 1 Test Error vs  Average Log  $\\alpha$\"+\"\\n Pretrained {} Models\".format(title))\n",
    "        #    plt.ylabel(r'$\\langle\\alpha\\rangle$')         \n",
    "    \n",
    "        plt.xlabel(\"{} Test Accuracy\".format(top))\n",
    "        #plt.gca().invert_xaxis()\n",
    "        plt.legend(prop=legend_prop)\n",
    "        plt.savefig(\"img/{}-w_alphas.png\".format(title))\n",
    "        plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& menet108\\_8x1\\_g3 & 43.92 & 5.307786842604698 \\\\\n",
      "& menet128\\_8x1\\_g4 & 43.95 & 4.464094203976507 \\\\\n",
      "& menet228\\_12x1\\_g3 & 33.57 & 4.818039195899305 \\\\\n",
      "& menet256\\_12x1\\_g4 & 33.41 & 4.97245827992455 \\\\\n",
      "& menet348\\_12x1\\_g3 & 30.1 & 5.735710334688667 \\\\\n",
      "& menet352\\_12x1\\_g8 & 33.31 & 4.420778709486468 \\\\\n",
      "& menet456\\_24x1\\_g3 & 28.4 & 5.106762640815178 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(title=\"MeNet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& resnet10 & 37.46 & 1.9442508762307031 \\\\\n",
      "& resnet12 & 36.18 & 0.7435730322077716 \\\\\n",
      "& resnet14 & 33.17 & 1.6989137427028054 \\\\\n",
      "& resnet16 & 30.9 & 1.4948560192525948 \\\\\n",
      "& resnet18\\_wd4 & 49.5 & 1.8316095061540871 \\\\\n",
      "& resnet18\\_wd2 & 37.04 & 1.8209534054298246 \\\\\n",
      "& resnet18\\_w3d4 & 33.61 & 0.275197055094145 \\\\\n",
      "& resnet18 & 29.52 & 1.0931776919464014 \\\\\n",
      "& resnet34 & 25.66 & -0.4167435565963109 \\\\\n",
      "& resnet50 & 23.79 & 0.12973522748591812 \\\\\n",
      "& resnet50b & 23.05 & 0.0914701378854356 \\\\\n",
      "& resnet101 & 21.9 & -0.6653172308894714 \\\\\n",
      "& resnet101b & 21.45 & -0.9206956482884197 \\\\\n",
      "& resnet152 & 21.26 & -1.107269622195169 \\\\\n",
      "& resnet152b & 20.74 & -1.7448372455844239 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = [10,10]\n",
    "plot_top_errors(\"ResNet\", small=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DPN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& dpn68 & 24.17 & 0.5671198123331914 \\\\\n",
      "& dpn98 & 20.81 & 0.10859653346304365 \\\\\n",
      "& dpn131 & 20.54 & -0.12574033092620057 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"DPN\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DenseNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& densenet121 & 25.57 & 1.248707987388755 \\\\\n",
      "& densenet161 & 22.86 & 0.838195490601221 \\\\\n",
      "& densenet169 & 24.4 & 0.6786168956124697 \\\\\n",
      "& densenet201 & 23.1 & 0.5016681704643254 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"DenseNet\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SeResNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& seresnet50 & 22.47 & -0.3455397203741907 \\\\\n",
      "& seresnet101 & 21.88 & -1.2371383409404113 \\\\\n",
      "& seresnet152 & 21.48 & -1.5342404162449716 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"SeResNet\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SeResNeXt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& seresnext50\\_32x4d & 21.0 & 1.8067620396913677 \\\\\n",
      "& seresnext101\\_32x4d & 19.96 & 0.7584031176832214 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"SeResNeXt\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& shufflenetv2\\_wd2 & 41.48 & 5.1152540755298626 \\\\\n",
      "& shufflenetv2\\_w1 & 34.39 & 2.863452304186872 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"ShuffleNet\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Counterexamples\n",
    "\n",
    "- All 3 MobileNet models, which we may be interpreting incorrectly\n",
    "\n",
    "- CondenseNet\n",
    "\n",
    "- SqueezeNet, which different from the Pytorch defaults *(the numbers may be off)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& mobilenet\\_wd4 & 46.26 & 5.543606824677111 \\\\\n",
      "& mobilenet\\_wd2 & 36.3 & 4.264810441406522 \\\\\n",
      "& mobilenet\\_w3d4 & 33.54 & 4.414959019154964 \\\\\n",
      "& mobilenet\\_w1 & 29.86 & 4.187408623053394 \\\\\n",
      "& mobilenetv2\\_wd4 & 49.72 & 12.120189843242203 \\\\\n",
      "& mobilenetv2\\_wd2 & 36.54 & 4.6901238612722125 \\\\\n",
      "& mobilenetv2\\_w3d4 & 31.89 & 4.205522477526878 \\\\\n",
      "& mobilenetv2\\_w1 & 29.31 & 3.5007829318466968 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"MobileNet\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& fdmobilenet\\_wd4 & 55.77 & 6.403295564078693 \\\\\n",
      "& fdmobilenet\\_wd2 & 43.85 & 7.01239491498429 \\\\\n",
      "& fdmobilenet\\_w1 & 34.7 & 7.1034958239729695 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"FDMobileNet\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  CondenseNet is an outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& condensenet74\\_c4\\_g4 & 26.25 & -1.832024790934699 \\\\\n",
      "& condensenet74\\_c8\\_g8 & 28.93 & -1.6294419980779795 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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4E+5ygu/PGQsbKRh1uC1wZbiT5rnAW2HiiffevUzATqEog90Sy+03EzJlwMUZHXPvq4WI3EiBYfGPYHs5JqAdRKJbHgUrs5OALL/64OhTFjvdwh2Nf+NM2F821vx1GE2c/VW0xFmuiWpHpZHRJKasEvl8iJZE9l9+eHf3KLQVoNiFGn/DHn3tUkZEimsKQ2yYM+CkBL1K/0WUJ2w5YX7vCXMCuyr2JuzrxiuAHthjAz/FdsRvBYQf7bgvxk7O74UdIbwSu6J4EgWnx+wDageEr4w9ds9gz/e+BbsYoqlz1Yni/r924skFakYR7mZPHjzp4+893/swdsP2bthjIdtgR2zfw/6TLnK+dQLCT/KE/9Ipn8uwp/88h12I8y2w25FZ4BNH/2jqBnaRhSu/HDt3rxV2g/nHsCOAJ7HGtSuXkeh7D4hrpicug91SqTjaUVNPGvs931uGCBNXO4hCt2QKTjcyWGPpYexK9hZO+dwPrPLIfBcsb6OpF9itrgyQ7eOX6Ymnf6Lz1xM2rv4qhnuOq1xJQDuKJm9D3EdE9xxpWkCGR250MZZVxM+HaMo10nslgf2XT9wNKThdzGCN1TbY+f0feNyf9Xyfhl0gGPHzrTivEldAr7PjIgbj1Qk3xNNBhLvGBYQdHWG4nUDbIOmPChEuK8J7aOUJMyfKfKvkuf8ix1I6Mo9jjeJw9xnMSIg5PPYEqf+FCLMRe854NokzXutgN6UPluYJ7Hn13vLPSPS9B8TTM0B+cDG2pS8D0vomjHzc7SAK3aph5wFHkt5nQN0QcUVcL0iQ8RpL/gaEjbm/iuGe4yrXRLSjaPM2nnKONC0iMF4TUVZOHKNChMmKpVyjvNeE9F8h4g4W3ynsH9NyFPTt7nV3LPUg0ZdOG1BKFGPMq0AD7MKDediO+AT23+Q27CbN/w+42hjz/wUEfxb7T/RZYBF2JOgotrHvduJ7EGhs7MEAfuk/gV288RGwi4LX5NHgPWjgvaBS/ukfw47qAdSj4HQYr8yT2H/6z2PnHh7A5tFW4AvgaeByY+dK+aURc3hj55C1xW6T8jV2ju4R7OjaH4DLjDEbAsPFgzFmB3Z05AlPmsewhvKrwBXGmFeCx1AorrjyzsN/sPUD7ChIqJOC4iVwr9FwC7XibgeRYozZb4y5HrsF0yvY8tmPXcxxEDsKnwX0MMa0NcZsCxZXCRJt/uYTZ38VLXGVayLbUWkkEWWVoOdDzCSw/woWdy/s1LXd2FH4o8AyoI8x5lljpwv1wP4RdXefWR7PPSUKcSxwRVEUJQhij47cjJ3v+qox5p4SVklRFOVni468KoqihGcQBf3l+JJURFEU5eeOjrwqiqKEQERSsK9aawKLjTFtSlglRVGUnzV6wpaiKEoAzrYwFYHzsHN73T00nywxpRRFURRAR14VRVGKICILgI4Bzu8Ye6qRoiiKUoLoyKuiKEpwjmNXeWcBL5asKoqiKAroyKuiKIqiKIpSitDdBhRFURRFUZRSgxqviqIoiqIoSqlBjVdFURRFURSl1KDGq6IoiqIoilJqUONVURRFURRFKTWo8aooiqIoiqKUGtR4VRRFURRFUUoNarwqipKPiGSIiHGu0SWtTyIRkdGee8soaX1KOyKS7eTlgpLWRVFOByKS6elD+hdjOtpXhUGNV6XU4WnUgVeeiOwTkeUi8jcRubykdVXOfkTkGhH5i4h8JSI7RCRHRA47xt0MEXlQRM4raT2Vksdj8BsROSUil0UQZq4b5nTomEh8+uh7IgzXzCdsu+LWVyk9qPGqnE2UBaoBlwH/H7BMRF4UESlZtSyn61+7cnoQkXYisgz4CBgGXA6cA5QHqgANgOuB54HNIvKWGrGKBwH+VNJKuIjIAqdvyi7GZAYkWE75mVKupBVQlDjYDlzr+V0WOBfoAwzC/jl7ADgAjDrt2pVCjDHZ2IeqEgIRGQyMA5IcpzXAv4Avgd2Oex2gI7Y+1gNuB5YBfz3d+ipnLNeKSKYxZkFJK1LM/ARUBK4SkWbGmLXBBEWkLHBnQDhFKYSOvCqlmVxjzGrP9T9jzH+MMfcAt3rkHhaR6iWlpHJ2ISLXA+OxBuoJ4B7gYmPMKGPMB8aYpcaYz40xU40xDwAXAPcC+0pOa+UM4yCQ63w/Y0Zfi5ElwA7ne/8wst2xbzAAphWXQkrpRo1X5azEGPMe8LnzswLQqQTVUc4SRCQdeAM7Om2AG40xrxpjTgULY4zJNcaMx04r+Pr0aKqc4fwIvOp8v1pE+pSkMqeBk8Cbzvc7ndHVYLhTBj4FNhSrVkqpRY1X5Wxmsed7htcjcKW0s8r+BRFZIyKHHL8iDxQRKS8ig0XkAxHZ5izO2e8sEvuTiNTxCZPhLLaY73Ge5LMgYUE8OopIkoh0dmSWiMheEckVkYMi8rWIjBOR5qEyLNxuA37+InKJiEx09D0uIj+KyIcicl2otALi7S4ib4rIdyJy1LnWi8hrkSxqceJoIyLvish2p1y2iMgUEekYqR4RMBRIdb6/boyZFWlAY8xmY8wnwfxFpJuI/ENENovIT04ZfyMiY0Wkcai4A+crikgVERkpIiuceI6IyP9E5HERqRJOVxEpJyL3icjnInLACb9GRJ4WkdqR3rMTV9RtxhO2yDxxEWkvIu+JyFYnrp0i8m8RaRuBLt1E5J9OPTvm1NetTj5NFJFbRaRyiPBlROQWEflXQDmtdsqpYRRZ8yRw1Pn+/yS0QRcRItLc0eNrJ49znPubKiJ9RIrO/xeRLLH9k9tOGkjRvsmISGac6k1yPutQeLqXV5d04LoA+YiIp/144qgnIi+JyEanbux22lZ/v7wLE1cDp70sE9sXnxC7oHO2iPQTkbimbTrxPyt2oegBsX39jyKy1mlrD0ZZH0sXxhi99CpVF3bEywDZYeSe9sg+EuCX7bgvAHpgX+OZgKtPQJgWwHc+ct7rCHY0zhsuI0wY91oQj47A9AjSOAk8HCLPvLqODuePnVucEyK9J8OUUXXsgqdwev8JkBDxPAacChL2FPB7R1/XLSPGurfDE0fTBNXnShGUXW6YclvgyGVjpymsDxHX/4BqIeKqhn3NGyz8DuyiyPz6GSKumNqMJ3ymR64/du56qHIeHCSeMtiRv0jaYbsgcTQAvoqgnH4bIj/cPNvo/H7SE3ZAkDBzXZkQ8ZbBLgw8GUa/D4HUgLBZEeZLZgx12w071/n9hfN7ShD5oZ46UZXCbTZYucTdfpx4rgUOh4hjFnCNtz6GiOtBQveLBjv/vW6Q8N77LtJXAb2BYxGU2WuJ6KPOxKvEFdBLr2gvT8PMDiP3H4/sHQF+7kNkE3AI2A/8AegAXAn0A1p45C/2dGw/AX8DfgW0AtoBj1Bg2OQBnTxhk4CLsK/DXH1+77h5r1/EqeMs7Gu2F4BfA62xr6qvB8ZgX1W66f8qSJ5leGRGh/H/DPuwXIOd03mVcz3i6OvKdQySVhVgtUduJnAX0N65v7uB5R7/PwSJZ5BH5jC242/nlM19wGbH70uPXEYM9a6ZJ/z6BNVlCain3wKDHd3bO/fizcv/CxLPAsd/N7AOO6L3HNDFqQM3Yx+WbjwTg8RTBvivR24FdvFMS6AzMBZrCGxy0jIEMV6Jo8144sj06LLI+fzCqSdXAm2Bp7Bzjw1wHGjkE89vPPGswS7k7Iw1rttiDePXnHsqYiRhF4Ju9+j6JnAbto1dDfwW2/bcNO4KkifZFDZeUyhol5uBZJ8wkRivWZ60V2Lr/TVO2d8A/Nvj/zFQxhO2Lrb/Wer4b6No33QRUDmOvto1Xu/xlFN1H/mVjv9k5/doTxx+5ZKo9nMRto4a7J+giVhjtiVwi6fuef/U9Q8Sl1fn74DfYefxXg70dOJ2/2R87ZevhDBegVoUtKuj2AWgPYErsG2iN7a/X44ar3rpdeZcnkadHUKmlaeDOAmcF+Cf7YlnJ3BBiLjKYh94budYL4hcLcffYA2IMgH+meE6vlh1dOSLPLQD/NOAVU58GwL1c2QyPGmODuNvsCM5FXzkOntkpgbRZ7ynAy5iuDgy5YD3KBg9yQjwr07Bw+kgcIlPHNWBbwL0zvBLL0z+3eYJ/06C6rL3D80ioJKPzIXAXkcmx093CoxXNx8u9ZGpBKz1xFPDR8b7R2AOkOQj04PCI3wLTlObMdgHv1+9vdsj84KPv2uQbwaqhiiPZKCKj/scJ/wu7OI8v7CVsfM0DXZxXpF0CDBeHbcHPboXMa4IY7xiF6e64R8myBsKCkY1DXB7iDqUnYi67cQZaLymUjBi+NsA2cs88pmO22iPm5/xmqj286knnn4+/gK8HVAX+/vItaXgzcBYoFyQfLnBI/d7H3/vfWcE+Hnreu8w+V+kjZ8tV4kroJde0V6ehpsd4F4GOA87CnLAI5flE0e2x9/3dZ1H9lce2TZhZK/zyHYK8MsM1fHFo2MUedfbE2cLH/8Mj//oMP4/AbVDpOWOdP7o43ceBaNlj4bRuQYFr+CeCPAb5tHnwRBxtA148GTEkHcPeML/JUHl8T8nvhOhdMKOJrlpP+fjv8DjPzREPPd55Hr5+LsjX8cJ8krTkZvgiWfBaWozO/D5o+TIlaFgFPcrH393GsW/YyijVh4dbgsje1GoNou/8VoB+MFx30OA0Ut449X9k/BRBPfijq4uDFGHshNRt504Cxmvjts7jtuyANmxjvsmHAOc8MZr3O0HO/ru+s0MEYd3lDyY8Trb8VsDlA2TN/9yZDf7+HnvOyPA71GPX0qiyqq0XbpgSynNFFpYgB0N2gK8RMGimgXYAwuCkQu8Gyadvs7nD8aYz0NK2vRcwi4giZBIdCyCiKSJyC+cRRwXichFFGzPA3akIx7mGmN2hfD/0vmsISKpAX7XUbBH6j9CJWKM2UvBKv3APHUXfpzCvjoNFsdn2FHHeKjq+X4kzrhwFj5d4vz8yNg9doPxpifNrmGifjuE35ee7+f76HOp8/NDY8y2EPFMCKNDcbSZfxljjvt5GLvbw1fOz/N9RNx76SgijcLoE4h7L7nA1FCCxpjV2FE+iLD9O/c02vmZDjwUqWIi0hQ7nQXCtCOHhc7n1YlYIBYjk5zPliJyMdhFfdg3G2AHG0y4SBLYfryLx14PFoEx5hD2LVAwfapgp2qAndN7MoQ+UFDv60t0h5d42+WgKMKdVajxqpyN5GBfA90NdDHGHA0hu94YcyxMfK2cz/pBVuF6DejDnnBBV1FHSSQ6AiAil4nIJBHZjp0juwk7r/Rr5/rAI54ep17hjEHvvqYpAX6tPN83RZCvLR3ZwDx1H14bHSM3FEvC+IfDW7ZhV+xHwCWe74uDSpFv4Cx3fl4UwvDYY4z5MURUocrEq0+4vFpB4T9CgRRHm4m0vgXeFxQYJdWBr8XuQjFIRC4UkXDPQfdekoDjEdxPjQjuJZDJFNzf70SkVoThvO1oYgS6PejIlsfmRUnwCXaQAQr2fO2NzTeDzYtISFT7iabeh/K/nIKDn/4QQVm85AkbTV2ZQcEfpBec3QweE5GOEmKnjLMNNV6V0sx27KIQ97oQe5JRVWNMe2PMJBNi/02H/RGkE+mDJJBKMYYLJBIdEZGHsIty+hNZZxivfuEMam/eBxpbicpT11DYHUHYnTGm6eI1CqPaLioINTzfI9HN3eS9DHb+sh/xlIlXn5D5aYzJpeAB6kdxtJlI763Ic80Y8xb2detx7LzWm7Cjx98APzrGbK8g2yEVe/t3Rukec35W8XwPR6y6QeL6p6hw+uQ3nJ93OFtGuXu7zjPGbI4wqkS1n4jrfZh0TktZGGMOYBeAbXScWmJ3rVgAHBCRxSLykIgE6yPOCvR4WKU0k+u8pouHcK92oKCdLCO6M7cjMjojIKyOItIBu7ocrJH1AjAP+B44aIw54cidj10BCyV7DKybp6ewIxaRlAPYuW1+hH3NSPz3u9zz/Yo44wokEv3jkY+WePOzpNtMEYwxfxKRSdjV452BNti3D9WwxuxNwEIR6eMYCC7uvewg/JQNL6He+Pjp928R+RI7mnqPiPw5zKtwr25g3zQtjSLJ7dHol2CysDuu1MK++nbzdVKwAGE4Xe0nkjoP8Dh2+65I+T4aJYwxS0WkGXaXgeuwU1SaOjovtNhAAAAgAElEQVRc7VwjReQWY8zcaOIuLajxqijh2YNdYFQnAcZycXGv83kSu1L3myBy1U6TPuHY43yWAY4aYzaGEg7BXuw2RpGMhMYzMoIxZp2I7MCOajcSkabGmHVxROkduYxkpNyVOYXdUSDRePUJmZ/OaFmounRGthljzE7gRefCMQB6YBeynY/dqP9lCh8vvQdoAtTETk/xnXebIEZg/3SWx253dFcY+T2e72XPpLwOhTFmo4h8it0y7S/YtwCHsFt6RUqi2o83nloUjND6EaoP8ZZFheIuC2NMHnYKwQwAEamBPUmyP9aorQ78W0TODzOVqFSi0wYUJTzuQpC6zqKnWCnO0bKLnc9VIQxXsPsAngl85fneLY54VjmfDUUk3By+q+JIx+U1z/cHg0pFxirP99ahBEWkAgUL7FZHsBgkXn1aBZWyXIY1sIKRqDZTrBhj1hpjXsCOpLsLYfo6C4hc3HspB/yymPWZjz20A+B2d0FTCBLVjqD4R/MDcUdZKzif/zTG/BRF+ES1n2jqfag+ZAUFU1fiLYuoMcbsNcb8yxhzHfB3x7kq1pA961DjVVHC4x0NiHQumh/eEZvkOOLxw32LEnTulLNI4d5g/qeZ9ymYKvB/IhLr/Ls5zmcZ7KENvohIa+yc6HgZS8GozUCJ7gjc+iLS2f3t7NSw0vnZVUQyQgS/nYLdDj6MWNsocPT5n/Ozm4Q4tpXwq5wT1WZOC8aY/RTsxFCewou+vPcyMoIFXvEyEmtIlsEewBCK/2EXZQL0kTDHP4fB7Z8S3TcF4z3sNJEc54pqykAC288cz/e7g0UgIlWxW8AF02cfBbs5tBSR027AevDeU80S06IYUeNVUcLzDnYjdYBbROT3oYRFpJKIDPN5yHm3OInorO0oWO/GKyLtfHQS4M8UbIVUohhjNlGwqvh84B+hVsqKpa+IBBqgb1CwWn2U38PbWbjwagLUxnn9dhfWuBBgqogMDmXQiEg5ERmEHZm5JMD7ReczCXhDRCr6hG8KPOP8PEHBqEpx8DfnswLwuogkBQqIyLXAwDDxJKrNJASxZ8kHHSkWkWoUjKodxLMrgzHmv9hX+WDnyf5dQpxLLyJJIjJA7FZOUWOMWQ5McX5eR9E645U1FGyzVRaY5sxrD4qItBSRHj5ebv9US4pubZdwjDFHjDHVjTEVnOuLGKKJu/0YY1ZiTwsEuF5E7vCJQ4BxhN+hZTQFI9iTReTyUMIi0lhEbgkTZ2CYbiJSL4yY13DeFFSqFKNzXhUlDMaYPBG5EdvBpQJ/FJHe2EUHq7D7B6Zi58V1wB7HWhVrCJzyxLNVRLKxG/0PFJFvsK/9chyRY8aYH2JUc5KTrgCzROQF7HZhh7H7QN6LffAuwh6beCYwFLtYqwVW93Ui8irwOXYeWiVsXl2F3WvzPOw+imvcCIwx+0Tkd9iV46nAYhF5Hrsdzwns6+CHnXiWkoBpE8aY90XkHuzDrDzWMB4mIlOwW+nswfat52Lz+gagQZDoJmMXEHVzZFc4ZbcSOwLWGTs9wR0JfCSK1dixMJGCI3q7A1+IyF+w2zilYLc0ug+7qX4VgozqJKrNJJAs7LZC7zs6rce2jWrYP3T3YcsLYJzPLiV3YMu2HvaI00wRmYBdkHYQmxcNsW3sBqyR0wh7IlcsPIat8+UIM3JmjHnTWbA5yElzlbMw7SOsQVoOOAe7Kv16bHv7f9gN9b0swv4pKYPddmssBUcAg92zN6It+04jiWo/v8GOvFfAGp2Z2L2192LL9bdO/O6COl+MMf8VkceBP2Lnx34hIm9jtyjMdsRqYetcT2x9eYfo9vH+NXaXhoXYEdZV2D4nCajv+N/gyG6iaDmfHZT0KQl66RXtRcHpItlxxJFNkNOBQoRpSsGJLuGuQ/icsIKdTB8szIJ4dMTuGxhKpw+xhqz7e7RPHBnx+AfIjvbIZgSRScGOMkWSp3lA6yDxPE7BcYuB1ynsNklh9YmyDrXD/vmIVPeJ2AVMgfFUxq5MDhU+F/vgDabLgkjaRCTlh13osSSELjuw8wfD1k/ibDNEcSod1kA1OAOSQfqMcNckfI7EdeI4F5gfYTzH8TkSF58TtkLcz/jAeEPICrYNnIhQv+E+cVSk4LQuvyszhjbihp0bbVifPqTICVuJaj9OPN2wf2iCxfE+9s9z2PoIDMH+QYukLMaFue+MAL+sCOPdADSLJd9Lw6Ujr4oSIcauNr8M6APciB0RrI39t34Y+2BaDnyMPWawyKIaY0yWs2L9N9hRwZqEXvgSjX73i8g8T9xVsNtmrQLewp681CARaSUKY0+tuVlErsTOWe2AHWFNwe7ruQ17yMI8YJqxq8X94nlSRD4B/g9rVFbHjkZ8AbxkjFkoIqMTrPun2Llt12BHUdoDdZ20T2Dz/n/YeXD/MMb4rmI29hCNPiLSHZsHrbH1Khe7mfsnwN+MMd/6hU80xo5mt8WOMN6J/cNT1tHlfeDPxphd/luiFokr7jaTIBoDXbCrsZthR7/cY4d/wI72ZzllGuxetgOdROSX2N0I2mAN2spYQ+UHbFubC0w3hbfbioUnsPlf5FW4j24GeNIZcR2CHXFsjB1ZzsWOoK7Djq7OMD4r4Y0xPznlPhxryF2A7UPO6OmFiWo/xpgPnWlJj2DfOtTF1tFvsAbjZOxuFJHo9KqITKVgG7ALsf3CKexo7npsnZtpjIn28JShwDRsGbfC7qJQC9tG92Dr4HRgsjEmJ1gkpR33/GBFURRFURRFOeM5o/9RKYqiKIqiKIoXNV4VRVEURVGUUoMar4qiKIqiKEqpQRdsncWkp6ebjIyMklZDURRFURQlLF999dWPxpiwByuo8XoWk5GRwbJly0paDUVRFEVRlLCISET7WOu0AUVRFEVRFKXUoMaroiiKoiiKUmpQ41VRFEVRFEUpNajxqiiKoiiKopQa1HhVFEVRFEVRSg1qvCqKoiiKoiilBjVeFUVRFEVRlFKDGq+KoiiKoihKqUEPKVAURSlmcnJy2LdvH4cPH+bkyZMlrY6iKEqxU7ZsWapWrUr16tVJTk5OaNxqvCqKohQjOTk5/PDDD1SrVo2MjAySkpIQkZJWS1EUpdgwxpCbm8uhQ4f44YcfqF+/fkINWJ02oCiKUozs27ePatWqkZ6eTvny5dVwVRTlrEdEKF++POnp6VSrVo19+/YlNH41XhVFUYqRw4cPk5KSUtJqKIqilAgpKSkcPnw4oXGq8aooilKMnDx5kqSkpJJWQ1EUpURISkpK+Fx/NV4VRVGKGZ0qoCjKz5Xi6P/UeFUURVEURVFKDWq8KoqiKIqiKKUGNV4VRVEURVGUUoMar4qiKEqxkp2djYjQv3//klbljGDBggWICKNHjy5pVRSlVKLGqxIbxsCWpbB2pv00pqQ1UhRFUc5yMjMzgy4Acv8khbsWLVoUMo0333wzX/a1114rjtuIiIEDB+brsXHjxhLTA2D9+vVUrlwZEeGOO+4oUV1AT9hSYmH9RzBrKBw/BCJgTkGFVLjuRWjctaS1UxRFUX6GpKWlMWrUKF+/LVu2MHHiRGrUqEGrVq2CxrFlyxbuv/9+qlSpwpEjR4pL1bDMnDmTiRMnlrgeAHl5edx5552UKXPmjHeq8apEx/qP4L27IO+nwu4njlr3X72hBqyiKIpy2klLSws6FWPkyJEA3HXXXUGPKTXGMGDAAGrUqEHfvn15/vnni0vVkOzZs4fBgwdzyy23sHPnThYuXFgierg89dRTrFy5kueee46hQ4eWqC4uZ44ZrZz5GAMzhxY1XF3yfoJZw3QKgaKUAMYYlv+wnw9X72T5D/sxpaAd9u/fHxEhOzub8ePHc/HFF1OhQgVq167NkCFDOHjwYFTxnTx5kldeeYW2bduSmppKxYoVadiwIYMGDWLDhg2FZA8ePMjIkSNp0qQJFSpUoFq1alx77bXMnTu3SLzeOaorV66kZ8+epKWlUalSJTp27Mjnn3/uq8+uXbsYOHAgtWvXpmLFirRo0YLJkyeHvId9+/YxcuRImjVrRsWKFUlNTaVLly589NFHRWSzsrIQEbKyspg/fz6ZmZlUrVqVlJQUevbsydq1a311euihh2jSpAmVK1cmLS2NJk2a0L9/fzZt2lREfs6cOfTo0YP09HSSk5O54IILGD58OAcOHCgim5GRQUZGBseOHWP48OH559k3bNiQZ555JmidXLJkCTfddBPnnHMO5cuXp169etxzzz1s3749X8adEuAact5pAJmZmSHzNC8vj6ysLACGDBkSVG7s2LHMmzePSZMmUbly5ZBxRsO7775Lly5dqF69OhUqVCAjI4Nbb72VZcuW+cq7Oo4bNy5hOqxfv54bb7yRatWqUblyZdq0acMHH3xQqA75sWzZMp588kkef/xxLrnkkoTpEy868qpEztZlkHMotMzxA7DtKzjvitOjk6IozF+3m0enfc2hn3IREU4ZQ2rFJJ664WI6Na1V0uqF5eGHH2bOnDn06tWLrl27Mn/+fCZMmMDGjRuZN29eRHGcOHGCnj17MnfuXOrVq8dtt91GSkoK2dnZTJs2jXbt2tGoUSMADhw4QNu2bVmzZg1XXnklw4YN48cff+S9996ja9euvPzyy9xzzz1F0li2bBnPPvssrVu3ZtCgQfzwww9MnTqVLl26sHLlSpo0aZIvu3fvXtq0acOmTZto164d7dq1Y8eOHdx777107er/dmrz5s1kZmaSnZ1N+/bt6datG0ePHmXWrFl069aN8ePHM3jw4CLhZs2axYwZM+jevTv33nsva9asYfbs2SxdupQ1a9aQnp4OwLFjx2jbti3fffcd11xzDb169cIYw+bNm5kxYwY33XQT559/fn68Y8aMYdSoUVSvXp3rrruOWrVqsWrVKp5//nlmz57N4sWLixx9nJubS9euXdm+fTvdu3enXLlyTJ8+nREjRnD8+PEir/UnTZrE4MGDSU5O5vrrr6devXps2LCB1157jZkzZ/LFF19Qv379/CkBWVlZbN68uVA8GRkZIevGjBkz2LlzJx06dKBp06a+MmvXrmXEiBEMHTqUDh06RFzvQuGO5E6ePJn09HT69u1LzZo12bp1K/Pnz6dJkyZccUXhZ2VWVhbTp09n2rRp1KhRI24dANatW0fbtm3Zt28fPXv25JJLLmHTpk3ccMMN9OjRI2i4n376ibvuuosWLVowYsQIPv3004TokxCMMXqdpVfLli1NQlnzvjFP1TVmVErw66m6Vk5RFGOMMWvWrCnW+Oet3WWaPDbbNHhkVpGryWOzzby1u4o1/Uj4/vvvDWD69etXyL1fv34GMPXq1TObN2/Od8/NzTXt27c3gFmyZElEaYwcOdIAplevXub48eOF/I4fP252796d/3vIkCEGMEOGDDGnTp3Kd1+/fr1JSUkx5cuXN99//32++/z58w1gADNp0qRCcb/yyisGML/5zW8KuQ8ePNgAZtiwYYXcly5dasqVK2cAM2rUqEJ+HTt2NCJi/vGPfxRy379/v7n00ktNhQoVzM6dO/PdJ02aZABTtmxZM3fu3EJhRowYYQDzzDPP5Lu9//77vjoZY0xOTo45dOhQ/u958+YZwLRu3drs37+/kKybbmA8DRo0MIDp3r27OXbsWL77rl27TGpqqklNTTUnTpzId//2229NUlKSueCCC8zWrVsLxfXJJ5+YMmXKmD59+hTJI2u6RE7Xrl0NYN5++21f/9zcXNOyZUvTuHHjfL1HjRplADNhwoSo0vIyfvx4A5grr7zSHDhwoJBfXl6e2b59eyG37Oxsk5KSYu644458N/d+N2zYELMenTt3NoD5+9//Xsh99uzZQeu1McY88MADJjk52XzzzTfGmIJ2cPvtt0etQ6T9ILDMRGDf6LQBJXKqnGMXZ4XCnIKqdU6PPoryM8cYw8h/f83xXP92eTz3FI9O+xr7TDhz+cMf/kD9+vXzf5crV44BAwYA8OWXX4YNf/LkSf7+979TsWJFXnnllSJzGpOTk6lZsyZgRwbfeustqlSpwp/+9KdCK9cbNWrEAw88wIkTJ3jjjTeKpNO2bdsi233dfffdlCtXrpCeubm5vP3221StWrXIHMwrrriC22+/vUjc//vf/1i4cCE33ngjv/71rwv5paWl8cQTT3D8+HGmTp1aJOyvf/1runTpUsjNffXsl38VK1Ys4la+fHmqVq2a/3vs2LEATJgwgbS0tEKy/fv3p0WLFrz99ttF4nHDetOoVasWvXv35uDBg3z77bf57i+//DK5ubm8+OKL1K1bt1AcnTt35vrrr2fmzJkcPnzYN51IyM7OZu7cudSoUYMbb7zRV2bMmDGsWLGCrKws37yJlZdeegmA8ePHk5qaWsivbNmy1KlT8Kw8deoU/fr1o0qVKvl5nwi2bNnCvHnzaNiwYZG3Cd27d+eXv/ylb7hPPvmEl156iTFjxnDhhRcmTJ9EodMGlMg57wpITrWLs4JRIQ3qtjx9OinKz5gVWw5w+HhuSJlDP+WycssBLqtf7TRpFT2Br04B6tWrB8D+/fvDhl+3bh0HDx7kqquu4txzzw0r674+r169ehH/zp0788c//pEVK1ZEpGdSUhK1a9cupKebRvv27YsYLWC3ewqc+7p48WLAzsX1W3S0Z88eAN95rJHmX8eOHalbty5PP/00y5cvp0ePHrRt25YWLVpQtmzZIvokJSUxZcoUpkyZUiT+EydOsGfPHvbu3Vvo9XZqaioNGzaMSB/3nhcuXMjSpUuLhNm9ezcnT55k/fr1tGwZ23NlwoQJ+Yah30KtL7/8kqeeeooHH3yQ1q1bx5SGH0ePHmX16tXUrl2byy67LKz8X/7yFxYuXMgHH3xAtWqJa6srV64EoHXr1r67BbRr167IPO8DBw4wYMAArrrqKh588MGE6ZJI1HhVIkcEer3ov9sAQLmKcN1frZyiKMXO7kM5Qfe8dBERdh3KOU0axUbgyB7Y0Vewo6rhcBcPBY7e+eEuAvOOenlx3f0WJPnp6erq1dNNo3bt2r7y55xzThG3vXv3AvDxxx/z8ccfB1Pfd9ukSPMvJSWFL774glGjRvH+++8zZ84cANLT07nvvvt47LHHSEpKytcnLy+PJ554Iqgurj5e4zVUHgXq497zc889FzaNWMjLy2PSpEmA/0Itdwuoxo0b8+STT8aURjCiqZMbNmzg97//PQMGDAg5BzUWwtVFP/ff/e53/Pjjj3z88cdF/tScKei0ASU6Gne122Gl1IXylSG5qv1MqavbZCnKaaZWSjKnwkwJMMZQO8V/a6CzBddg2rZtW1hZdyR0586dvv47duwoJBcLbthdu3b5+vul7YZ58cUXQ871c42xWDnvvPN4/fXX2b17N6tXr2bs2LHUqFGDMWPGMGbMmEL6VKtWLezcwwYNGsSsi3vPBw8eDJlGx44dY4p/5syZ7Nixg44dOxZaTOdy5MgR1q9fz9q1a6lQoUKhHQxco33w4MGICMOGDYsq7Wjq5DfffENOTg6TJk0qcqCCu7tCo0aNEBGmT58elR7ugrpgddHPffny5fz00080bdq0kC6dOnUC4O2330ZEaNGiRVS6JBIdeVWip3FX+L9v7K4Ch3fYOa51W+qIq6KcZi6rl0ZKhSSOnQg+OplSMYkW9fxHw84WmjZtSlpaGqtWrWL79u0hpw40adKESpUqsXLlSvbv31/kFe38+fMBuPzyy+PSx03j4MGDRQzhBQsWFAlz9dVXA7Bo0SIeeOCBmNOOFBGhefPmNG/enD59+lC/fn2mT5+ePwJ59dVX88EHH/DNN9/QvHnzYtHh6quv5quvvmLRokX07NkzojDuSODJkyfDjgq++uqrQPDtsZKTkxk4cKCv3/Lly1mxYgXt2rWjSZMmUU8pqFy5MhdddBGrV69mxYoVIacOZGRkBNXjgw8+YOfOndx8882kpKSE3VkhEDfdxYsXc+rUqSJTB/x2EOjbt6/vVJQdO3Ywe/ZsLrjgAjIzMwvNUz/tRLKqS6/SeSV8twFFUaJGdxsIv9uAd2W/i7uyOXBFfjAeffTRoLsN5OTkFNptwN0J4Le//W0huY0bN5rU1FSTlJRkNm3aFLEuDRo0MA0aNCjkFstuA+3btzdlypQxr7/+um86q1atMrt2FZSnu+rfb6W4McYApmPHjvm/v/76a9+8Xrp0qQFMq1at8t3mzp2bv9vAtm3bioQ5cuSIWbx4cSE3v3xwcVfvz58/P99t7dq1JikpyTRq1Mh8++23RcLk5OSY//73v4Xcbr75ZgMUKh8/srOzTZkyZUyNGjWK1IdISMRuA6+++mrQ3QZOnjxZZLcBPxKx20BmZqbvbgP/+c9/Qu42EMiZtNuAjrwqiqKUYjo1rcXLt7cstM+rMYaUUrTPayIYNWoUS5YsYebMmTRu3JjrrruOqlWrsmXLFj766COee+65/J0Cnn76aRYtWsTf/vY3li5dSqdOnfL3eT18+DB/+9vf+MUvfhGXPk899RSffPIJf/3rX1m2bFn+Pq/vvvsuPXr04P333y8S5p133qFz584MHDiQsWPHctVVV5GWlsbWrVtZtWoVq1evZvHixdSqFVuZzp07l9/97ne0adOGpk2bUqtWLbZu3cqMGTMoU6YMw4cPz5ft0qULTz/9NCNHjqRRo0b06NGDX/ziFxw5coTNmzezcOFC2rVrx4cffhhzHjVt2pSJEydy991307x5c7p160bjxo3Jzc3lhx9+YNGiRdSsWZN169YV0mvKlCn07duXHj16ULFiRRo0aMCdd95ZKO7XXnst5EKt08GgQYP49NNPeeONN2jUqBG9e/emZs2abN++nXnz5nH33XcHPREskYwbN462bdty3333MXv27Px9XqdOnUrv3r3zy780ocaroihKKadT01p8PqIzK7ccYNehHGqnJNOiXlrYxVxnE+XLl+fDDz/klVde4Y033mDy5MkYYzj33HO54YYbaNeuXb5s9erVWbx4MX/605/497//zZ///GcqVqxIq1atGD58eNBDBKIhPT2dzz77jEcffZSZM2eybNkymjRpwssvv0xGRoav8Xreeefx1Vdf8dJLLzF16lTefvttTp48yTnnnMOFF17I/fffz8UXXxyzTtdeey3Dhg3jv//9LzNmzODQoUPUqVOHa665Jt+o9fLII4/Qtm1bxo4dy6effsqMGTNITU2lbt26DBkyhNtuuy1mXVzuuOMOLr30Ul544QXmz5/PRx99ROXKlTn33HO56aabuOWWWwrJDxo0iM2bN/PPf/6TZ599lry8PDp27FjIeD158iQTJ04EQp+oVdyICJMnT6Zr1668+uqrvPfee+Tk5FCnTh3at2/P9ddff1r0uPDCC1m8eDGPPvoo8+bNY968eVxyySVMmzaNtWvXMmPGjCKHTZzpiB2lVc5GrrjiChPs+DlFUU4Pa9eupVmzZiWthqIoShFuv/123nnnHdatW+e7qC1RRNoPishXxpiwR3SWrnFiRVEURVEUJWJOnTrlu8PFJ598wrvvvsuFF15YrIZrcaDTBhRFURRFUc5STpw4Qb169ejUqRNNmzalXLlyfPPNN3z88ceUL1+ecePGlbSKUaPGq6IoiqIoShgWLFjgu81ZIGlpaVHvCxsNWVlZZGdnh5Vr0aIFffr0ISkpiXvvvZd58+axZMkSjh07Rnp6OjfffDMjRoyI6ASwMw01XhVFURRFUcKwYMGCsCeOATRo0KDYjVf38IJQ9OvXjz59+lC2bFleeumlYtOnJNAFW2cxumBLUUoeXbClKMrPHV2wpSiKoiiKovxsUeNVURRFURRFKTWo8aooiqIoiqKUGtR4VRRFURRFUUoNarwqiqIoiqIopQY1XhVFURRFUZRSgxqviqIoiqIoSqlBjVdFURRFURSl1KDGq6IoiqIoilJqUONVURRFKVays7MREfr371/SqpwRLFiwABFh9OjRJa2KopRK1HhVFEVRFKVUkJmZiYj4+rl/ksJdixYtCpnGm2++mS/72muvFcdt+JKTk8O4ceNo1aoV6enpVKlShWbNmvHAAw+wefPm06aHy/fff8+9995L06ZNqVSpErVr16Z169a8+uqrnDhx4rTr46VciaauKIqiKIqSANLS0hg1apSv35YtW5g4cSI1atSgVatWQePYsmUL999/P1WqVOHIkSPFpWoR8vLy6NKlC5999hlNmzbl1ltvJTk5maVLl/LSSy/xxhtv8Pnnn3PhhReeFn2WLl1Kp06d+Omnn+jWrRu9e/fm0KFDzJw5k3vuuYepU6fy4YcfBv0jUdyo8aooiqIoSqknLS0t6FSMkSNHAnDXXXeRnJzsK2OMYcCAAdSoUYO+ffvy/PPPF5eqRZg2bRqfffYZXbp04aOPPqJMmYIX46NGjWLMmDE8//zzTJw48bToM3r0aI4ePUpWVhb9+vXLd3/++edp1aoVH330EYsWLaJDhw6nRZ9AdNqAoijK2YAxsGUprJ1pP40paY3C0r9/f0SE7Oxsxo8fz8UXX0yFChWoXbs2Q4YM4eDBg1HFd/LkSV555RXatm1LamoqFStWpGHDhgwaNIgNGzYUkj148CAjR46kSZMmVKhQgWrVqnHttdcyd+7cIvF656iuXLmSnj17kpaWRqVKlejYsSOff/65rz67du1i4MCB1K5dm4oVK9KiRQsmT54c8h727dvHyJEjadasGRUrViQ1NTXfoAkkKysLESErK4v58+eTmZlJ1apVSUlJoWfPnqxdu9ZXp4ceeogmTZpQuXJl0tLSaNKkCf3792fTpk1F5OfMmUOPHj1IT08nOTmZCy64gOHDh3PgwIEishkZGWRkZHDs2DGGDx9O/fr1SU5OpmHDhjzzzDOYIHVyyZIl3HTTTZxzzjmUL1+eevXqcc8997B9+/Z8GXdKwMKFCwEKTQPIzMwMmVGzxiYAACAASURBVKd5eXlkZWUBMGTIkKByY8eOZd68eUyaNInKlSuHjDMa3n33Xbp06UL16tWpUKECGRkZ3HrrrSxbtixfxs37nj17FjJcAXr37g3Anj17YtZhx44dDBgwgFq1ahWqi8HmX7v6XH/99YXcK1euTJcuXeLWJ1505FVRFKW0s/4jmDUUjh8CETCnoEIqXPciNO5a0tqF5eGHH2bOnDn06tWLrl27Mn/+fCZMmMDGjRuZN29eRHGcOHGCnj17MnfuXOrVq8dtt91GSkoK2dnZTJs2jXbt2tGoUSMADhw4QNu2bVmzZg1XXnklw4YN48cff+S9996ja9euvPzyy9xzzz1F0li2bBnPPvssrVu3ZtCgQfzwww9MnTqVLl26sHLlSpo0aZIvu3fvXtq0acOmTZto164d7dq1Y8eOHdx777107epfJps3byYzM5Ps7Gzat29Pt27dOHr0KLNmzaJbt26MHz+ewYMHFwk3a9YsZsyYQffu3bn33ntZs2YNs2fPZunSpaxZs4b09HQAjh07Rtu2bfnuu++45ppr6NWrF8YYNm/ezIwZM7jppps4//zz8+MdM2YMo0aNonr16lx33XXUqlWLVatW8fzzzzN79mwWL15MSkpKIV1yc3Pp2rUr27dvp3v37pQrV47p06czYsQIjh8/XuS1/qRJkxg8eDDJyclcf/311KtXjw0bNvDaa68xc+ZMvvjiC+rXr58/JSArK4vNmzcXiicjIyNk3ZgxYwY7d+6kQ4cONG3a1Fdm7dq1jBgxgqFDh9KhQ4eI610o3JHcyZMnk56eTt++falZsyZbt25l/vz5NGnShCuuuAKA5s2bA/Cf//yHoUOHFjJgZ82aBcAvf/nLmPTYvXs3bdq0ITs7mw4dOtCmTRt27tzJfffdF7QuNm/enHXr1vHBBx9wxx135LsfO3aMefPmUblyZVq3bh2TPgnBGKPXWXq1bNnSKIpSsqxZs6Z4E/h2jjFP1jZmVErR68na1r+E+f777w1g+vXrV8i9X79+BjD16tUzmzdvznfPzc017du3N4BZsmRJRGmMHDnSAKZXr17m+PHjhfyOHz9udu/enf97yJAhBjBDhgwxp06dyndfv369SUlJMeXLlzfff/99vvv8+fMNYAAzadKkQnG/8sorBjC/+c1vCrkPHjzYAGbYsGGF3JcuXWrKlStnADNq1KhCfh07djQiYv7xj38Uct+/f7+59NJLTYUKFczOnTvz3SdNmmQAU7ZsWTN37txCYUaMGGEA88wzz+S7vf/++746GWNMTk6OOXToUP7vefPmGcC0bt3a7N+/v5Csm25gPA0aNDCA6d69uzl27Fi++65du0xqaqpJTU01J06cyHf/9ttvTVJSkrngggvM1q1bC8X1ySefmDJlypg+ffoUySNrukRO165dDWDefvttX//c3FzTsmVL07hx43y9R40aZQAzYcKEqNLyMn78eAOYK6+80hw4cKCQX15entm+fXv+71OnTpm+ffsawFx44YXmgQceMA899JDp1KmTSUpKMvfff7/Jy8uLSY+7777bAObhhx8u5L5y5UpTvnx537q4du1aU6dOHVO2bFnTq1cv88gjj5jf/OY3pl69eqZOnTpm9uzZUekQaT8ILDMR2DclbmDppcaropzNFKvxeuqUMc839Tdc3euFZlauBAlnvPoZCBMnTjSAeemll8LGn5eXZ1JTU03FihXNtm3bQsqeOHHCVKpUyVSpUsXs3bu3iP9jjz1mAPPEE0/ku7nGa9u2bX3jK1eunPH2t24aVatWLWK0GFNw316DYeXKlQYwN910k6/e06dPN4AZN25cvptrRN5+++1F5Ddt2mQAc+ONN+a7ucbryJEjfdPw0qdPHwOY1atX+/q3aNHC1KxZs5Cba7xu2LChiPxdd91lAPP111/nuw0bNswAZtasWUF1KFu2bCGjOlrj9fvvvzdlypQxNWrUKPKnxuXxxx83ZcqUMZ9//nm+WyKM14suusgAZvny5RHJnzp1yowePdqULVs2/88SYLp06WIWL14ckw45OTmmYsWKJjU1tVA+ugwaNMjXeDXGmK1bt+b/iXSvpKQkM3z4cLNv376o9Ei08arTBhRFUUorW5dBzqHQMscPwLav4LwrTo9OMeC+OvVSr149APbv3x82/Lp16zh48CBXXXUV5557blhZ9/V59erVi/h37tyZP/7xj6xYsSIiPZOSkqhdu3YhPd002rdvT2pqapEwmZmZRea+Ll68GLBzcf0WHbnzC/3msUaafx07dqRu3bo8/fTTLF++nB49etC2bVtatGhB2bJli+iTlJTElClTmDJlSpH4T5w4wZ49e9i7dy81atTId09NTaVhw4YR6ePe88KFC1m6dGmRMLt37+bkyZOsX7+eli1bFvGPhAkTJnDq1Cn69evnu1Dryy+/5KmnnuLBBx9M6Gvwo0ePsnr1amrXrs1ll10WVv748ePcdddd/Oc//2HcuHH07t2bSpUq8dlnn/HAAw/QoUMHpkyZkj//NVK+/fZbfvrpJ6644gqqVq1axL9du3a+24GtWLGCPn36UKtWLRYtWkSLFi04cOAAb731Fo899hjTp09n6dKlvvX7dKDGq6IoSmnlyE47xzUUUgYO7zg9+sRIWlpaEbdy5ezj6eTJk2HDu4uH6tatG1bWXQRWp04dX3/X3W9Bkp+erq5ePd00ateu7St/zjnnFHHbu3cvAB9//DEff/xxMPV9t2+KNP9SUlL44osvGDVqFO+//z5z5swBID09nfvuu4/HHnuMpKSkfH3y8vJ44oknguri6uM1XkPlUaA+7j0/99xzYdOIhby8PCZNmgT4L9TKy8vjzjvvpHHjxjz55JMxpRGMaOokwNNPP82UKVN48cUXC8237t69O//6179o0aIFQ4cOjdp4DVcX/dzz8vL41a9+xZ49e1iyZEl+fa1SpQojRoxg165d/PWvf+Uvf/lLiR20obsNKIqilFaqnGMXZ4XCnIKq/oba2YJrMG3bti2srDtStHPnTl//HTt2FJKLBTfsrl27fP390nbDvPjiiyFfl7rGWKycd955vP766+zevZvVq1czduxYatSowZgxYxgzZkwhfapVqxb29W2DBg1i1sW954MHD4ZMo2PHjjHFP3PmTHbs2EHHjh0LLaZzOXLkCOvXr2ft2rVUqFCh0A4GrtE+ePBgRIRhw4ZFlXY0dRIKFmV16tSpiN+ll15K9erV2bx5c77BHynugrpgddHPfd26dWzcuJFmzZr5/tFydfzqq6+i0iWRqPGqKIpSWjnvCkgOY2RVSIO6sb1yLS00bdqUtLQ0Vq1aVWh7JT+aNGlCpUqVWLlype+UhPnz5wNw+eWXx6WPm4bfdl8LFiwo4nb11VcDhD39KVGICM2bN+f+++/PH+mdPn16IX3279/PN998U2w6xHLP7vSGSEbkX331VSD49ljJyckMHDjQ93Jf9bdr146BAwdGPaWgcuXKXHTRRezatct3CkogOTk5gP/2Uzk5ORw6ZKcHlS9fPio9mjZtSsWKFVm1ahWHDx8u4v//s3fn8XJUdd7HPz9CNkJCiAmLCgQFDcLIIrigyKICxp1FBUaJKLiMo6LiiDqCzwgyLo+AjjrKo+iIICgiKCJjWAZciYLso44GcEAIS9ghCfk9f1Q1t7np23frm77n9uf9etWrbi2n6vS5leSb6lOnLr/88gHrcuedd7Y8ZqOOw61LJxleJalUEfCqk2Dd6a23rzsdXnni4F0LCjdp0iTe9a538fDDD/OOd7zj8X98Gxr9M6H6B/eQQw7hgQce4OMf//gT9vuf//kfTj75ZCZPnsyb3vSmEddn8uTJHHLIIdx///1rfK26ZMkSTjvttDXK7Lzzzuy2226cffbZAw5Ef80113DHHXeMuF7XXnstS5cuXWN94+7beuut9/i6I488EqjuPLb6D8GDDz7Ir371qxHXBeDd7343kydP5sgjj+QPf/jDGttXrFixRrBtdFG4+eab2x77pptu4sILL+RJT3oS+++/f8t9pk+fzimnnNJyaoxveuihh3LKKafwhje8Ydif7z3veQ8Ab3/729f4T8zq1asfv8sPsNtuuwFw/PHHr3H9HnvssaxatYpddtmlZb/VdqZMmcIb3vAG7r33Xj75yU8+Ydvvf/97vvWtb61RZrvttmP27NncfPPNa/SHXb58+eMvb2iM99oN9nmVpJI9Y294/bfgR++rHs6KdepxXmdXwbWAcV474ZhjjuHXv/415513Hs94xjN45StfycyZM7nlllu48MIL+cxnPsOiRYuAqn/hZZddxhe/+MXHX4PZGOf1/vvv54tf/CJbbrnlqOpz/PHHs3jxYk488USWLFny+Div3/3ud1m4cCHnnnvuGmW+853vsNdee/HWt76Vk08+mec973nMnj2bv/71r1x99dVce+21/PKXv2SjjTYaUZ1+9rOf8f73v59dd92VBQsWsNFGG/HXv/6VH/7wh6yzzjocddRRj+/7kpe8hBNOOIGjjz6arbfemoULF7LlllvywAMPcNNNN3HppZfyohe9iAsuuGDEbbRgwQK+/vWvc9hhh7Htttuy77778oxnPIOVK1dy8803c9lllzFv3jxuvPHGJ9TrrLPOYr/99mPhwoVMnz6dLbbYYo3/bJxyyiltH9RaG972trdx+eWX861vfYutt96a17zmNcybN49bb72Viy66iMMOO+zx/9x89KMf5bzzzmPx4sUsWLCAfffdl+nTp/Pzn/+c3/zmN0yfPp2TTjppRPU44YQTuOiii/j0pz/Nr3/9a3bddVduu+02zjzzTBYuXMg555zzhHFlp06dyoknnshb3vIWDj/8cM444wx23HFH7rnnHs4991yWLVvG85//fN761rd2oplGZihDEjiVOTlUltR9Yz7Oa8Pq1Zm3XJF5/bnVvMvDYzUbbKis5jFVGxrDU7UawmcgK1euzC984Qu5yy675IwZM3K99dbLrbbaKg8//PA1hm+655578kMf+lButdVWOWXKlNxggw3ypS99af70p2uOiztYXbbYYovcYost1lh/22235Vve8pacO3duTps2Lbfffvv8xje+0fZ49913Xx533HG500475YwZM3LatGk5f/78XLhwYf77v/97PvDAA4/v2xgqq//Ysw1A7r777o8vX3/99XnkkUfmc57znJw7d25OmTIlt9hii9x///3z5z//ectjXHbZZXnggQfmpptumpMnT865c+fm9ttvn0ceeWReccUVQ2qHzL6hpy6++OI1tl199dV56KGH5uabb55TpkzJDTfcMLfddts84ogjcvHixU/Yd9WqVXn00Ufnlltu+fh4uc2fsbHPk5/85ATyxhtvbFmfwXRiqKyGb3/72/niF784Z82alVOnTs358+fnwQcfnL/97W+fsN8dd9yRH/jAB3LBggU5derUnDx5cm6++ea5aNGivOGGG0ZVh7/+9a/55je/+QnX4qmnnppnnXVWAvn5z39+jTKXXnppvu51r8tNNtkk11133ZwxY0butNNO+alPfSoffvjhYZ2/00NlRbWvJqKdd945m18/J2ntu+GGG9hmm226XQ1JWsNHP/pRjj/+eC644AL22WefMTvPUP8ejIjfZuag4/rZ51WSJGkCa9Vv+ZprruHkk09mzpw5Ix7RoVt6qs9rREwF9gB2aZoaY8i8PDNH3nnnieeZCbwbeC2wNTANuB24Cjg3M9cY6yQilgKDjTlyVGZ+thN1lCRJvWHnnXdmq622YrvttmPGjBn88Y9/5Mc//jGrV6/mK1/5CtOmTet2FYelp8IrsA3QkYA6kIjYBfgB0BiZeAXwCDC/nv4OaDdQ3z11mVYe7EglJUnSsFxyySUthznrb/bs2cMeF3Y4zjnnHK666qpB95s/f/7jDym+/e1v55xzzuH000/n/vvvZ/bs2eyzzz588IMfZI899hizuo6VXguvAMuB3wJXAEuA73XqwBHxTOBCYDawGPgo8JvMzIiYBTwfeOEgh9kvMy/pVJ0kSdLoXXLJJYO+cQxgiy22GPPw2v/1wq3svvvuj4fXY445hmOOOWbM6rS29dQDWxGxDtB4oq2xrvHzqLsNRMTlVOH0fODVmTn4KMp9ZZdSdRvYs1Ph1Qe2pO7zgS1Jva7TD2z11J3XzMHeozhyEbE7VXB9DHjncIKrJEmShsbRBjrnkHp+UWa2f/WHJEmSRsTw2jmNFx9fHhFPj4hvRcRtEfFoRNwcEd+MiG2HcJzPR8SyiFgREX+LiPMj4uCImDSWlZc0dnqpe5YkNRuLv/8Mr52zdT2fA1wJvAnYEHgY2Ax4M/C7iDhwkOPsAKxHNULBxsDLgdOAxRExe7BKRMQREbEkIpY03uUtqXsmTZrEypUru10NSeqKlStXMmlSZ++/GV47ICKmAY2XJ78HWA28Hlg/M2dTDY/1a2AK8M2I2KrFYc4B9gfmZuaMzJxF9QDXZ+vj7Q6cOVhdMvOrmblzZu48b968UX4ySaM1c+ZM7rvvvm5XQ5K64r777mPmzJkdPea4D68R8fGIWDXC6bi1VM3mdgzgvZl5VmauAsjMa4HXAA8A04Ej+x8gM9+XmWdn5l1N627OzKOAf6xXvSwi9h6rDyGp8+bMmcM999zDnXfeyYoVK+xCIGnCy0xWrFjBnXfeyT333MOcOXM6evwSRhtYBxjp/ea10k80Mx+KiNVUdb0b+I8W+9weEd8BjgBeOsxTfBk4iuolB6+iGktWUgGmTp3K5ptvzt13383SpUt57DEHIpE08U2aNImZM2ey+eabM3Xq1MELDMO4D6+ZeSxwbJerMRS3Ub1V609thuT673q+2XAOXL/k4Aqq8Pq0EddQUldMnTqVTTfdlE033XTwnSVJbY37bgMFua6eD+U7wZF8bxijKCtJkjQhGF47Z3E937p+k1crC+r5TcM5cEQE0HjjxNLhV02SJGliMLx2zhnASqqhst7cf2NEbAwcVC+e329b9N+/n7dTdRkA+PGoailJklSwnguvEbFhRMxtTE2bZjWvj4jJLcoujYiMiFP7b6vfqvXFevHEiDggItaty20L/BBYH1gOfL5f8ZMj4qSIeFFETG8632YRcULTcS/OzJ+M8KNLkiQVb9w/sDUGrqQaP7W/7/Zb3hO4ZJjH/ifgGcArgLOARyLiUWCDevv9wAGZ+b/9ys0EDqUeIzYi7qUaKWFW0z6XAgcMsz6SJEkTSi+G1zGTmSsj4lXAW+ppO6pxXf8HuAD4TGa26u/6FWAZsCuwOfAkqrvitwBLgNOB77cZxUCSJKkn9Fx4zcz5Y1k2qxHIv15PQz3ur4BfjbRekiRJvaLn+rxKkiSpXIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFaOnwmtETI2IfSLiYxHxw4i4NSKynvYd5bEvaTrWYNMxbY5zYERcFBF3RcRDEXFDRHwyImaOpn6SJEkTwbrdrsBatg1wwRgd+27g9jbbpwEb1D//rtUOEfFV4PB6cRXwCLAA+ChwUETslpm3dqa6kiRJ5empO6+15cBi4ATggE4dNDP3y8xNBpqAb9a73gH8pH/5iHgnVXBdDRwFrJ+ZM4EXAjcBTwPO7FR9JUmSStRrd16vBuZkZjZWRMSYnzQiJgMH1YunZeaqftunAsfWiydl5mcb2zLzFxHxOuC3wAsj4lWZed6YV1qSJGkc6qk7r5m5ujm4rkULgXn1z6e22P5SYCMggc/135iZVwI/qxcPGYP6SZIkFaGnwmsXHVrPr8rMq1ts37OeX5uZ/zvAMX5az/fqaM0kSZIKYngdYxHxJOAV9eI3B9jtWfX8ujaHur6ez4uIuZ2omyRJUmkMr2PvYGAK1egBpw2wz6b1vN1IAs3bNh1wL0mSpAnM8Dr2Gl0Gzs/MZQPsM6OeP9zmOA81/bz+QDtFxBERsSQilixbNtDpJEmSyjTuw2tEfDwiVo1wOq7Ldd8WeE69OFCXAYDGkAejfpgsM7+amTtn5s7z5s0bvIAkSVJBShgqax1g0gjLjrRcpzTuut4F/KjNfg/U8/Xa7NO87YEB95IkSZrAxn14zcxj6RsDtRgRMQn4+3rx9Mxc0Wb3W4EdgCe32ad5222jrJ4kSVKRxn23gYLtTd+DVe26DEDfSALbttmnMSLBssy8czQVkyRJKpXhdew0ugxcl5lLBtn34nq+bUQMdPd173q+eNQ1kyRJKpThdQxExAbAa+rFwe66QhVI76D6fby/xfG2p3oLFww83JYkSdKE13PhNSI2jIi5jalp06zm9RExuUXZpRGREXHqIKd5AzANeAz49mB1ysxH6evXe2REfCAiptbnfAHwA6rf1c8zs92DX5IkSRNaz4VX4EpgWdPU8N1+6184inM0ugxcmJlDergqM78MfI3qd/JZ4P6IuB/4BbAl8Gfg9aOokyRJUvF6MbyOqYjYCti1XhxKl4HHZeYRVHdtL6YaDmtd4EbgOGCHzGz3Bi5JkqQJb9wPldVpmTl/LMtm5p/oe+nASM5xJnDmSMtLkiRNZN55lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkooxovAaES/sdEUkSZKkwYz0zutlEfGziNi9o7WRJEmS2hhpeP0BsAdwUUT8V0S8rN3OEfG1iPjnEZ5LkiRJAoYQXiPiHf3XZeb+wDbA14HnAhdExK8i4hUtym8EHAwcO+raSpIkqaetO9CGiHgm8DXgBcBXWu0CLAeuogqwuwDnRsR1wJ+AlcAkYHdgOnBTR2suSZKknrNGeI2IdYGjgY8AdwJ7t9hnD+CndflorK7n29VTNq2/H3hnB+stSZKkHtTqzuuHqL7iPwc4PDPvbrHPvwCTqe66/ivVndZH6m3TgQ8Ar6cKrtcC+2TmbR2tuSRJknpOq/C6Dn13UR8boNx2wGpg38y8o8X2gyLic8BXgR2A8yPixZl5/2grLEmSpN7V6oGtTwPHAa8EromIF7fYJ4H7Bwiu1Q6ZS4DnAT8Gtge+NPrqSpIkqZetEV4zc0Vm/jOwE3ALsLhFud8BsyJi+3YHz8yVwFup7tK+fPTVlSRJUi8bcKiszLwuM18IvLfF5lOouhb8R0Q8pd0J6ruzDwKzRlNRSZIkadBxXjNzja/7M/MMqjuy2wE3RsRHImJ2q/IRsT8wE7hrlHWVJElSjxtwnNcheAPwE6rxXf8FOCYiLgd+TtXdYB2q8V//nqqP7CWjqqkkSZJ63ojDa2beHRG7AR8E3gfMBfakem1sswDuAXw9rCRJkkZlNHdeycwVwPER8RmqlxnsCewIzAemAMuo7rh+PjNvGVVNJUmS1PNGFV4b6lEFflxPkiRJ0pgY9IEtSZIkabwwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGD0VXiNiakTsExEfi4gfRsStEZH1tO8oj31J07EGm45pUX7pEMp9cDR1lCRJKt26F+vCmwAAIABJREFU3a7AWrYNcMEYHftu4PY226cBG9Q//67NfvcAKwbY9uAI6iVJkjRh9Fp4BVgO/Ba4AlgCfK8TB83M/dptj4iTgPcAdwA/abPrfpl5SSfqJEmSNNH0Wni9GpiTmdlYERFjftKImAwcVC+elpmrxvykkiRJE1BPhdfMXN2lUy8E5tU/n9qlOkiSJBWvpx7Y6qJD6/lVmXl1V2siSZJUMMPrGIuIJwGvqBe/OYQin4+IZRGxIiL+FhHnR8TBETFpDKspSZJUBMPr2DsYmAKsAk4bwv47AOsBjwAbAy+vyy2OiNljVUlJkqQSGF7HXqPLwPmZuazNfucA+wNzM3NGZs4CtgA+C6wGdgfOHOxkEXFERCyJiCXLlrU7nSRJUnnGfXiNiI9HxKoRTsd1ue7bAs+pF9t2GcjM92Xm2Zl5V9O6mzPzKOAf61Uvi4i9BznOVzNz58zced68ee12lSRJKs64D69UdZw0iqmbGndd7wJ+NIrjfBlYWv/8qtFUSJIkqWTjfqiszDwWOLbL1Ri2+gGrv68XT8/Mgd6aNajMzIi4ApgPPK0D1ZMkSSpSCXdeS7U3sGn981BGGRhM420K2XYvSZKkCczwOnYaXQauy8wlozlQVK8B27leXDqaY0mSJJXM8DoGImID4DX14qB3XWPwd9S+narLAMCPR14zSZKkso37Pq+dFhEb0vpBrlkRMbdp+d7MXNmv7FKq4au+mZmL2pzmDcA04DHg20Oo1skRsRo4C/htZj5cn28z4B+AD9b7XZyZPxnC8SRJkiaknguvwJVUAbS/7/Zb3hO4ZITnaHQZuDAzbxvC/jPrMu8BVkfEvVQBe1bTPpcCB4ywPpIkSRNCL4bXMRURWwG71otDfVDrK8CyutzmwJOounTcAiwBTge+n5mrO1tbSZKksvRceM3M+WNZNjP/RN/IAEM97q+AX42wWpIkST3DB7YkSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjF6KrxGxNSI2CciPhYRP4yIWyMi62nfDp1jz4g4MyJuiYhHI+LBiLg+Ir4QEU8fQvkDI+KiiLgrIh6KiBsi4pMRMbMT9ZMkSSrZut2uwFq2DXDBWB08Ij4FfLhp1YPAlPq82wBvi4gDMvPHA5T/KnB4vbgKeARYAHwUOCgidsvMW8eq/pIkSeNdT915rS0HFgMnAAd06qARsTd9wfV0YMvMXB+YBuwKXF3//O2I2KBF+XdSBdfVwFHA+pk5E3ghcBPwNODMTtVXkiSpRL125/VqYE5mZmNFRHTq2IfU8z8Cb8rMxwAyczXwy4h4LfBnYDawJ3BOUx2mAsfWiydl5mcb2zLzFxHxOuC3wAsj4lWZeV6nKi1JklSSnrrzmpmrm4Nrh21cz69uBNd+5/4LcHe9OKPf5pcCGwEJfK5F2SuBn9WLh/TfLkmS1Ct6KryOsaX1/NkRMan/xojYEphTL17Zb/Oe9fzazPzfAY7/03q+12gqKUmSVDLDa+ecQnXndGvgWxGxBUBErBMRL6Cvm8DXMvP6fmWfVc+va3P8Rpl5ETG3Q3WWJEkqiuG1QzJzCXAY1QgBBwNLI+IB4GHgF8BM4IPA21sU37SetxtJoHnbpgPtFBFHRMSSiFiybNmyYXwCSZKk8c/w2kGZeSrwWqCRGmdQDZUFsB5Vt4Epa5Z8vA/sw20O/1DTz+u3qcNXM3PnzNx53rx5Q6m2JElSMcZ9eI2Ij0fEqhFOx63Fek6OiFOoxpH9E7AHsCHwFOAgYCXwEeA/I2Jy/+L1fKweJpMkSZoQxn14parjpFFMa8uHgLdS9U3dMzMvzczlmXlrZp4BvISqS8FuwNv6lX2gnq/X5vjN2x4YcC9JkqQJbNyH18w8NjNjhNOHBz9Dx7y3nn8pMx9t8Tn+ADTerPWafpsb/Vmf3Ob4zdtuG1ENJUmSCjfuw2sJIuJJQKOD6V/a7Prnej6/3/rGSALbtinbGJFgWWbeOawKSpIkTRCG185Y3fTz5m3226Ke399v/cX1fNuIGOju6971fPEw6yZJkjRhGF47IDPvAW6uFw8b4CUFTwX2rRd/3W/zYuAOqt/H+1uU3Z7qLVwAp3WizpIkSSXqufAaERtGxNzG1LRpVvP6FiMCEBFLIyIj4tQWh/5KPd8FODsinhmVyRGxB9UoBLOAVcCXmgvWfWSPrRePjIgPRMTU+pwvAH5A9bv6eWb+aKSfXZIkqXQ9F16pXs26rGlq+G6/9S8c5nE/A3yv/vnVwI3Ag1Tjs15M1Z91JfC2Fm/YIjO/DHyN6nfyWeD+iLif6gUHW1L1l339MOskSZI0ofRieB0TmbkqMw8E9gfOpRoRYF2qwPpH4KvAjpn5zTbHOAJ4A1XYfaAufyNwHLBDZrZ7A5ckSdKEt263K7C2Zeb8sSybmWcDZ4/iHGcCZ460vCRJ0kTmnVdJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRirNvtCkiSJGl8yUyuvGU5d9z3KBvNmsqOm80mIrpdLcDwKkmSpCYX33gHH/nBNdz38EoigtWZbDB9Mse/7u/Yc8FG3a6e3QYkSZJUufjGO3jnab/ltnsf4cEVj/HAo6t4aMVj3HbvI7zztN9y8Y13dLuKhldJkiRVXQWOPvsaHlm5uuX2R1au5iM/uIbMXMs1eyLDqyRJkrjyluXc/8jKtvvc9/BKrrpl+VqqUWuGV0mSJHHHfY8O+lBWRHD7fY+upRq1ZniVJEkSG82ayupBugRkJhvPmrqWatSa4VWSJEnsuNlsZk2b3HafWdMns8Nms9dSjVozvEqSJImI4FP7/R3TJreOh9Mmr8Pxr/u7ro/3aniVJEkSAHsu2IgvH/IcNt1gGjOmTGL9qesyY8okNt1gGl8+5DnjYpxXX1IgSZKkx+25YCN+8eG9uOqW5dx+36NsPGsqO/iGLUmSJI1XEcGOm2/Y7Wq0ZLcBSZIkFcPwKkmSpGIYXiVJklQMw6skSZKKYXiVJElSMQyvkiRJKobhVZIkScUwvEqSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0mSJBXD8CpJkqRiGF4lSZJUDMOrJEmSimF4lSRJUjEMr5IkSSqG4VWSJEnFMLxKkiSpGIZXSZIkFcPwKkmSpGIYXiVJklQMw6skSZKK0VPhNSKmRsQ+EfGxiPhhRNwaEVlP+3boHHtGxJkRcUtEPBoRD0bE9RHxhYh4eptyS5vqMtD0wU7UUZIkqVTrdrsCa9k2wAVjdfCI+BTw4aZVDwJT6vNuA7wtIg7IzB+3Ocw9wIoBtj3YkYpKkiQVqqfuvNaWA4uBE4ADOnXQiNibvuB6OrBlZq4PTAN2Ba6uf/52RGzQ5lD7ZeYmA0xf7lR9JUmSStRrd16vBuZkZjZWRESnjn1IPf8j8KbMfAwgM1cDv4yI1wJ/BmYDewLndOrEkiRJvaKn7rxm5urm4NphG9fzqxvBtd+5/wLcXS/OGKM6SJIkTWg9FV7H2NJ6/uyImNR/Y0RsCcypF69cW5WSJEmaSAyvnXMKkMDWwLciYguAiFgnIl5AXzeBr2Xm9W2O8/mIWBYRKyLibxFxfkQc3CoQS5Ik9RrDa4dk5hLgMOAR4GBgaUQ8ADwM/AKYCXwQePsgh9oBWK8+zsbAy4HTgMURMXtsai9JklQGw2sHZeapwGuBZfWqGVRDZUEVSOc0Lfd3DrA/MDczZ2TmLGAL4LPAamB34MzB6hARR0TEkohYsmzZssF2lyRJKkqM3fNLnRERHwc+PsLi/5qZHx3k+I0GeHlmjngM2IiYDHwZeCvwS+Bo4PdUofXFwGeApwKXAS/JzJXDOPa7gH+rF/fJzAuHWG4ZcNNQzwPMBe4cxv7qDNu9O2z37rHtu8N27x7bfmi2yMx5g+1UwlBZ6wAj7e+5NvuJfogquF4P7JmZj9brlwNnRMTvqMLsbsDbqILuUH0ZOAqYD7wKGFJ4HcoF0CwilmTmzsMpo9Gz3bvDdu8e2747bPfuse07a9x3G8jMYzMzRjh9ePAzdMx76/mXmoJr8+f4A9B4s9ZrhnPgenivK+rFp424hpIkSYUb9+G1BBHxJKBxl/MvbXb9cz2fP5LT1PPx3c9DkiRpDBleO2N108+bt9lvi3p+/3AOHtVrwBpfNywdTtlh+uoYHlsDs927w3bvHtu+O2z37rHtO2jcP7A11jr4wNZNVMH1CuAF/d+yFRFPBa4DZgH/lpnvbtoW7d78FRHvoK+P7MLM/MlI6ylJklSynrvzGhEbRsTcxtS0aVbz+nr0gP5ll0ZERsSpLQ79lXq+C3B2RDwzKpMjYg/gAqrgugr4Ur+yJ0fESRHxooiY3nS+zSLiBOCL9aqLDa6SJKmX9dyd14hYSt/X9+3smZmXDFD2m5m5qN+2dYHTgQOaVj8MTKZvVIeVwOGZ+c1+ZU8FDq0XVwP3Uo2UMKtpt0uB/TLz7iHUXZIkaUIqYaisImTmKuDAiNiPKojuQjWu20qqh7guBk7OzOtaFP8K1YsNdqXqevAkqrvitwBLqELx9zNzdYuykiRJPaPn7ryWqqlv7lDskZmXNpVdh+oNXbtQPfi1C30jHrwzM7+yxhGGX78ADgfeAmxDdef4T8B3gJMyc8Voz9EN47ndh1i3AzPze6M5T7eMsu1nUQ1JtzdVu29ONWLHrcB/Uf1H8spR1m8K8D6q10FvRdUl6AbgG8DX2vVjH8/Ga7tHxHzaj+bSsEv9uu6ijLLdn0J1HT4X2BbYCNiA6lu864DvAV9tNYzjMOo3Ia93GL9tP9Gv+dEwvBYiIv42yC6zgOnACuDJmXlXU9nZwD0DlOtEiJpM9XrbhfWqFcBjdX2geohtr8x8YDTn6YZx3u6NP7x3UrV3K2/LzB+N5jzdMsq2/yPVP7AND1GFqMY1+RjwT5n5uRHWbRZwEfCcpuOvS9/rn38EvK7+RqYo47Xd+/1DfnubXffJzN8P9/jdNsp2fyPVN3QNj9ZTc9ezG4CXZeb/jqBuE/Z6h/Hb9hP9mh+VzHSaABNwFdUYsN9vsW028ADVnY//CxwE3Fbv/44OnPtf62M9TNVlYhLVP1ivBO6qt53W7TaagO2e9TS/2+0wDtt+KfA74F1UrxuEqivOs6n+EW603cIRnvu7dfm76us86uv+0PrPQQLHdbuNJlK7U31rkdTvbem1aZB23xU4FtgTmNO0fhbVN2L312UXj/DcPXu9d7Pte/2ab9s23a6AUwd+ibBD0z8Kr26xPYB1+q1b2okQBWwCPFIf6z0ttr+m3rYaeHa322qitHt9rJ4Nr0No+93alJ1O9RrnpBrBY7jn3nGQc7+33vYQsFG322oCtXvP/kM+WLsPofxbm8pvNsyyPXu9j4O279lrfrCp54bKmqAOrefLgPP7b8zKWD3stT8wlap/zxqDMGfmD4E/UAW5g8eoDt3SzXbvdYO1/WUDFczMh6nuJEHf16DD0biO/zszz22x/atUfx6mA/uN4PjjWTfbvZe1bfchuKLp5ycPs2wvX+/Q3bbXAAyvhauH6Gr85XJarv0+R3vW8//KzEcG2OfCer7XWqjPWjEO2r1ndajtG33WJo2gbOOav7DVxjqkNUKc1/wTjabde1KH2n3Xpp+XDrNsT17vMC7aXgMwvJbv5VRPNwJ8s92OY+RZ9bzVEGAN19fzbepRCSaCbrd7szMj4p6IeDQi/hoR34+IV3S5TmOpE22/ez2/djiF6ut3Qb04lGv+WW32KU3X2r2/iPhlRNwXEQ9HxF8i4tsR8aLRHHMcG1G7R8SUiNgyIt4PNB6QOysz2z340/8YvXy9QxfbvsUxe+maH5ThtXyL6vnVmXlVF86/aT2/tc0+jW3r19NEsKied6vdm+1CdSdrJfAUqq/ufhQRZ9bD20w0i+r5iNo+InYCXlcvfmOYxWcBM+qfh3LNb9pmn9IsqufdaPf+nk/Vjx6qfoGHAJdFxIkT6D/IDYvq+ZDaPSL+VI9E8ijwZ6rwNB04CzhsmOfu5esdutv2/fXSNT8ow2vBImIO1ZOfAKd2qRqNv9gebrPPQ00/Fx9ex0m7Q3UnYF9gw8yclZnrU42x2wgGB9L3auEJYbRtHxEzgdOowv7vgFOGeYgZTT8P5Zov/nqHcdHuUD0Y+iXgxcDMzJwNrEfVf/a8ep/3AkeP4Njj0gjbfRnVsErNQxOeCXwkhz9cYU9e7zAu2h568JofKsNr2Q6iGmdvFdU/DN3USwMGj4t2z8xFmfnTzFzetO7GzDwM+Ey96m0RsaD1EYo04rav+699h+pr0OXAG0fQh635DofX/BB0qN3JzL9l5j9k5mWNIFA/FPm7zHw11d0tgI/UYyxPBMNu98x8QWZukpkzqUaD+RhVCLsmIg4c5vl79XqH7rd9r17zQ2J4LVvjKcifZOYdXarDg/V8vTb7NG8r7kUFLYyHdh/MJ6julAQwkfq/jqjt67ednUr1D8lDwKsy848jOH/z9TuUa34iXO/Q/XYfin+q5zOAl4zROda2Uf1dk5m3Z+ZxVEFsGnBq/UaooerV6x263/ZDMRGv+SExvBYqIrah6usI3X1gqNHXqd0QII1tD1D4X27jqN3byswH6Xso5mndrEunjLTt6/5gX6bqI7aC6k1Al4+wGvfR9x+2oVzzt43wPOPGOGn3QWXmX6i+toUJcM138u+azDwPuIkqZL5xGEV77nqHcdP2Qzn2hLrmh8PwWq5F9fxu+vq+dEPjKdNt2+zTeAL1hsws/aunRfW82+0+FI2v/Epv84ZF9Xy4bX8icATV139vzMyWQ/4MRX393lAvDuWav77NPqVYVM+71u7DMJGu+UX1vFN/1zReTfr0oRbo0esdxkHbD8NEuuaHzPBaoPqruL+vF0/PzBVdrM7F9Xy3iJg2wD4vq+eL10J9xsw4a/e2ImIGff/YLO1iVTpipG0fEZ8C3kP1lO6hmfmDDlSncc2/rNXG+s/BbvViT17zY9Tug51zS2Buvbh0rM83lsbo75r59Xy43371zPUO467t25pI1/xwGV7L9DL6vqbp9lfXZ1MNCzIbeFv/jRHxKuCZVP8rPH3tVq3jxk27D2FolH+mGqIlGdlbYcabYbd9RPwz8GGqNjgiM7/Tobo0ruMFEfHKFtsPBzag6nM85qFtjI2bdh/CNX98PX8YuKgT5+yiYbV7/VBcu+2HNB1vwLegDaCXrncYR23fY9f88Iz2/bJOa3+ienI3geuGUWYDqv+hNaab62N8oN/6qS3KXlLve8kAx/5X+t5t/SZgUr1+IXBnve20brfbRGp3qqdMjwN2BqY0rX8m8DX63qX9jW63WzfaHnhfUxv8wwjOt7Que+oA279bb78TWFivmwS8uf5zkMBx3W63idTuwKVUQwJt1/R3TAA7UoWmxnmP6Xa7daHdf0H1H4ZnNdqmXr85cAzVDYYElgDrDKfd6+09cb2Pt7bvpWt+2L+nblfAaZi/sGrQ6MZfFh8aRrlLmi70dtOiNmUvGeDYk4EfNx3jEapO/o3l31CNUdf19pso7d7vuKuoXrv5QL9jnkWLUFzaNJK2p/q6OoHHgL8NMm3WovyA/6A01WlJU1s/WF/3jeXzgHW73XYTqd2btiXVA2B3NtWvMX0BiG63XRfavVXb9P/74DfAJoOU79nrfTy2fa9c8yOZ2t7u1rj0eqqvg1cD3+5yXQDIzJV194DDqTq6P4vqf+VXUX3ldGKO4/6hQzTe2v144Gqqt648FZhDVbe/AL+i+otwbTwgszaMpO0bX7etA2w8yL6ThluhzLwvInYFjqQaCmcrqjssV1K9JOJrWf/rU7Dx1u5HUX2l+1yqMTTnUP2D/t/Az4GvZuavh3nM8Wgk7b6I6oUlLwY2A+bV5ZdSvRTiLKrXkz42kgr1yPUO46/te+WaH7aYGNebJEmSeoEPbEmSJKkYhldJkiQVw/AqSZKkYhheJUmSVAzDqyRJkopheJUkSVIxDK+SJEkqhuFVkiRJxTC8SpIkqRiGV0lrTUQsiohjI2KHbtellYh4dkS8IyL+X0RcHRGrIiIj4owRHu/YuvxIpj06/PGGUt8FdZ3f0eHjXtL0uRZ28tiSes+63a6ApJ6yCNid6r3fV3W1Jq19C9i+g8d7ALi9xfopwIb1z3cCrd57vqKD9RiqBcAxwO+Br3TigBExn+q97w2HAud34tiSepPhVZL6rKQK1UuAK4D9gH1GerDM/Czw2f7r67uqF9eLu2Tm0pGeowBvBgL4JvBG4DURMTszl3e3WpJKZXiVpD7Pz8zH74JGxK7drMwE8eZ6/iVgFvA64A3Av3etRpKKZp9XSWOu7uuaVF0GAL7Rr3/n0hZlNo6Iz0XEjRHxUETcGxG/iYgPRMTUAc5zan28YyNiWkR8oi7/cETcERGnR8QzBqpnc3AdbyLiyXV7XB8RD0bEAxFxVUR8PCJmDVBmekR8qG63eyNiRUTcFhFXRsSJEbFT077LgR/Ui9u36IP72hHU+UXA04E/ZeZvgNPqTYcOsfwOEfH1iPif+nd4d0T8vm6HvxugzCYR8al6v/vqtroxIv4jIvbtt++J9Wc7sU0dzqn3eV+/9a+t119VL78uIn4WEcsiYnVELKrXR0S8KCI+GxFX1O2/IiL+FhHnRcQrhtAOQ/pMEXF2XadTBjneSfV+dt9QkbzzKmlteJiq7+ccYDJwX72uYVnzzhHxXOAn9f4A91P1E92lnt4UEXtn5h0DnG8q1dfyz6fqO/oIMI/qa+tXR8TLM/O/OvC51oqI2Bv4HjCzXvUokFT9c7enao+XZuZNTWWmA5cBz6lXJbCcqh02AXYApgGNh7Nur/eZDawC7upXjUdGUPVGSP1OPf8RcC/wgoh4Rmb+YaCCEfFR4F+ouhxA1X94OvDseno68Np+ZfYFvkt1hxeqdloBPLOeXkX1+ToqIv4P8M/0tXE2bX4K1e+hoXE9bgy8EnhlRHw6M/9pgGMP5zOdQnVn+/UR8Z7MfKjF8aYAh9SLXx/eJ5XGB++8ShpzmfndzNwE+EW96r2ZuUnTtEtj34jYEDiHKrheAzw3M2cB6wMHAvdQBbbTGNg7qQLOocD6mbkBsCPwO2A94Mz6PONeRGxDdUd0feBkqtA2HZgB7ARcCmxFFXCaHU4VXO8FDgCmZeYcqsD6NOD9wA2NnTPzmcBb6sXr+v1+NsnMC4ZZ7+nA6+vF79TneBT4fr3uza3K1WUPBz5JX1/ZrTNzJtXvbjPgMODafmWeDZxNFfJ+BbwIWK++duZSBcUfD+czDNFWwMeATwPz6jaeBfy03r6K6nreH9iU6vfQqNMHqcLohyLiZf0PPILPdAFwC9V/cg4YoL6vBp5E9aDguSP7yFKXZaaTk5PTWpmAS6juSi1qs0/jDtY9wCYttu9db09gr37bTm3adkiLsnOp/tFO4GNDqG/jeGd0uB32aKrn/EH2/VG93ycG2D4D+GO9z0ub1n+nXvepYdTrtXWZqzrwGQ+qj7Wk3/q96vU3ATHA57mr3udLwzjfhXWZ31EFxKGUObEuc2Kbfc6p93nfAG01rHq2OP4/1sf4QYc+0yfqMhcPsP38wT6zk9N4n7xk9M08AAAHyklEQVTzKmm8adwxOiUz/9Z/Y2ZeCPyyXnx9/+21m+j7qrq57J30PSg00J2pcSMi5gELqYbSOqnVPpn5IPDDerH57t199XzTMatge4vqef875JcAtwKbA3u2KPcqqrvuDwMfHcqJImJT+j770Zk5ki4Oo/GZUZQ9r56/sHnlKD7T14HVwO4R8bR+x3wy1X/+GvtJRTK8Sho36v5429WLF7fZ9aJ6vtMA2y/NzBxoWz3frj7fePZ8qq/OA7i+fshnjQk4ot5/s6ayjYdxDo2IMyPi1RHR8f6erdQh6aVUIeoJ3RkyczVwer3YquvA8+v5LzPzniGe8nn1/FH6ro215fbM/Eu7HSJiSkS8q36g62/1A1sZ1UOMjbLzIqL5OZQRfaas+j3/jOqaWdRv86HAJKq74VcP9ZjSeGN4lTSezKHv76X/bbPfX+v5vAG2tyvb2DaJvhcFjFeNu6brUD3gM9DUeJBrvUbBzDyXaozZ1VR9hX8I3B0R19RPrm8xhvV+U13nSzLz1hbbG3djD4iIGf22bVzPbx7G+RplbsvMlcMo1wnL2m2MiDnAb4B/A15CVdeVdbnbgeaHDpvbYjSfqTHawKER0fzv/KJ67l1XFc3wKmm8ajkcVgfE4LuMG42/o/+SmTGE6QlP32fmUcA2VP2IfwY8RHVn+8PAf0fE68ao3o07qnu1GHKr0YcTqrC2f7+yI/n9dPN3Otjwap+iesDwVqp+wHMzc0ZmbpTVQ4zPato3Bvh5uM6hCsebU/Uxbgxb9gyqkQ5OH7ioNP4ZXiWNJ3dT3SkEaHdn8Kn1fKC7Xk9uU7ZxN/MxqofCxrPGq2U3i4iZbfccQGb+ITM/mZkvo7rTvA/V28OmAv9vpMcdSETswhMD2WD6j/na6Oc8nDvDjTKbDrMryKp6Pq3NPhsM43itHFjP35qZZ2Rm/yHINu5foDbSz0R9p/Zb9WJjBInD6vnZ6dvNVDjDq6S1qRFMW95VyswV9A2B1Ophnoa96vnvBti++wDrm7ddW59vPPtVPV+X6kGmUcnMlfUDb6+uV20INA/23/b3M0SNMHp+ffyBpsZ594yIzZvKNz7z84cxnNmv6/lU+q6NoWiEuKe22hgRk6numo5IRKxHX9eUKwfY7aUDrB/pZ2podB3YLyKeQl+ItsuAimd4lbQ2NZ6Ab/fg0Pfq+aL6iesnqAfsf0G9eOYAx5gfEQe1KDuHvoebzhq8ut2VmbfRN17ov7R74Kp+KGi95uU2h36EvoH0m7tnDOX3M6D6nG+sF8/KzOVtpmup/vMRVH1kG86juiM+HThuKOet2+k/68XjI6LdndRm19Tz3Qdo27czun7Rj1C9UACe+J8E4PHr8ahWBUfxmRrlbwQup7qr/F2qcYKXsvYfaJM6zvAqaW26rp7vFxEDfR37ReA2qvByQUTsDBARkyJif+CMer+fZeZA/xDfC3wtIv6+8QR3PeD7T6ke8roD+FL/QhGxXkTMbUz0BbspzesjYv1hferROZLq7VJPA34REQsbwbR+9eiCiPgQ1Vivza++/UFEfCUi9mp+KCoitgb+gyo0Lqd6mKjhBqpQu3lEvGQEdX0l1QD4qxjaAPhn1/PHRx2oh/46ul58Z0R8IyKeXtc9IuKpEfHuiDih37GOonoyf0fgoojYNSKiLjcnIvaLiO/3K/OfVG2wPvCd+g4lEbF+RBwJ/F/67s4OWz2ywuJ68UsR8bzo8yKqYcOmtznESD5Ts8bd18YwXN9oMwqHVI5uDzTr5OTUOxOwgL5Xm66kevJ/KXB5v/2eS9X/tTEIfON1so3l3wMbtTj+qfX2T1GNBZtUd7/ubSr7IPDiAep3bNN+7aZTR9kOezQda/4Q9n8xVf/eRpkVVC9beLRfvbZvKnNJ0/rVdXs+1LTuUeC1Lc71w6Z97ql/P0uBvYdQz0bZ/xzG9dA41wv6bfsET/xs/a+Bc1oc75VUQb+xz8N1ucby8hZlDu13nuVU4TuBzzH4SwravtCB6gG55jo8VF+Djc+0sGnb7E58pqay69H3utrHgM27/XeAk1MnJu+8Slprsvoq82VUr7G8F9iE6sGcp/bb7zdUD/18HvgDMJkqUCyhuhv1vMxsHmKov0ep+sz+H6oXFkyhCn9nADtl5n917lONvbq+zwA+TnWn9EGqr/YfpOob+Umq4Pr7pmLvoRrk/2dUY4lOo/q27Y9UL2rYPjPPaXG6N1G1+5+o7gpuUU/rtdj3cfULFV5eL57dbt+mz3UjcH29eGi/bcdQjXX6bapXnk6l+rxXUQ0BtsYLDDLzR8Az6/rfQBXaA/hvqgeYDmxR5ptU/Ykvq48/ieqBtoMz8wND+RyDfMZrqf4zdibVm8Mm1fNvUI1T/IuBS4/sMzWVfYi+bieLM3M4w49J41Zk+g2CpIkhIk6lCkGfyMxju1sbqbvqLjO3UP0n8aDMPGOQIvr/7d0hDgIxEAXQv8meAcdlUDhuhUOTcAkE18IgUUV0PaZJM5v3XJOKL38maYcSTF4BYJ8u6cX1neQ5OQsMo7wCwM5sK3qv2/HeWvvOzAMjrf+vAAAVLMvySHJOX8axpq9Svk0NBYOZvALAfhySHNN/KHglObXWPnMjwVgebAEAUIbJKwAAZSivAACUobwCAFCG8goAQBnKKwAAZfwAQ/C3bpOxNsQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(title=\"CondenseNet\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ResNeXt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "& resnext101\\_32x4d & 21.81 & 1.2247421658391497 \\\\\n",
      "& resnext101\\_64x4d & 21.04 & 1.3415310024058 \\\\\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_errors(\"ResNeXt\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "o"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " & resnet10 & 62.54 & 1.94 \\\\\n",
      " & resnet12 & 63.82 & 0.74 \\\\\n",
      " & resnet14 & 66.83 & 1.70 \\\\\n",
      " & resnet16 & 69.10 & 1.49 \\\\\n",
      " & resnet18_wd4 & 50.50 & 1.83 \\\\\n",
      " & resnet18_wd2 & 62.96 & 1.82 \\\\\n",
      " & resnet18_w3d4 & 66.39 & 0.28 \\\\\n",
      " & resnet18 & 70.48 & 1.09 \\\\\n",
      " & resnet34 & 74.34 & -0.42 \\\\\n",
      " & resnet50 & 76.21 & 0.13 \\\\\n",
      " & resnet50b & 76.95 & 0.09 \\\\\n",
      " & resnet101 & 78.10 & -0.67 \\\\\n",
      " & resnet101b & 78.55 & -0.92 \\\\\n",
      " & resnet152 & 78.74 & -1.11 \\\\\n",
      " & resnet152b & 79.26 & -1.74 \\\\\n"
     ]
    }
   ],
   "source": [
    "for fname in osmr.fixedname:\n",
    "    if fname.startswith('resnet'):\n",
    "        top1 = osmr[osmr['fixedname']==fname]['top1'].values[0]\n",
    "        top1_acc = 100.0-top1\n",
    "        w_alpha = np.average(alphas_4model[fname])\n",
    "                \n",
    "        print(\" & {0} & {1:0.2f} & {2:0.2f} \\\\\\\\\".format(fname, top1_acc, w_alpha))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_table_rows(title, fixednames=None, tops=[\"top1\"]):\n",
    "    print(title)\n",
    "    for top in tops:\n",
    "        \n",
    "        if fixednames is None:\n",
    "            fixednames = []\n",
    "            startstr = title.lower()\n",
    "\n",
    "            for fname in alphas_4model:\n",
    "                if fname.startswith(startstr):\n",
    "                    fixednames.append(fname)\n",
    "        \n",
    "        for fname in fixednames:\n",
    "                try:\n",
    "                    top_error = osmr[osmr['fixedname']==fname][top].values[0]\n",
    "                    avga = np.average(alphas_4model[fname])\n",
    "                    \n",
    "                    top_acc = 100.0-top_error\n",
    "                    table_line = \"& {0} & {1:0.2f} & {2:0.2f} \\\\\\\\\".format(fname.replace(\"_\",\"\\_\"), top_acc, avga)\n",
    "                    print(table_line)\n",
    "                except:\n",
    "                    pass\n",
    "    print(\"\\hline\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DenseNet\n",
      "& densenet121 & 74.43 & 1.25 \\\\\n",
      "& densenet161 & 77.14 & 0.84 \\\\\n",
      "& densenet169 & 75.60 & 0.68 \\\\\n",
      "& densenet201 & 76.90 & 0.50 \\\\\n",
      "\\hline\n",
      "SqueezeNet\n",
      "& squeezenet\\_v1\\_0 & 58.69 & 2.55 \\\\\n",
      "& squeezenet\\_v1\\_1 & 58.18 & 1.56 \\\\\n",
      "\\hline\n",
      "CondenseNet\n",
      "& condensenet74\\_c4\\_g4 & 73.75 & -1.83 \\\\\n",
      "& condensenet74\\_c8\\_g8 & 71.07 & -1.63 \\\\\n",
      "\\hline\n",
      "DPN\n",
      "& dpn68 & 75.83 & 0.57 \\\\\n",
      "& dpn98 & 79.19 & 0.11 \\\\\n",
      "& dpn131 & 79.46 & -0.13 \\\\\n",
      "\\hline\n",
      "ShuffleNet\n",
      "& shufflenetv2\\_wd2 & 58.52 & 5.12 \\\\\n",
      "& shufflenetv2\\_w1 & 65.61 & 2.86 \\\\\n",
      "\\hline\n",
      "MobileNet\n",
      "& mobilenet\\_wd4 & 53.74 & 5.54 \\\\\n",
      "& mobilenet\\_wd2 & 63.70 & 4.26 \\\\\n",
      "& mobilenet\\_w3d4 & 66.46 & 4.41 \\\\\n",
      "& mobilenet\\_w1 & 70.14 & 4.19 \\\\\n",
      "& mobilenetv2\\_wd4 & 50.28 & 12.12 \\\\\n",
      "& mobilenetv2\\_wd2 & 63.46 & 4.69 \\\\\n",
      "& mobilenetv2\\_w3d4 & 68.11 & 4.21 \\\\\n",
      "& mobilenetv2\\_w1 & 70.69 & 3.50 \\\\\n",
      "\\hline\n",
      "SEResNet\n",
      "& seresnet50 & 77.53 & -0.35 \\\\\n",
      "& seresnet101 & 78.12 & -1.24 \\\\\n",
      "& seresnet152 & 78.52 & -1.53 \\\\\n",
      "\\hline\n",
      "SEResNeXt\n",
      "& seresnext50\\_32x4d & 79.00 & 1.81 \\\\\n",
      "& seresnext101\\_32x4d & 80.04 & 0.76 \\\\\n",
      "\\hline\n"
     ]
    }
   ],
   "source": [
    "print_table_rows(title=\"DenseNet\")\n",
    "print_table_rows(title=\"SqueezeNet\")\n",
    "print_table_rows(title=\"CondenseNet\")\n",
    "print_table_rows(title=\"DPN\")\n",
    "print_table_rows(title=\"ShuffleNet\")\n",
    "print_table_rows(title=\"MobileNet\")\n",
    "print_table_rows(title=\"SEResNet\")\n",
    "print_table_rows(title=\"SEResNeXt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ResNeXt\n",
      "& resnext101\\_32x4d & 78.19 & 1.22 \\\\\n",
      "& resnext101\\_64x4d & 78.96 & 1.34 \\\\\n",
      "\\hline\n",
      "MeNet\n",
      "& menet108\\_8x1\\_g3 & 56.08 & 5.31 \\\\\n",
      "& menet128\\_8x1\\_g4 & 56.05 & 4.46 \\\\\n",
      "& menet228\\_12x1\\_g3 & 66.43 & 4.82 \\\\\n",
      "& menet256\\_12x1\\_g4 & 66.59 & 4.97 \\\\\n",
      "& menet348\\_12x1\\_g3 & 69.90 & 5.74 \\\\\n",
      "& menet352\\_12x1\\_g8 & 66.69 & 4.42 \\\\\n",
      "& menet456\\_24x1\\_g3 & 71.60 & 5.11 \\\\\n",
      "\\hline\n",
      "FDMobileNet\n",
      "& fdmobilenet\\_wd4 & 44.23 & 6.40 \\\\\n",
      "& fdmobilenet\\_wd2 & 56.15 & 7.01 \\\\\n",
      "& fdmobilenet\\_w1 & 65.30 & 7.10 \\\\\n",
      "\\hline\n"
     ]
    }
   ],
   "source": [
    "print_table_rows(title=\"ResNeXt\")\n",
    "print_table_rows(title=\"MeNet\")\n",
    "print_table_rows(title=\"FDMobileNet\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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