cudavision4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch._C.Generator at 0x7fcd2ba8cb70>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Gautam Jain, Jannis Horn \n",
    "\n",
    "#%matplotlib notebook\n",
    "import time\n",
    "from typing import Tuple\n",
    "from collections import OrderedDict\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.use('Agg')\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "import torch  \n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as func\n",
    "import torch.optim as topt\n",
    "import wandb\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    device = torch.device(\"cuda\")\n",
    "else:\n",
    "    device = torch.device(\"cpu\")\n",
    "\n",
    "torch.manual_seed( 666 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n",
      "Input Shape: torch.Size([3, 32, 32])\n",
      "Training Set: 50000, Test Set: 10000\n"
     ]
    }
   ],
   "source": [
    "import torchvision.datasets as dsets\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "trainset = dsets.CIFAR10('./data', train=True, download=True, transform=transforms.ToTensor())\n",
    "testset = dsets.CIFAR10('./data', train=False, download=True, transform=transforms.ToTensor())\n",
    "\n",
    "print( \"Input Shape: {}\".format( trainset[0][0].shape ) )\n",
    "print( \"Training Set: {}, Test Set: {}\".format( len(trainset), len(testset) ) )\n",
    "\n",
    "#print( trainset[0][0] )\n",
    "\n",
    "dim_in = tuple(trainset[0][0].shape)\n",
    "dim_out = 10\n",
    "dt_dims = (dim_in, dim_out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "\n",
    "current_cmap = copy.copy( matplotlib.cm.get_cmap() )\n",
    "current_cmap.set_bad(color='white')\n",
    "\n",
    "def flattenConvVols( vol ):\n",
    "    \"\"\" Flatten 3D Volume along 0 axis and concat with whitespace \"\"\"\n",
    "    m = int(np.ceil(np.sqrt( vol.shape[0] )))\n",
    "    out = torch.full( [vol.shape[1]*m+m-1, vol.shape[2]*m+m-1], np.nan )\n",
    "    x_it = 0\n",
    "    y_it = 0\n",
    "    for it in range( vol.shape[0] ):\n",
    "        x_st = x_it *vol.shape[1] +x_it\n",
    "        y_st = y_it *vol.shape[2] +y_it\n",
    "        out[x_st:x_st+vol.shape[1],y_st:y_st+vol.shape[2]] = vol[it,:,:]\n",
    "        y_it += 1\n",
    "        if y_it >= m:\n",
    "            y_it = 0\n",
    "            x_it += 1\n",
    "    return out\n",
    "\n",
    "def flattenConvWeight( vol ):\n",
    "    \"\"\" Flatten 4D Volume to rows to 2D \"\"\"\n",
    "    out = torch.full( [(vol.shape[2]+3)*vol.shape[0]-1, (vol.shape[3]+1)*vol.shape[1]-1], np.nan )\n",
    "    for x_it in range( vol.shape[0] ):\n",
    "        for y_it in range( vol.shape[1] ):\n",
    "            x_st = x_it *vol.shape[2] +3*x_it\n",
    "            y_st = y_it *vol.shape[3] +y_it\n",
    "            out[x_st:x_st+vol.shape[2],y_st:y_st+vol.shape[3]] = vol[x_it,y_it,:,:]\n",
    "    return out\n",
    "    \n",
    "\n",
    "def convVolsAsFigure( vol ):\n",
    "    \"\"\" Create 2D Image from 3D input volume and add a colorbar \"\"\"\n",
    "    m = int(np.ceil(np.sqrt( vol.shape[0] )))\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=1)\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    ax.axis('off')\n",
    "    if vol.dim() == 3: \n",
    "        a = flattenConvVols( vol )\n",
    "        fig.set_size_inches( 0.075*a.shape[1]+2, 0.075*a.shape[0] )\n",
    "    elif vol.dim() == 4: \n",
    "        a = flattenConvWeight( vol )\n",
    "        fig.set_size_inches( 0.15*a.shape[1]+2, 0.15*a.shape[0] )\n",
    "    im = ax.imshow( a, cmap=current_cmap )\n",
    "    divider = make_axes_locatable(ax)\n",
    "    cax = divider.append_axes('right', size='5%', pad=0.1)\n",
    "    fig.colorbar( im, cax=cax )\n",
    "    return fig\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def logTraining( epoch, train_loss, time ):\n",
    "    \"\"\" Log training results \"\"\"\n",
    "    wandb.log( {\"train_loss\": train_loss, \n",
    "                \"train_time\": time}, step=epoch )\n",
    "    \n",
    "def logTest( epoch, test_loss, acc, conf_mat, time ):\n",
    "    \"\"\" Log information gathered from testing \"\"\"\n",
    "    wandb.log( {\"test_loss\": test_loss,\n",
    "                \"accuracy\": acc, \n",
    "                \"conf_mat\": [wandb.Image(conf_mat, caption=\"Confussion Matrix\")],\n",
    "                \"test_time\": time},\n",
    "               step=epoch)\n",
    "    \n",
    "def logNetData( epoch, acts, weights, grads ):\n",
    "    \"\"\" Log images for net activation, weights and grads.\n",
    "    \n",
    "    For each element in given dictionaries create a figure and log image\n",
    "    \"\"\"\n",
    "    ims = {}\n",
    "    for k, a in acts.items():\n",
    "        f = convVolsAsFigure(a[0,:,:,:])\n",
    "        ims[\"act_{}\".format(k)] = wandb.Image(f, caption=k)\n",
    "        plt.close(f)\n",
    "    for k, w in weights.items():\n",
    "        f = convVolsAsFigure(w[:,:,:,:])\n",
    "        ims[\"w_{}\".format(k)] = wandb.Image(f, caption=k)\n",
    "        plt.close(f)\n",
    "    for k, g in grads.items():\n",
    "        f = convVolsAsFigure(g[:,:,:,:])\n",
    "        ims[\"grad_{}\".format(k)] = wandb.Image(f, caption=k)\n",
    "        plt.close(f)\n",
    "    wandb.log( ims, step=epoch )\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hook taken from https://discuss.pytorch.org/t/how-can-l-load-my-best-model-as-a-feature-extractor-evaluator/17254/6\n",
    "\n",
    "class MaxAvgPool2d( nn.Module ):\n",
    "    def __init__( self, ksize, stride=None, padding=0 ):\n",
    "        super( MaxAvgPool2d, self ).__init__()\n",
    "        self.mpool = nn.MaxPool2d( ksize, stride, padding )\n",
    "        self.apool = nn.AvgPool2d( ksize, stride, padding )\n",
    "        self.kernel_size = ksize\n",
    "    \n",
    "    def forward( self, x ):\n",
    "        x1 = self.mpool( x )\n",
    "        x2 = self.apool( x )\n",
    "        return torch.cat((x1, x2), dim=1)\n",
    "\n",
    "\n",
    "    \n",
    "class ConvNet( nn.Module ):\n",
    "    \"\"\"\n",
    "    Wrapper for convolutional neural network.\n",
    "    \n",
    "    Holds layers, hooks for interlayer inputs/outputs.\n",
    "    Computes norms and creates wandb config\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__( self, c_layers, l_layers, map_size ):\n",
    "        super( ConvNet, self ).__init__()\n",
    "        self.conv_layers = c_layers\n",
    "        self.lin_layers = l_layers\n",
    "        self.lin_inp_dim = l_layers[0][0].in_features\n",
    "        self.map_size = map_size\n",
    "        self.gradients = {}\n",
    "        self.activations = {}\n",
    "        self.weights = {}\n",
    "        self.collect = False\n",
    "        \n",
    "    \n",
    "    def save( self, f ):\n",
    "        torch.save(self.state_dict(), \"{}.th\".format(f))\n",
    "        \n",
    "    def load( self, f ):\n",
    "        self.load_state_dict(torch.load( \"{}.th\".format(f) ))\n",
    "        \n",
    "    def hook( self, hook, seq, name ):\n",
    "        def getActivationHook( model, input, output ):\n",
    "            if self.collect: self.activations[name] = output.detach().to( \"cpu\" )\n",
    "        def getWeightHook( model, input, output ):\n",
    "            if self.collect: self.weights[name] = model.weight.detach().to( \"cpu\" )\n",
    "        def getGradientHook( model, grad_input, grad_output ):\n",
    "            if self.collect: self.gradients[name] = grad_output.detach().to( \"cpu\" )\n",
    "        if hook in [1,3,5,7]:\n",
    "            seq[0].register_forward_hook( getActivationHook )\n",
    "        if hook in [2,3,6,7]:\n",
    "            seq[0].register_backward_hook( getGradientHook )\n",
    "        if hook in [4,5,6,7]:\n",
    "            seq[0].register_forward_hook( getWeightHook )\n",
    "        \n",
    "    def hookAll( self, hooks ):\n",
    "        for it, l in enumerate(self.conv_layers):\n",
    "            self.hook( hooks[0], l, \"conv{}\".format(it) )\n",
    "        for it, l in enumerate(self.conv_layers):\n",
    "            self.hook( hooks[1], l, \"lin{}\".format(it) )\n",
    "        \n",
    "    \n",
    "    def forward( self, x ):\n",
    "        for layer in self.conv_layers:\n",
    "            x = layer(x)\n",
    "        x = x.view( -1, self.lin_inp_dim )\n",
    "        for layer in self.lin_layers:\n",
    "            x = layer(x)\n",
    "        return x\n",
    "    \n",
    "    \n",
    "    def getL1Norm( self ):\n",
    "        n = torch.tensor( 0.0 ).to( device )\n",
    "        for l in self.conv_layers:\n",
    "            n += l[0].weight.abs().sum()\n",
    "        for l in self.lin_layers[:-1]:\n",
    "            n += l[0].weight.abs().sum()\n",
    "        n += self.lin_layers[-1].weight.abs().sum()\n",
    "        return n\n",
    "    \n",
    "    def getL2Norm( self ):\n",
    "        n = torch.tensor( 0.0 ).to( device )\n",
    "        for l in self.conv_layers:\n",
    "            n += l[0].weight.square().sum()\n",
    "        for l in self.lin_layers[:-1]:\n",
    "            n += l[0].weight.square().sum()\n",
    "        n += self.lin_layers[-1].weight.square().sum()\n",
    "        return n\n",
    "    \n",
    "    \n",
    "    def getLayer( self, key, it ):\n",
    "        if key == \"c\":\n",
    "            return self.conv_layers[it][0]\n",
    "        elif key == \"l\":\n",
    "            return self.lin_layers[it][0]\n",
    "    \n",
    "    def getGradientNorm( self, norm=2 ):\n",
    "        out = {}\n",
    "        for key, val in self.gradients:\n",
    "            out[key] = val.norm( norm )\n",
    "            \n",
    "    def getActivations( self ):\n",
    "        return self.activations\n",
    "    \n",
    "    def getWeights( self, key, it ):\n",
    "        if key == \"c\":\n",
    "            return self.conv_layers[it][0].weight.detach()\n",
    "        if key == \"l\":\n",
    "            return self.lin_layers[it][0].weight.detach()\n",
    "        return None\n",
    "    \n",
    "    def setWeights( self, key, it, ws ):\n",
    "        with torch.no_grad():\n",
    "            if key == \"c\":\n",
    "                self.conv_layers[it][0].weight = nn.Parameter( torch.reshape( ws, self.conv_layers[it][0].weight.shape ) )\n",
    "            elif key == \"l\":\n",
    "                self.lin_layers[it][0].weight = nn.Parameter( torch.reshape( ws, self.lin_layers[it][0].weight.shape ) )\n",
    "     \n",
    "    \n",
    "    def setFromLayer( self, key, it, ol ):\n",
    "        if key == \"c\":\n",
    "            self._resetConvLayer( it, ol )\n",
    "        elif key == \"l\":\n",
    "            self._resetLinLayer( it, ol )\n",
    "            \n",
    "    def _resetConvLayer( self, it, ol ):\n",
    "        with torch.no_grad():\n",
    "            self.conv_layers[it][0].weight = nn.Parameter( ol.weight.detach() )\n",
    "            self.conv_layers[it][0].bias = nn.Parameter( ol.bias.detach() )\n",
    "            \n",
    "    def _resetLinLayer( self, it, ol ):\n",
    "        with torch.no_grad():\n",
    "            self.lin_layers[it][0].weight = nn.Parameter( ol.weight.detach() )\n",
    "            self.lin_layers[it][0].bias = nn.Parameter( ol.bias.detach() )        \n",
    "    \n",
    "    def paramOut( self ):\n",
    "        self.collect = True\n",
    "    \n",
    "    def wandbConfig( self ):\n",
    "        wandb.config.conv_layers = len(self.conv_layers)\n",
    "        wandb.config.lin_layers = len(self.lin_layers)\n",
    "        for it, seq in enumerate(self.conv_layers):\n",
    "            self.convToParamSet( it, seq )\n",
    "        for it, seq in enumerate(self.lin_layers):\n",
    "            self.linToParamSet( it, seq )\n",
    "            \n",
    "    def convToParamSet( self, it, seq ):\n",
    "        def wandbConfig( name, it, key, val ):\n",
    "            wandb.config.update( {\"{}{}_{}\".format(name, it, key): val} )\n",
    "            \n",
    "        for name, mod in seq.named_modules():\n",
    "            if \"conv\" in name:\n",
    "                wandbConfig( name, it, \"ch_out\", mod.out_channels )\n",
    "                wandbConfig( name, it, \"ksize\", mod.kernel_size )\n",
    "                wandbConfig( name, it, \"stride\", mod.stride )\n",
    "                wandbConfig( name, it, \"pad\", mod.padding )\n",
    "            elif \"pool\" in name:\n",
    "                if isinstance( mod, nn.MaxPool2d ): pt = \"max\"\n",
    "                elif isinstance( mod, nn.AvgPool2d ): pt = \"avg\"\n",
    "                elif isinstance( mod, MaxAvgPool2d ): pt = \"both\"\n",
    "                wandbConfig( name, it, \"pool_type\", pt )\n",
    "                wandbConfig( name, it, \"pool_ks\", mod.kernel_size )\n",
    "            elif \"drop\" in name:\n",
    "                wandb.config.update( {\"{}_conv{}\".format(name,it): mod.p} )\n",
    "            elif \"act\" in name:\n",
    "                wandb.config.update( {\"{}_conv{}\".format(name,it): mod} )\n",
    "                \n",
    "    def linToParamSet( self, it, seq ):\n",
    "        for name, mod in seq.named_modules():\n",
    "            if \"lin\" in name:\n",
    "                wandb.config.update( {\"{}{}\".format(name,it): mod.out_features} )\n",
    "            if \"act\" in name:\n",
    "                wandb.config.update( {\"{}_lin{}\".format(name,it): mod} )\n",
    "            if \"drop\" in name:\n",
    "                wandb.config.update( {\"{}_lin{}\".format(name,it): mod.p} )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 16.0, 16.0)\n",
      "(16, 8.0, 8.0)\n",
      "(16, 4.0, 4.0)\n",
      "256\n",
      "(16, 16.0, 16.0)\n",
      "(32, 8.0, 8.0)\n",
      "(16, 4.0, 4.0)\n",
      "256\n",
      "256\n",
      "ConvNet(\n",
      "  (conv_layers): ModuleList(\n",
      "    (0): Sequential(\n",
      "      (conv): Conv2d(3, 16, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (1): Sequential(\n",
      "      (conv): Conv2d(16, 16, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (2): Sequential(\n",
      "      (conv): Conv2d(16, 16, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "  )\n",
      "  (lin_layers): ModuleList(\n",
      "    (0): Sequential(\n",
      "      (lin): Linear(in_features=256, out_features=256, bias=True)\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (1): Linear(in_features=256, out_features=10, bias=True)\n",
      "  )\n",
      ") [(3, 32, 32), (16, 16.0, 16.0), (16, 8.0, 8.0), (16, 4.0, 4.0), 256, 10]\n",
      "ConvNet(\n",
      "  (conv_layers): ModuleList(\n",
      "    (0): Sequential(\n",
      "      (conv): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (1): Sequential(\n",
      "      (conv): Conv2d(16, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (2): Sequential(\n",
      "      (conv): Conv2d(32, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "  )\n",
      "  (lin_layers): ModuleList(\n",
      "    (0): Sequential(\n",
      "      (lin): Linear(in_features=256, out_features=256, bias=True)\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (1): Sequential(\n",
      "      (lin): Linear(in_features=256, out_features=256, bias=True)\n",
      "      (drop): Dropout(p=0.2, inplace=False)\n",
      "      (act): ReLU()\n",
      "    )\n",
      "    (2): Linear(in_features=256, out_features=10, bias=True)\n",
      "  )\n",
      ") [(3, 32, 32), (16, 16.0, 16.0), (32, 8.0, 8.0), (16, 4.0, 4.0), 256, 256, 10]\n"
     ]
    }
   ],
   "source": [
    "class Config():\n",
    "    \"\"\"\n",
    "    Wrapper to convert lists or dictionaries to constructor tokens\n",
    "    \n",
    "    Parse lists and dictionaries of different parameters\n",
    "    Generate tokenset for unified construction\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, dt_dims ):\n",
    "        super().__init__()\n",
    "        self.dts_dims = dt_dims\n",
    "        self.num_c = 0\n",
    "        self.num_l = 0\n",
    "        self.ps_c = []\n",
    "        self.ps_l = []\n",
    "\n",
    "    @classmethod \n",
    "    def fromList( cls, dt_dims, ilist ):\n",
    "        out = cls( dt_dims )\n",
    "        out.parseList( ilist )\n",
    "        return out\n",
    "\n",
    "    @classmethod\n",
    "    def fromDict( cls, dt_dims, idict ):\n",
    "        out = cls( dt_dims )\n",
    "        out.parseDict( idict )\n",
    "        return out\n",
    "\n",
    "    def parseDict( self, idict ):\n",
    "        def ifInDict( key, default ):\n",
    "            if key in idict:\n",
    "                return idict[key]\n",
    "            else:\n",
    "                return default\n",
    "\n",
    "        act_f = ifInDict( \"act\", \"relu\" )\n",
    "        dp_f = ifInDict( \"dp\", 0.0 )\n",
    "        if \"num_c\" in idict:\n",
    "            out_c = ifInDict( \"out_c\", None )\n",
    "            ksize_c = ifInDict( \"ksize\", None )\n",
    "            act_c = ifInDict( \"act_c\", act_f )\n",
    "            stride_c = ifInDict( \"stride\", 1 )\n",
    "            pad_c = ifInDict( \"pad\", False )\n",
    "            pool_c = ifInDict( \"pool\", (\"max\", 1) )\n",
    "            dp_c = ifInDict( \"dp_c\", dp_f )\n",
    "            for it in range(idict[\"num_c\"]):\n",
    "                out = ifInDict( \"out_c_{}\".format(it), out_c )\n",
    "                ksize = ifInDict( \"ksize_{}\".format(it), ksize_c )\n",
    "                act = ifInDict( \"act_c_{}\".format(it), act_c )\n",
    "                stride = ifInDict( \"stride_{}\".format(it), stride_c )\n",
    "                pad = ifInDict( \"pad_{}\".format(it), pad_c )\n",
    "                pool = ifInDict( \"pool_{}\".format(it), pool_c )\n",
    "                dp = ifInDict( \"dp_c_{}\".format(it), dp_c )\n",
    "                self.addConvLayer( out, ksize, act, stride, pad, pool, dp )\n",
    "        if \"num_l\" in idict:\n",
    "            out_l = ifInDict( \"out_l\", None )\n",
    "            act_l = ifInDict( \"act_l\", act_f )\n",
    "            dp_l = ifInDict( \"dp_l\", dp_f )\n",
    "            for it in range( idict[\"num_l\"] ):\n",
    "                out = ifInDict( \"out_l_{}\", out_l )\n",
    "                act = ifInDict( \"act_l_{}\", act_l )\n",
    "                dp_l = ifInDict( \"dp_l_{}\", dp_l )\n",
    "                self.addLinearLayer( out, act, dp_l )\n",
    "\n",
    "\n",
    "    def parseList( self, ilist ):\n",
    "        def ifIt( obj, it, default ):\n",
    "            if len(obj) > it: return obj[it]\n",
    "            else: return default\n",
    "\n",
    "        for tp in ilist:\n",
    "            #Convolutional Parameters: [\"c\",ch_out,ksize,act_str,stride*,pad*,pool*,dropout*]\n",
    "            if tp[0] == \"c\":\n",
    "                self.addConvLayer( tp[1], tp[2], tp[3], ifIt(tp,4,1), ifIt(tp,5,0),\n",
    "                                   ifIt(tp,6,(\"max\",1)), ifIt(tp,7,0.0) )\n",
    "            #Linear Parameters: [\"l\",size_out,act_str,dropout*]\n",
    "            elif tp[0] == \"l\":\n",
    "                self.addLinearLayer( tp[1], tp[2], ifIt(tp,3,0.0) )\n",
    "\n",
    "\n",
    "\n",
    "    def addConvLayer( self, ch_out: int, k_s: int, act: str, stride: int, pad: bool, \n",
    "                      pool: Tuple[str, int], dropout: float ):\n",
    "        self.num_c += 1\n",
    "        self.ps_c.append( {\"out\":ch_out, \"ksize\":k_s, \"act\":act, \"str\":stride, \n",
    "                           \"pad\":pad, \"pool\":pool, \"dp\":dropout} )\n",
    "\n",
    "    def addLinearLayer( self, s_out: int, act: str, dropout: int ):\n",
    "        self.num_l += 1\n",
    "        self.ps_l.append( {\"out\":s_out, \"act\":act, \"dp\":dropout} )\n",
    "\n",
    "        \n",
    "    def changeConv( self, key, params ):\n",
    "        if key in self.ps_c[0]:\n",
    "            for it, p in enumerate(params):\n",
    "                if p is not None:\n",
    "                    self.ps_c[it][key] = p\n",
    "                \n",
    "    def changeLin( self, key, params ):\n",
    "        if key in self.ps_l[0]:\n",
    "            for it, p in enumerate(params):\n",
    "                if p is not None:\n",
    "                    self.ps_l[it][key] = p\n",
    "        \n",
    "\n",
    "    def __getitem__( self, it ):\n",
    "        if it < self.num_c:\n",
    "            return self.ps_c[it]\n",
    "        else:\n",
    "            return self.ps_l[it-num_c] \n",
    "\n",
    "\n",
    "class Constructor:\n",
    "    \"\"\"\n",
    "    Given config create layers for ConvNet\n",
    "    \"\"\"\n",
    "    def __call__( self, net_type, config ):\n",
    "        conv_layers = nn.ModuleList()\n",
    "        lin_layers = nn.ModuleList()\n",
    "        map_size = []\n",
    "        dim_in = config.dts_dims[0]\n",
    "        map_size.append( dim_in )\n",
    "        for ps in config.ps_c:\n",
    "            l, dim_in = self.buildConvLayer( dim_in, ps )\n",
    "            conv_layers.append( l )\n",
    "            map_size.append( dim_in )\n",
    "            print(dim_in)\n",
    "        dim_in = np.array(dim_in, dtype=np.int).prod().item()\n",
    "        for ps in config.ps_l:\n",
    "            l, dim_in = self.buildLinLayer( dim_in, ps )\n",
    "            lin_layers.append( l )\n",
    "            map_size.append( dim_in )\n",
    "            print(dim_in)\n",
    "        lin_layers.append( nn.Linear( dim_in, config.dts_dims[1] ) )\n",
    "        map_size.append( config.dts_dims[1] )\n",
    "        return net_type( conv_layers, lin_layers, map_size )\n",
    "\n",
    "    def buildConvLayer( self, d_in, params ):\n",
    "        out = OrderedDict()\n",
    "        if params[\"pad\"]: pad = int((params[\"ksize\"]-1) /2)\n",
    "        else: pad = 0\n",
    "        out[\"conv\"] = nn.Conv2d( d_in[0], params[\"out\"], params[\"ksize\"], params[\"str\"], padding=pad )\n",
    "        if params[\"dp\"] > 0.0:\n",
    "            out[\"drop\"] = nn.Dropout( params[\"dp\"] )\n",
    "        pl = params[\"pool\"]\n",
    "        m = 1\n",
    "        if pl[1] > 1:\n",
    "            pool, m = self.strToPool( pl[0] )\n",
    "            out[\"pool\"] = pool( pl[1] )\n",
    "        out[\"act\"] = self.strToAct( params[\"act\"] )()\n",
    "        toNewSize = lambda x : (x-params[\"ksize\"]+1 +pad*2) /params[\"str\"] / pl[1]\n",
    "        d_out = (params[\"out\"]*m, toNewSize(d_in[1]), toNewSize(d_in[2]))\n",
    "        return nn.Sequential( out ), d_out\n",
    "\n",
    "    def buildLinLayer( self, s_in, params ):\n",
    "        out = OrderedDict()\n",
    "        out[\"lin\"] = nn.Linear( s_in, params[\"out\"] )\n",
    "        if params[\"dp\"] > 0.0:\n",
    "            out[\"drop\"] = nn.Dropout( params[\"dp\"] )\n",
    "        out[\"act\"] = self.strToAct( params[\"act\"] )()\n",
    "        return nn.Sequential( out ), params[\"out\"]\n",
    "\n",
    "    def strToAct( self, act_str ):\n",
    "        if act_str in [\"relu\", \"ReLU\"]:\n",
    "            return nn.ReLU\n",
    "        elif act_str in [\"sig\", \"sigmoid\", \"Sigmoid\"]:\n",
    "            return nn.Sigmoid\n",
    "        elif act_str in [\"tanh\", \"Tanh\"]:\n",
    "            return nn.Tanh\n",
    "        else:\n",
    "            raise RuntimeError( \"Unknown act_str\" )\n",
    "\n",
    "    def strToPool( self, p_str ):\n",
    "        if p_str == \"max\": \n",
    "            return nn.MaxPool2d, 1\n",
    "        elif p_str == \"avg\": \n",
    "            return nn.AvgPool2d, 1\n",
    "        elif p_str == \"both\":\n",
    "            return MaxAvgPool2d, 2\n",
    "        else:\n",
    "            raise RuntimeError( \"Unknown p_str\" )\n",
    "            \n",
    "llist = [[\"c\",16,5,\"relu\",1,True,(\"max\",2)]]*3 +[[\"l\",256,\"relu\",0.2]]\n",
    "ldict = {\"num_c\": 3, \"num_l\":2, \"act\":\"relu\", \"dp\":0.2, \"ksize\":3, \"pool\":(\"max\",2), \n",
    "         \"out_c\":16, \"out_c_1\":32, \"out_l\":256, \"pad\":True}\n",
    "cfg = Config.fromList( dt_dims, llist )\n",
    "cstr = Constructor()\n",
    "test_net = cstr( ConvNet, cfg )\n",
    "test_net_2 = cstr( ConvNet, Config.fromDict(dt_dims,ldict) )\n",
    "print(test_net, test_net.map_size)\n",
    "print(test_net_2, test_net_2.map_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Runner:\n",
    "    \"\"\"\n",
    "    Wrapper for network training\n",
    "    \n",
    "    Combines training -> testing and logging\n",
    "    \"\"\"\n",
    "    def __init__( self, project_name, entity=\"cudavisionlab\" ):\n",
    "        self.pr_name = project_name\n",
    "        self.entity = entity\n",
    "    \n",
    "    def wandbConfig( self ):\n",
    "        self.model.wandbConfig()\n",
    "        wandb.config.optimizer = self.optimizer\n",
    "        wandb.config.regularizer = \"lambdas={}\".format( self.reg_w )\n",
    "        wandb.config.dataset = \"Cifar10\"\n",
    "    \n",
    "    \n",
    "    def initRun( self, model, batch_size, dev, opt, lr, momentum, reg ):\n",
    "        self.model = model\n",
    "        self.dev = dev\n",
    "        self.model.to( dev )\n",
    "        if opt in [topt.Adagrad, topt.Adadelta, topt.Adam]:\n",
    "            self.optimizer = opt( model.parameters(), lr=lr )\n",
    "        else:\n",
    "            self.optimizer = opt( model.parameters(), lr=lr, momentum=momentum )\n",
    "        self.loss_func = nn.CrossEntropyLoss().to( dev )\n",
    "        self.reg_w = torch.Tensor([reg[0], reg[1]]).to( dev )\n",
    "        self.tr_size = len( trainset )\n",
    "        self.te_size = len( testset )\n",
    "        self.loader_training = torch.utils.data.DataLoader( dataset=trainset, \n",
    "                                                            batch_size=batch_size, \n",
    "                                                            shuffle=True,\n",
    "                                                            num_workers=2 )\n",
    "        self.loader_eval = torch.utils.data.DataLoader( dataset=testset, \n",
    "                                                        batch_size=batch_size, \n",
    "                                                        shuffle=False,\n",
    "                                                        num_workers=2 )\n",
    "        \n",
    "    def initHooks( self, vis_cfg ):\n",
    "        c_hook, l_hook = 0,0\n",
    "        for c in vis_cfg[\"act\"]:\n",
    "            if c == \"c\": c_hook += 1\n",
    "            elif c == \"l\": l_hook += 1\n",
    "        for c in vis_cfg[\"grad\"]:\n",
    "            if c == \"c\": c_hook += 2\n",
    "            elif c == \"l\": l_hook += 2\n",
    "        for c in vis_cfg[\"weight\"]:\n",
    "            if c == \"c\": c_hook += 4\n",
    "            elif c == \"l\": l_hook += 4\n",
    "        self.model.hookAll( (c_hook, l_hook) )\n",
    "                \n",
    "    \n",
    "    def testModel( self ):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            st_pt = time.time()\n",
    "            conv_mat = np.zeros([10,10])\n",
    "            corr = 0\n",
    "            bt_loss = 0.0\n",
    "            for (x, label) in self.loader_eval:\n",
    "                #x = x.view( -1, dim_in ).to( self.dev )\n",
    "                x = x.to( self.dev )\n",
    "                label = label.to( self.dev )\n",
    "                out = self.model(x)\n",
    "                loss = self.loss_func( out, label )\n",
    "                bt_loss += loss.cpu().item()\n",
    "                \n",
    "                _, pred = torch.max( out.data, 1 )\n",
    "                ls = label.cpu().numpy()\n",
    "                pr = pred.cpu().numpy()\n",
    "                for it in range( label.size(0) ):\n",
    "                    conv_mat[ls[it], pr[it]] += 1\n",
    "                corr += (pred.cpu() == label.cpu()).sum().float()\n",
    "                \n",
    "            ts_time = time.time() -st_pt\n",
    "        return bt_loss /len( self.loader_eval ), corr/self.te_size, 10*conv_mat/self.te_size, ts_time\n",
    "\n",
    "        \n",
    "    def trainModel( self ):\n",
    "        self.model.train()\n",
    "        st_pt = time.time()\n",
    "        bt_loss = 0.0\n",
    "        for it, (x, label) in enumerate( self.loader_training ):\n",
    "            self.optimizer.zero_grad()\n",
    "            #x = x.view(-1,dim_in).to( self.dev )\n",
    "            x = x.to( self.dev )\n",
    "            label = label.to( self.dev )\n",
    "\n",
    "            out = self.model(x)\n",
    "            loss = self.loss_func(out, label)\n",
    "            norm_1 = self.model.getL1Norm()\n",
    "            norm_2 = self.model.getL2Norm()\n",
    "            loss += self.reg_w[0] *norm_1 + self.reg_w[1] *norm_2\n",
    "            loss.backward()\n",
    "            bt_loss += loss.cpu().item()\n",
    "\n",
    "            self.optimizer.step()\n",
    "\n",
    "        tr_time = time.time() -st_pt\n",
    "        return bt_loss /len( self.loader_training ), tr_time\n",
    "    \n",
    "    \n",
    "    def __call__( self, model, config, vis_cfg, num_epoch, im_int, key=\"\", load=None ):\n",
    "        run = wandb.init( project=self.pr_name, entity=self.entity, name=key, reinit=True )\n",
    "        if load is not None:\n",
    "            model.load( load )\n",
    "        with run:\n",
    "            self.initRun( model, config[\"bs\"], config[\"dev\"], \n",
    "                          config[\"opt\"], config[\"lr\"], config[\"mom\"],\n",
    "                          config[\"reg\"] )\n",
    "            self.initHooks( vis_cfg )\n",
    "            self.wandbConfig()\n",
    "            e_it = 0\n",
    "            for epoch in range(num_epoch):\n",
    "                e_it += 1\n",
    "                if e_it % im_int == 0:\n",
    "                    self.model.collect = True\n",
    "                tr_l, tr_time = self.trainModel()\n",
    "                logTraining( epoch, tr_l, tr_time )\n",
    "                ts_l, acc, cmat, ts_time = self.testModel()\n",
    "                logTest( epoch, ts_l, acc, cmat, ts_time )\n",
    "                if e_it % im_int == 0:\n",
    "                    self.model.collect = False\n",
    "                    logNetData( epoch, self.model.activations, self.model.weights, self.model.gradients )\n",
    "                print( \"{}/{}\".format( e_it, num_epoch ), end='\\r' )\n",
    "        if key != \"\":\n",
    "            self.model.save( key )\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "runner = Runner( \"cudavision4\" )\n",
    "cfg = { \"bs\": 5000, \"dev\": device, \"opt\": topt.Adam, \n",
    "        \"lr\": 2*10e-5, \"mom\": 0.5, \"reg\": (10e-5, 10e-4) }\n",
    "vis_cfg = { \"act\":\"c\", \"grad\":\"\", \"weight\":\"c\" }\n",
    "\n",
    "ldict = {\"num_c\": 3, \"num_l\":2, \"act\":\"relu\", \"dp\":0.2, \"ksize\":3, \"pool\":(\"both\",2), \n",
    "         \"out_c\": 32, \"out_c_1\":64, \"out_c_2\":128, \"out_l\":256, \"pad\":True}\n",
    "\n",
    "cstr = Constructor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "                Tracking run with wandb version 0.10.12<br/>\n",
       "                Syncing run <strong style=\"color:#cdcd00\">c_64_128_256</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
       "                Project page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4</a><br/>\n",
       "                Run page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/3g1rgfyp\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/3g1rgfyp</a><br/>\n",
       "                Run data is saved locally in <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201209_163805-3g1rgfyp</code><br/><br/>\n",
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       "Find user logs for this run at: <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201209_163805-3g1rgfyp/logs/debug.log</code>"
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       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
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       "<tr><td>train_loss</td><td>1.83835</td></tr><tr><td>train_time</td><td>12.02478</td></tr><tr><td>test_loss</td><td>1.6135</td></tr><tr><td>accuracy</td><td>0.4308</td></tr><tr><td>test_time</td><td>2.39993</td></tr><tr><td>_step</td><td>49</td></tr><tr><td>_runtime</td><td>236</td></tr><tr><td>_timestamp</td><td>1607528521</td></tr></table>"
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       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
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       "<tr><td>train_loss</td><td>█▇▅▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>train_time</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█</td></tr><tr><td>test_loss</td><td>██▇▆▅▅▅▅▄▄▄▄▃▃▃▃▂▂▂▂▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>accuracy</td><td>▁▁▃▄▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇▇▇█▇██▇██████████████</td></tr><tr><td>test_time</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█</td></tr><tr><td>_step</td><td>▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇███</td></tr><tr><td>_runtime</td><td>▁▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▆▇▇▇▇█</td></tr><tr><td>_timestamp</td><td>▁▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▆▆▇▇▇▇█</td></tr></table><br/>"
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       "                    <br/>Synced <strong style=\"color:#cdcd00\">c_64_128_256</strong>: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/3g1rgfyp\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/3g1rgfyp</a><br/>\n",
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    {
     "ename": "DecompressionBombError",
     "evalue": "Image size (185540976 pixels) exceeds limit of 178956970 pixels, could be decompression bomb DOS attack.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mDecompressionBombError\u001b[0m                    Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-11-e1ba0222230b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"c_64_128_256\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mrunner\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mnet\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcfg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvis_cfg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3000\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-7-7495d4744ba7>\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, model, config, vis_cfg, num_epoch, im_int, key, load)\u001b[0m\n\u001b[1;32m    122\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0me_it\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mim_int\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollect\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 124\u001b[0;31m                     \u001b[0mlogNetData\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mactivations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweights\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgradients\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    125\u001b[0m                 \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0;34m\"{}/{}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0me_it\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_epoch\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'\\r'\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    126\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-4-6a92c487df73>\u001b[0m in \u001b[0;36mlogNetData\u001b[0;34m(epoch, acts, weights, grads)\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m         \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconvVolsAsFigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m         \u001b[0mims\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"w_{}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwandb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcaption\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m         \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgrads\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.8/site-packages/wandb/data_types.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data_or_path, mode, caption, grouping, classes, boxes, masks)\u001b[0m\n\u001b[1;32m   1405\u001b[0m                     \u001b[0mbuf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1406\u001b[0m                     \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mensure_matplotlib_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1407\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_image\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPILImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1408\u001b[0m                 \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mPILImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1409\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_image\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.8/site-packages/PIL/Image.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(fp, mode, formats)\u001b[0m\n\u001b[1;32m   2927\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2928\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2929\u001b[0;31m     \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_open_core\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprefix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2930\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2931\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.8/site-packages/PIL/Image.py\u001b[0m in \u001b[0;36m_open_core\u001b[0;34m(fp, filename, prefix, formats)\u001b[0m\n\u001b[1;32m   2914\u001b[0m                     \u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2915\u001b[0m                     \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfactory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2916\u001b[0;31m                     \u001b[0m_decompression_bomb_check\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2917\u001b[0m                     \u001b[0;32mreturn\u001b[0m \u001b[0mim\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2918\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mSyntaxError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstruct\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.8/site-packages/PIL/Image.py\u001b[0m in \u001b[0;36m_decompression_bomb_check\u001b[0;34m(size)\u001b[0m\n\u001b[1;32m   2826\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2827\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mpixels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mMAX_IMAGE_PIXELS\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2828\u001b[0;31m         raise DecompressionBombError(\n\u001b[0m\u001b[1;32m   2829\u001b[0m             \u001b[0;34mf\"Image size ({pixels} pixels) exceeds limit of {2 * MAX_IMAGE_PIXELS} \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2830\u001b[0m             \u001b[0;34m\"pixels, could be decompression bomb DOS attack.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mDecompressionBombError\u001b[0m: Image size (185540976 pixels) exceeds limit of 178956970 pixels, could be decompression bomb DOS attack."
     ]
    }
   ],
   "source": [
    "net_cfg = Config.fromDict( dt_dims, ldict )\n",
    "net_cfg.changeConv( \"out\", [32,64,128] )\n",
    "net = cstr( ConvNet, net_cfg )\n",
    "\n",
    "name = \"c_32_64_128\"\n",
    "runner( net, cfg, vis_cfg, 3000, 50, name )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mthehorn93\u001b[0m (use `wandb login --relogin` to force relogin)\n"
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       "                Syncing run <strong style=\"color:#cdcd00\">p_both</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
       "                Project page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4</a><br/>\n",
       "                Run page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/g0x8tqir\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/g0x8tqir</a><br/>\n",
       "                Run data is saved locally in <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201209_125028-g0x8tqir</code><br/><br/>\n",
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      "3000/3000\r"
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       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
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       "<tr><td>train_loss</td><td>0.42473</td></tr><tr><td>train_time</td><td>3.40075</td></tr><tr><td>test_loss</td><td>1.14398</td></tr><tr><td>accuracy</td><td>0.6567</td></tr><tr><td>test_time</td><td>1.27545</td></tr><tr><td>_step</td><td>2999</td></tr><tr><td>_runtime</td><td>10621</td></tr><tr><td>_timestamp</td><td>1607525249</td></tr></table>"
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       "<h3>Run history:</h3><br/><style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
       "    </style><table class=\"wandb\">\n",
       "<tr><td>train_loss</td><td>█▇▆▅▅▅▄▄▄▄▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>train_time</td><td>▁▁▁▁▁▂▁▂▁▁▁▂▂▂▁▂▂▁▂▁▁█▂▁▂▁▂▁▂▁▂▂▁▁▁▂▁▁▁▁</td></tr><tr><td>test_loss</td><td>█▆▅▄▄▄▄▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>accuracy</td><td>▁▃▄▄▄▅▅▅▅▆▆▆▇▆▇▇▇▇▇▇▇███████████████████</td></tr><tr><td>test_time</td><td>▂▁▁▁▁▂▂▁▁▁▁▁▂▁▁▁▂▁▁▁▁█▂▂▁▁▁▂▂▂▁▁▁▁▂▂▁▁▂▁</td></tr><tr><td>_step</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>_runtime</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>_timestamp</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr></table><br/>"
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       "\n",
       "                    <br/>Synced <strong style=\"color:#cdcd00\">p_both</strong>: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/g0x8tqir\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/g0x8tqir</a><br/>\n",
       "                "
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   "source": [
    "pools = [\"both\"]\n",
    "net_cfg = Config.fromDict( dt_dims, ldict )\n",
    "net_cfg.changeConv( \"out\", [16,16,32] )\n",
    "cfg[\"reg\"] = (10e-6,2*10e-5)\n",
    "\n",
    "for p in pools:\n",
    "    ldict[\"pool\"] = (p,2)\n",
    "    net = cstr( ConvNet, net_cfg )\n",
    "\n",
    "    name = \"p_{}\".format(p)\n",
    "    runner( net, cfg, vis_cfg, 3000, 50, name )\n",
    "    \n",
    "# max pooling performs a lot better than avg and both "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 14.0, 14.0)\n",
      "(32, 5.0, 5.0)\n",
      "(128, 1.0, 1.0)\n",
      "128\n",
      "128\n"
     ]
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       "\n",
       "                Tracking run with wandb version 0.10.12<br/>\n",
       "                Syncing run <strong style=\"color:#cdcd00\">1_conv_to_lin</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
       "                Project page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4</a><br/>\n",
       "                Run page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/3iyi97f8\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/3iyi97f8</a><br/>\n",
       "                Run data is saved locally in <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201211_164238-3iyi97f8</code><br/><br/>\n",
       "            "
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     "text": [
      "1068/2000\r"
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   "source": [
    "ldict_0 = {\"num_c\": 3, \"num_l\":2, \"act\":\"relu\", \"dp\":0.2, \"ksize\":5, \"pool\":(\"max\",2), \n",
    "         \"out_c\": 16, \"out_c_1\":32, \"out_c_2\":128, \"out_l\":128, \"pad\":False,\n",
    "         \"out_c_3\":128, \"ksize_3\":1, \"pool_2\":(\"max\",1)}\n",
    "\n",
    "net_cfg = Config.fromDict( dt_dims, ldict_0 )\n",
    "net = cstr( ConvNet, net_cfg )\n",
    "\n",
    "name = \"1_conv_to_lin\"\n",
    "runner( net, cfg, vis_cfg, 2000, 50, name )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 14.0, 14.0)\n",
      "(32, 5.0, 5.0)\n",
      "(128, 1.0, 1.0)\n",
      "128\n",
      "128\n",
      "(16, 14.0, 14.0)\n",
      "(32, 5.0, 5.0)\n",
      "128\n",
      "128\n",
      "128\n"
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       "\n",
       "                Tracking run with wandb version 0.10.12<br/>\n",
       "                Syncing run <strong style=\"color:#cdcd00\">lin_from_conv</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
       "                Project page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4</a><br/>\n",
       "                Run page: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/ed44do21\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/ed44do21</a><br/>\n",
       "                Run data is saved locally in <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201211_154344-ed44do21</code><br/><br/>\n",
       "            "
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     "text": [
      "1/1\r"
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     "data": {
      "text/html": [
       "<br/>Waiting for W&B process to finish, PID 24459<br/>Program ended successfully."
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    {
     "data": {
      "text/html": [
       "Find user logs for this run at: <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201211_154344-ed44do21/logs/debug.log</code>"
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      "text/html": [
       "Find internal logs for this run at: <code>/home/user/horn/Documents/Cuda-vision-Lab/wandb/run-20201211_154344-ed44do21/logs/debug-internal.log</code>"
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      "text/html": [
       "<h3>Run summary:</h3><br/><style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
       "    </style><table class=\"wandb\">\n",
       "<tr><td>train_loss</td><td>2.82075</td></tr><tr><td>train_time</td><td>2.39208</td></tr><tr><td>test_loss</td><td>2.30331</td></tr><tr><td>accuracy</td><td>0.1</td></tr><tr><td>test_time</td><td>0.76304</td></tr><tr><td>_step</td><td>0</td></tr><tr><td>_runtime</td><td>4</td></tr><tr><td>_timestamp</td><td>1607697828</td></tr></table>"
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       "<h3>Run history:</h3><br/><style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
       "    </style><table class=\"wandb\">\n",
       "<tr><td>train_loss</td><td>▁</td></tr><tr><td>train_time</td><td>▁</td></tr><tr><td>test_loss</td><td>▁</td></tr><tr><td>accuracy</td><td>▁</td></tr><tr><td>test_time</td><td>▁</td></tr><tr><td>_step</td><td>▁</td></tr><tr><td>_runtime</td><td>▁</td></tr><tr><td>_timestamp</td><td>▁</td></tr></table><br/>"
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      "text/html": [
       "Synced 5 W&B file(s), 5 media file(s), 0 artifact file(s) and 0 other file(s)"
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       "\n",
       "                    <br/>Synced <strong style=\"color:#cdcd00\">lin_from_conv</strong>: <a href=\"https://wandb.ai/cudavisionlab/cudavision4/runs/ed44do21\" target=\"_blank\">https://wandb.ai/cudavisionlab/cudavision4/runs/ed44do21</a><br/>\n",
       "                "
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   "source": [
    "net.save( \"conv_to_lin\" )\n",
    "\n",
    "def convToLinWeights( ws, s_out ):\n",
    "    with torch.no_grad():\n",
    "        w_out = torch.zeros( s_out )\n",
    "        for o_it in range( s_out[0] ):\n",
    "            #print(s_out, ws[o_it,:,:,:].flatten().shape)\n",
    "            w_out[o_it,:] = ws[o_it,:,:,:].flatten()\n",
    "        return w_out\n",
    "\n",
    "net = cstr( ConvNet, Config.fromDict( dt_dims, ldict_0 ) )\n",
    "net.load( \"conv_to_lin\" )\n",
    "    \n",
    "c_w = net.getWeights( \"c\", 2 )\n",
    "#print(c_w.shape)\n",
    "\n",
    "ldict_1 = ldict_0\n",
    "ldict_1[\"num_c\"] = 2\n",
    "ldict_1[\"num_l\"] = 3\n",
    "net_1 = cstr( ConvNet, Config.fromDict( dt_dims, ldict_1 ) )\n",
    "# conv weights to lin layer\n",
    "net_1.setWeights( \"l\", 0, convToLinWeights( c_w, net_1.getWeights( \"l\", 0 ).shape ) )\n",
    "\n",
    "net_1.setFromLayer( \"c\", 0, net.getLayer( \"c\", 0 ) )\n",
    "net_1.setFromLayer( \"c\", 1, net.getLayer( \"c\", 1 ) )\n",
    "net_1.setFromLayer( \"l\", 1, net.getLayer( \"l\", 0 ) )\n",
    "net_1.setFromLayer( \"l\", 2, net.getLayer( \"l\", 1 ) )\n",
    "\n",
    "name = \"lin_from_conv\"\n",
    "cfg[\"lr\"] = 0.0\n",
    "runner( net_1, cfg, vis_cfg, 1, 1, name )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "net.save( \"conv_test\" )"
   ]
  },
  {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![wandb4.png](attachment:wandb4.png)"
   ]
  },
  {
   "attachments": {
    "act0.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## activations\n",
    "![act0.png](attachment:act0.png)"
   ]
  },
  {
   "attachments": {
    "act1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![act1.png](attachment:act1.png)"
   ]
  },
  {
   "attachments": {
    "act2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![act2.png](attachment:act2.png)"
   ]
  },
  {
   "attachments": {
    "w0.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## weights\n",
    "![w0.png](attachment:w0.png)"
   ]
  },
  {
   "attachments": {
    "w1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![w1.png](attachment:w1.png)"
   ]
  },
  {
   "attachments": {
    "w2.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![w2.png](attachment:w2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}