Graph of ResNetV2-18 & 50 with tensorboardX

resnet_v2_graph.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Graph of ResNetV2-18 & 50 with tensorboardX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from tensorboardX.graph import graph\n",
    "# ResnetV2 is not in the official repository of torchvision\n",
    "from torchvision.models.resnet_v2 import resnet18_v2, resnet50_v2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/torch/onnx/utils.py:365: UserWarning: ONNX export failed on ATen operator adaptive_avg_pool2d because torch.onnx.symbolic.adaptive_avg_pool2d does not exist\n",
      "  .format(op_name, op_name))\n"
     ]
    }
   ],
   "source": [
    "model1 = resnet18_v2()\n",
    "model2 = resnet50_v2()\n",
    "\n",
    "x = torch.rand(2, 3, 32, 32)\n",
    "graph_def1 = graph(model1, x)\n",
    "graph_def2 = graph(model2, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TensorFlow Graph visualizer code\n",
    "import numpy as np\n",
    "from IPython.display import clear_output, Image, display, HTML\n",
    "\n",
    "def show_graph(graph_def, max_const_size=32):\n",
    "    \"\"\"Visualize TensorFlow graph.\"\"\"\n",
    "    if hasattr(graph_def, 'as_graph_def'):\n",
    "        graph_def = graph_def.as_graph_def()\n",
    "    # strip_def = strip_consts(graph_def, max_const_size=max_const_size)\n",
    "    strip_def = graph_def\n",
    "    code = \"\"\"\n",
    "        <script src=\"//cdnjs.cloudflare.com/ajax/libs/polymer/0.3.3/platform.js\"></script>\n",
    "        <script>\n",
    "          function load() {{\n",
    "            document.getElementById(\"{id}\").pbtxt = {data};\n",
    "          }}\n",
    "        </script>\n",
    "        <link rel=\"import\" href=\"https://tensorboard.appspot.com/tf-graph-basic.build.html\" onload=load()>\n",
    "        <div style=\"height:600px\">\n",
    "          <tf-graph-basic id=\"{id}\"></tf-graph-basic>\n",
    "        </div>\n",
    "    \"\"\".format(data=repr(str(strip_def)), id='graph'+str(np.random.rand()))\n",
    "\n",
    "    iframe = \"\"\"\n",
    "        <iframe seamless style=\"width:1200px;height:620px;border:0\" srcdoc=\"{}\"></iframe>\n",
    "    \"\"\".format(code.replace('\"', '&quot;'))\n",
    "    display(HTML(iframe))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe seamless style=\"width:1200px;height:620px;border:0\" srcdoc=\"\n",
       "        <script src=&quot;//cdnjs.cloudflare.com/ajax/libs/polymer/0.3.3/platform.js&quot;></script>\n",
       "        <script>\n",
       "          function load() {\n",
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       "          }\n",
       "        </script>\n",
       "        <link rel=&quot;import&quot; href=&quot;https://tensorboard.appspot.com/tf-graph-basic.build.html&quot; onload=load()>\n",
       "        <div style=&quot;height:600px&quot;>\n",
       "          <tf-graph-basic id=&quot;graph0.2898867718144692&quot;></tf-graph-basic>\n",
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       "    "
      ],
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simply call this to display the result. Unfortunately it doesn't save the output together with\n",
    "# the Jupyter notebook, so we can only show a non-interactive image here.\n",
    "show_graph(graph_def1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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    "# Simply call this to display the result. Unfortunately it doesn't save the output together with\n",
    "# the Jupyter notebook, so we can only show a non-interactive image here.\n",
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