integration-tests/examples/test_templates/deeplearning/template_mxnet.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mxnet as mx\n",
    "a = mx.sym.Variable('a')\n",
    "b = mx.sym.Variable('b')\n",
    "c = a + b\n",
    "(a, b, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# elemental wise times\n",
    "d = a * b  \n",
    "# matrix multiplication\n",
    "e = mx.sym.dot(a, b)   \n",
    "# reshape\n",
    "f = mx.sym.Reshape(d+e, shape=(1,4))  \n",
    "# broadcast\n",
    "g = mx.sym.broadcast_to(f, shape=(2,4))  \n",
    "mx.viz.plot_network(symbol=g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from __future__ import print_function\n",
    "import os\n",
    "import time\n",
    "# set the number of threads you want to use before importing mxnet\n",
    "os.environ['MXNET_CPU_WORKER_NTHREADS'] = '4'\n",
    "import mxnet as mx\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download example images\n",
    "proxy = os.popen('cat /etc/profile | grep https_proxy | cut -f2 -d\"=\"').read()[:-1]\n",
    "os.popen('wget -e use_proxy=yes -e http_proxy={} http://data.mxnet.io/data/test_images.tar.gz'.format(proxy)).read()\n",
    "os.popen('tar -xf test_images.tar.gz').read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# opencv\n",
    "import cv2\n",
    "N = 1000\n",
    "tic = time.time()\n",
    "for i in range(N):\n",
    "    img = cv2.imread('test_images/ILSVRC2012_val_00000001.JPEG', flags=1)\n",
    "    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "print(N/(time.time()-tic), 'images decoded per second with opencv')\n",
    "plt.imshow(img); plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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