none debugging.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'lasagne.layers.conv.Conv2DLayer'>, valid, same, (1, 16, 96, 16)\n",
      "<class 'lasagne.layers.conv.Conv2DLayer'>, valid, diff, (1, 16, 96, 16)\n",
      "<class 'lasagne.layers.conv.Conv2DLayer'>, full, same, (1, 16, 104, 24)\n",
      "<class 'lasagne.layers.conv.Conv2DLayer'>, full, diff, (1, 16, 104, 24)\n",
      "<class 'lasagne.layers.conv.Conv2DLayer'>, same, same, (1, 16, 100, 20)\n",
      "<class 'lasagne.layers.conv.Conv2DLayer'>, same, diff, (1, 16, 100, 20)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import theano\n",
    "import lasagne\n",
    "import itertools\n",
    "\n",
    "# Create network, starting with input layer\n",
    "l_in = lasagne.layers.InputLayer(shape=(None, 16, 100, 20))\n",
    "\n",
    "x_same = np.random.randn(1, 16, 100, 20).astype(theano.config.floatX)\n",
    "x_diff = np.random.randn(1, 16, 200, 20).astype(theano.config.floatX)\n",
    "\n",
    "for layer, mode in itertools.product([lasagne.layers.Conv2DLayer],\n",
    "                                     ['valid', 'full', 'same']):\n",
    "    \n",
    "    l_1 = layer(l_in, num_filters=16, filter_size=(5, 5), border_mode=mode)\n",
    "    \n",
    "    out = theano.function([l_in.input_var], l_1.get_output())\n",
    "    \n",
    "    for x, shape in zip([x_same, x_diff], ['same', 'diff']):\n",
    "        print \"{}, {}, {}, {}\".format(layer, mode, shape, out(x).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.8.2\n",
      "0.7.0rc2.dev-d2c39c4ebd21eeb066681db0c74fd9ab3b0798e8\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'module' object has no attribute '__version__'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-97d63e01435e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mprint\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__version__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mprint\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__version__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[1;32mprint\u001b[0m \u001b[0mlasagne\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__version__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: 'module' object has no attribute '__version__'"
     ]
    }
   ],
   "source": [
    "print np.__version__\n",
    "print theano.__version__\n",
    "print lasagne.__version__"
   ]
  }
 ],
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