dimshuffle.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:5920b1afec8cc9b2dd87015709f32fee73ba2013a3b60b8719a831377a772a24"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import theano\n",
      "import theano.tensor as T\n",
      "\n",
      "A = theano.shared(np.ones(1000, dtype=np.float32))\n",
      "B = theano.shared(np.ones((1000,1), dtype=np.float32))\n",
      "\n",
      "def reshape():\n",
      "    global A\n",
      "    A = A.reshape((1000,1))\n",
      "    \n",
      "def dimshuffle():\n",
      "    global A\n",
      "    A = A.dimshuffle(0, 'x')\n",
      "    \n",
      "def newaxis():\n",
      "    global A\n",
      "    A = A[:, np.newaxis]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit dimshuffle()\n",
      "%timeit newaxis()\n",
      "%timeit reshape()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10000 loops, best of 3: 39.9 \u00b5s per loop\n",
        "10000 loops, best of 3: 182 \u00b5s per loop"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "1000 loops, best of 3: 247 \u00b5s per loop"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(A.dimshuffle(0,'x') + B).eval().shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "(1000, 1)"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "B = theano.shared(np.ones((10,5), dtype=np.float32))\n",
      "T.sum(B, axis=1).dimshuffle(0, 'x').eval().shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "(10, 1)"
       ]
      }
     ],
     "prompt_number": 20
    }
   ],
   "metadata": {}
  }
 ]
}