Theano.ipynb

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  {
   "cell_type": "code",
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   "source": [
    "import theano.tensor as T\n",
    "\n",
    "from theano import function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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   "outputs": [],
   "source": [
    "x = T.dscalar('x')\n",
    "\n",
    "y = T.dscalar('y')\n",
    "\n",
    "z = x + y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "f = function([x,y],z)"
   ]
  },
  {
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   "execution_count": 4,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(5.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f(2,3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Exercise\n",
    "Modify and execute this code to compute this expression: a ** 2 + b ** 2 + 2 * a * b."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a = T.dscalar('a')\n",
    "b = T.dscalar('b')\n",
    "c = (a + b) ** 2\n",
    "f2 = function([a,b],c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(36.0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f2(2,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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