Lisa-lab code path fixed

bi-lab · Apr 15, 2016 · 394cdbb · 394cdbb
1 parent feb9ba8
commit 394cdbb
Showing 1 changed file with 22 additions and 41 deletions.
diff --git a/CNN with MNIST.ipynb b/CNN with MNIST.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
@@ -13,7 +13,7 @@
     "import timeit\n",
     "\n",
     "import numpy \n",
-    "deep_root = 'DeepLearningTutorials/'\n",
+    "deep_root = '../DeepLearningTutorials/'\n",
     "sys.path.insert(0, os.path.join(deep_root,'code'))\n",
     "\n",
     "import theano\n",
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "metadata": {
     "collapsed": true
    },
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "collapsed": true
    },
@@ -62,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -91,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -115,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -126,7 +126,7 @@
        "<TensorType(int32, vector)>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -137,7 +137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -149,38 +149,19 @@
      "text": [
       "... building the model\n",
       "... training\n",
-      "training @ iter =  0\n",
-      "epoch 1, minibatch 100/100, validation error 8.500000 %\n",
-      "     epoch 1, minibatch 100/100, test error of best model 8.910000 %\n",
-      "training @ iter =  100\n",
-      "epoch 2, minibatch 100/100, validation error 5.840000 %\n",
-      "     epoch 2, minibatch 100/100, test error of best model 6.130000 %\n",
-      "training @ iter =  200\n",
-      "epoch 3, minibatch 100/100, validation error 4.310000 %\n",
-      "     epoch 3, minibatch 100/100, test error of best model 4.700000 %\n",
-      "training @ iter =  300\n",
-      "epoch 4, minibatch 100/100, validation error 3.510000 %\n",
-      "     epoch 4, minibatch 100/100, test error of best model 3.610000 %\n",
-      "training @ iter =  400\n",
-      "epoch 5, minibatch 100/100, validation error 2.960000 %\n",
-      "     epoch 5, minibatch 100/100, test error of best model 3.090000 %\n",
-      "training @ iter =  500\n",
-      "epoch 6, minibatch 100/100, validation error 2.670000 %\n",
-      "     epoch 6, minibatch 100/100, test error of best model 2.750000 %\n",
-      "training @ iter =  600\n",
-      "epoch 7, minibatch 100/100, validation error 2.410000 %\n",
-      "     epoch 7, minibatch 100/100, test error of best model 2.410000 %\n",
-      "training @ iter =  700\n",
-      "epoch 8, minibatch 100/100, validation error 2.300000 %\n",
-      "     epoch 8, minibatch 100/100, test error of best model 2.200000 %\n",
-      "training @ iter =  800\n",
-      "epoch 9, minibatch 100/100, validation error 2.230000 %\n",
-      "     epoch 9, minibatch 100/100, test error of best model 2.070000 %\n",
-      "training @ iter =  900\n",
-      "epoch 10, minibatch 100/100, validation error 2.030000 %\n",
-      "     epoch 10, minibatch 100/100, test error of best model 1.900000 %\n",
-      "Optimization complete.\n",
-      "Best validation score of 2.030000 % obtained at iteration 1000, with test performance 1.900000 %\n"
+      "training @ iter =  0\n"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-8-21d5ce3e743f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m    162\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0miter\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;36m100\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    163\u001b[0m             \u001b[1;32mprint\u001b[0m \u001b[1;34m'training @ iter = '\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miter\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 164\u001b[1;33m         \u001b[0mcost_ij\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtrain_model\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mminibatch_index\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    165\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    166\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0miter\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mvalidation_frequency\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m    857\u001b[0m         \u001b[0mt0_fn\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    858\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 859\u001b[1;33m             \u001b[0moutputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    860\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    861\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'position_of_error'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
      ]
     }
    ],