tflearn examples

justinday123 · Apr 1, 2017 · 40301e7 · 40301e7
1 parent 3fd284d
commit 40301e7
Show file tree

Hide file tree

Showing 8 changed files with 192 additions and 24 deletions.
diff --git a/.ipynb_checkpoints/tflearn toy ANN reload-checkpoint.ipynb b/.ipynb_checkpoints/tflearn toy ANN reload-checkpoint.ipynb
diff --git a/.ipynb_checkpoints/tflearn toy ANN-checkpoint.ipynb b/.ipynb_checkpoints/tflearn toy ANN-checkpoint.ipynb
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -108,11 +108,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Training Step: 999  | total loss: \u001b[1m\u001b[32m0.24585\u001b[0m\u001b[0m | time: 0.002s\n",
-      "| Adam | epoch: 500 | loss: 0.24585 - acc: 0.9570 -- iter: 16/18\n",
-      "Training Step: 1000  | total loss: \u001b[1m\u001b[32m0.22196\u001b[0m\u001b[0m | time: 0.005s\n",
-      "| Adam | epoch: 500 | loss: 0.22196 - acc: 0.9613 -- iter: 18/18\n",
-      "--\n"
+      "Training Step: 999  | total loss: \u001b[1m\u001b[32m0.00214\u001b[0m\u001b[0m | time: 0.003s\n",
+      "| Adam | epoch: 500 | loss: 0.00214 - acc: 1.0000 -- iter: 16/18\n",
+      "Training Step: 1000  | total loss: \u001b[1m\u001b[32m0.00209\u001b[0m\u001b[0m | time: 0.006s\n",
+      "| Adam | epoch: 500 | loss: 0.00209 - acc: 1.0000 -- iter: 18/18\n",
+      "--\n",
+      "INFO:tensorflow:/home/gk/gensim/notebooks/ANN.model is not in all_model_checkpoint_paths. Manually adding it.\n"
      ]
     }
    ],
@@ -135,7 +136,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false
    },
@@ -144,17 +145,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1, 1, 1, 1, 1] [[0.9917974472045898, 0.008202536962926388]]\n",
-      "[1, 1, 1, 1, 0] [[0.0033489016350358725, 0.9966511130332947]]\n",
-      "[1, 1, 0, 0, 1] [[0.9948439598083496, 0.0051560611464083195]]\n",
-      "[1, 0, 0, 1, 1] [[0.9970082640647888, 0.002991726389154792]]\n"
+      "[1, 1, 1, 1, 1] [[0.9939707517623901, 0.006029300391674042]]\n",
+      "[1, 1, 1, 1, 0] [[0.0010782598983496428, 0.9989217519760132]]\n",
+      "[1, 1, 0, 0, 1] [[0.997883141040802, 0.0021168675739318132]]\n",
+      "[1, 0, 0, 1, 1] [[0.9975355863571167, 0.002464443678036332]]\n"
      ]
     }
    ],
    "source": [
     "for i,t in enumerate(test_x):\n",
     "    print(test_x[i], model.predict([test_x[i]]))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

diff --git a/ANN.model.data-00000-of-00001 b/ANN.model.data-00000-of-00001
diff --git a/ANN.model.index b/ANN.model.index
diff --git a/ANN.model.meta b/ANN.model.meta
diff --git a/checkpoint b/checkpoint
@@ -1,2 +1,2 @@
-model_checkpoint_path: "model.ckpt"
-all_model_checkpoint_paths: "model.ckpt"
+model_checkpoint_path: "/home/gk/gensim/notebooks/ANN.model"
+all_model_checkpoint_paths: "/home/gk/gensim/notebooks/ANN.model"
diff --git a/tflearn toy ANN reload.ipynb b/tflearn toy ANN reload.ipynb
diff --git a/tflearn toy ANN.ipynb b/tflearn toy ANN.ipynb
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -108,11 +108,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Training Step: 999  | total loss: \u001b[1m\u001b[32m0.24585\u001b[0m\u001b[0m | time: 0.002s\n",
-      "| Adam | epoch: 500 | loss: 0.24585 - acc: 0.9570 -- iter: 16/18\n",
-      "Training Step: 1000  | total loss: \u001b[1m\u001b[32m0.22196\u001b[0m\u001b[0m | time: 0.005s\n",
-      "| Adam | epoch: 500 | loss: 0.22196 - acc: 0.9613 -- iter: 18/18\n",
-      "--\n"
+      "Training Step: 999  | total loss: \u001b[1m\u001b[32m0.00214\u001b[0m\u001b[0m | time: 0.003s\n",
+      "| Adam | epoch: 500 | loss: 0.00214 - acc: 1.0000 -- iter: 16/18\n",
+      "Training Step: 1000  | total loss: \u001b[1m\u001b[32m0.00209\u001b[0m\u001b[0m | time: 0.006s\n",
+      "| Adam | epoch: 500 | loss: 0.00209 - acc: 1.0000 -- iter: 18/18\n",
+      "--\n",
+      "INFO:tensorflow:/home/gk/gensim/notebooks/ANN.model is not in all_model_checkpoint_paths. Manually adding it.\n"
      ]
     }
    ],
@@ -135,7 +136,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false
    },
@@ -144,17 +145,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1, 1, 1, 1, 1] [[0.9917974472045898, 0.008202536962926388]]\n",
-      "[1, 1, 1, 1, 0] [[0.0033489016350358725, 0.9966511130332947]]\n",
-      "[1, 1, 0, 0, 1] [[0.9948439598083496, 0.0051560611464083195]]\n",
-      "[1, 0, 0, 1, 1] [[0.9970082640647888, 0.002991726389154792]]\n"
+      "[1, 1, 1, 1, 1] [[0.9939707517623901, 0.006029300391674042]]\n",
+      "[1, 1, 1, 1, 0] [[0.0010782598983496428, 0.9989217519760132]]\n",
+      "[1, 1, 0, 0, 1] [[0.997883141040802, 0.0021168675739318132]]\n",
+      "[1, 0, 0, 1, 1] [[0.9975355863571167, 0.002464443678036332]]\n"
      ]
     }
    ],
    "source": [
     "for i,t in enumerate(test_x):\n",
     "    print(test_x[i], model.predict([test_x[i]]))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {