12장, 15장 노트북 재실행

12_distributed_tensorflow.ipynb

@@ -9,12 +9,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPython 3.5.5\n",
-      "IPython 6.3.0\n",
+      "CPython 3.6.5\n",
+      "IPython 6.4.0\n",
       "\n",
       "numpy 1.14.3\n",
       "sklearn 0.19.1\n",
-      "scipy 1.0.1\n",
+      "scipy 1.1.0\n",
       "matplotlib 2.2.2\n",
       "tensorflow 1.8.0\n"
      ]
@@ -254,9 +254,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.0, 6, 44]\n"
+     ]
+    }
+   ],
    "source": [
     "reset_graph()\n",
     "\n",
@@ -271,7 +279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -279,8 +287,8 @@
      "output_type": "stream",
      "text": [
       "더 이상 읽을 파일이 없습니다\n",
-      "[array([[4.00000000e+00, 5.00000000e+00],\n",
-      "       [1.00000000e+00, 1.27106565e+36]], dtype=float32), array([1, 0], dtype=int32)]\n",
+      "[array([[ 4.,  5.],\n",
+      "       [ 1., -1.]], dtype=float32), array([1, 0], dtype=int32)]\n",
       "[array([[7., 8.]], dtype=float32), array([0], dtype=int32)]\n",
       "더 이상 훈련 샘플이 없습니다\n"
      ]
@@ -334,7 +342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -354,16 +362,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[array([[4.00000000e+00, 5.00000000e+00],\n",
-      "       [1.00000000e+00, 1.27106565e+36]], dtype=float32), array([1, 0], dtype=int32)]\n",
-      "[array([[7., 8.]], dtype=float32), array([0], dtype=int32)]\n",
+      "[array([[ 7.,  8.],\n",
+      "       [ 1., -1.]], dtype=float32), array([0, 0], dtype=int32)]\n",
+      "[array([[4., 5.]], dtype=float32), array([1], dtype=int32)]\n",
       "더 이상 훈련 샘플이 없습니다\n"
      ]
     }
@@ -408,15 +416,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[array([[4.00000000e+00, 5.00000000e+00],\n",
-      "       [1.00000000e+00, 1.27106565e+36]], dtype=float32), array([1, 0], dtype=int32)]\n",
+      "[array([[ 4.,  5.],\n",
+      "       [ 1., -1.]], dtype=float32), array([1, 0], dtype=int32)]\n",
       "[array([[7., 8.]], dtype=float32), array([0], dtype=int32)]\n",
       "더 이상 훈련 샘플이 없습니다\n"
      ]
@@ -469,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -526,7 +534,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -542,7 +550,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,7 +574,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -583,9 +591,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 1 2 3 4 5 6]\n",
+      "[7 8 9 0 1 2 3]\n",
+      "[4 5 6 7 8 9 0]\n",
+      "[1 2 3 4 5 6 7]\n",
+      "[8 9]\n",
+      "완료\n"
+     ]
+    }
+   ],
    "source": [
     "with tf.Session() as sess:\n",
     "    try:\n",
@@ -611,9 +632,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[array([0, 1, 2, 3, 4, 5, 6]), array([0, 1, 2, 3, 4, 5, 6])]\n",
+      "[array([7, 8, 9, 0, 1, 2, 3]), array([7, 8, 9, 0, 1, 2, 3])]\n",
+      "[array([4, 5, 6, 7, 8, 9, 0]), array([4, 5, 6, 7, 8, 9, 0])]\n",
+      "[array([1, 2, 3, 4, 5, 6, 7]), array([1, 2, 3, 4, 5, 6, 7])]\n",
+      "[array([8, 9]), array([8, 9])]\n",
+      "완료\n"
+     ]
+    }
+   ],
    "source": [
     "with tf.Session() as sess:\n",
     "    try:\n",
@@ -632,7 +666,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -641,7 +675,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -657,9 +691,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0,1,7,8,4,5,2,3,9,0,6,7,4,5,1,2,8,9,6,3,0,1,2,8,9,3,4,5,6,7,완료\n"
+     ]
+    }
+   ],
    "source": [
     "with tf.Session() as sess:\n",
     "    try:\n",
@@ -692,7 +734,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -701,7 +743,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -710,7 +752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -726,7 +768,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -746,7 +788,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -762,7 +804,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -772,9 +814,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 1. -1.] 0.0\n",
+      "[4. 5.] 1.0\n",
+      "[7. 8.] 0.0\n",
+      "완료\n"
+     ]
+    }
+   ],
    "source": [
     "with tf.Session() as sess:\n",
     "    try:\n",
@@ -818,7 +871,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.5"
+   "version": "3.6.5"
   },
   "nav_menu": {},
   "toc": {