fix bug

Author: MorvanZhou

tutorial-contents-notebooks/201_torch_numpy.ipynb

@@ -183,14 +183,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\nmatrix multiplication (matmul) \nnumpy:  [[ 7 10]\n [15 22]] \ntorch:  tensor([[  7.,  10.],\n        [ 15.,  22.]])\n"
+      "\nmatrix multiplication (matmul) \nnumpy:  [[ 7 10]\n [15 22]] \ntorch:  tensor([[ 7., 10.],\n        [15., 22.]])\n"
      ]
     }
    ],
@@ -208,29 +208,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "matrix multiplication (dot) \n",
-      "numpy:  [[ 7 10]\n",
-      " [15 22]] \n",
-      "torch:  30.0\n"
-     ]
+     "ename": "RuntimeError",
+     "evalue": "dot: Expected 1-D argument self, but got 2-D",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-3-a29f9258176b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0;34m'\\nmatrix multiplication (dot)'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0;34m'\\nnumpy: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m        \u001b[0;31m# [[7, 10], [15, 22]]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m     \u001b[0;34m'\\ntorch: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m     \u001b[0;31m# 30.0. Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m )\n",
+      "\u001b[0;31mRuntimeError\u001b[0m: dot: Expected 1-D argument self, but got 2-D"
+     ],
+     "output_type": "error"
     }
    ],
    "source": [
     "# incorrect method\n",
     "data = np.array(data)\n",
-    "tensor = torch.Tensor([1,2,3,4]\n",
+    "tensor = torch.Tensor(data)\n",
     "print(\n",
     "    '\\nmatrix multiplication (dot)',\n",
     "    '\\nnumpy: ', data.dot(data),        # [[7, 10], [15, 22]]\n",
-    "    '\\ntorch: ', torch.dot(tensor.dot(tensor)     # 30.0. Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\n",
+    "    '\\ntorch: ', torch.dot(tensor.dot(tensor))     # NOT WORKING! Beware that torch.dot does not broadcast, only works for 1-dimensional tensor\n",
     ")"
    ]
   },