changed file name for backprop

Author: simonjisu

lab-09_8_mnist_back_prop.ipynb renamed to lab-08_4_mnist_back_prop.ipynb

@@ -88,8 +88,9 @@
     {
      "data": {
       "text/plain": [
-       "tensor([ 1.8153,  0.1568,  0.0348,  0.0334,  0.9967,  0.3957,  1.0805,  0.0302,\n",
-       "        -0.4433, -0.0206], device='cuda:0', grad_fn=<CopyBackwards>)"
+       "Parameter containing:\n",
+       "tensor([ 0.3078, -1.9857,  1.0512,  1.5122, -1.0199, -0.7402, -1.3111,  0.6142,\n",
+       "        -0.6474,  0.1758], requires_grad=True)"
       ]
      },
      "execution_count": 7,
@@ -110,7 +111,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def sigma(x):\n",
+    "def sigmoid(x):\n",
     "    #  sigmoid function\n",
     "    return 1.0 / (1.0 + torch.exp(-x))\n",
     "    # return torch.div(torch.tensor(1), torch.add(torch.tensor(1.0), torch.exp(-x)))"
@@ -122,9 +123,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def sigma_prime(x):\n",
+    "def sigmoid_prime(x):\n",
     "    # derivative of the sigmoid function\n",
-    "    return sigma(x) * (1 - sigma(x))"
+    "    return sigmoid(x) * (1 - sigmoid(x))"
    ]
   },
   {
@@ -136,16 +137,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "829\n",
-      "846\n",
-      "870\n",
-      "876\n",
+      "736\n",
+      "862\n",
+      "860\n",
       "881\n",
-      "892\n",
-      "894\n",
-      "894\n",
-      "891\n",
-      "898\n"
+      "874\n",
+      "890\n",
+      "904\n",
+      "923\n",
+      "916\n",
+      "920\n"
      ]
     }
    ],
@@ -161,19 +162,19 @@
     "        X = X.view(-1, 28 * 28).to(device)\n",
     "        Y = torch.zeros((batch_size, 10)).scatter_(1, Y.unsqueeze(1), 1).to(device)    # one-hot\n",
     "        l1 = torch.add(torch.matmul(X, w1), b1)\n",
-    "        a1 = sigma(l1)\n",
+    "        a1 = sigmoid(l1)\n",
     "        l2 = torch.add(torch.matmul(a1, w2), b2)\n",
-    "        y_pred = sigma(l2)\n",
+    "        y_pred = sigmoid(l2)\n",
     "\n",
     "        diff = y_pred - Y\n",
     "\n",
     "        # Back prop (chain rule)\n",
-    "        d_l2 = diff * sigma_prime(l2)\n",
+    "        d_l2 = diff * sigmoid_prime(l2)\n",
     "        d_b2 = d_l2\n",
     "        d_w2 = torch.matmul(torch.transpose(a1, 0, 1), d_l2)\n",
     "\n",
     "        d_a1 = torch.matmul(d_l2, torch.transpose(w2, 0, 1))\n",
-    "        d_l1 = d_a1 * sigma_prime(l1)\n",
+    "        d_l1 = d_a1 * sigmoid_prime(l1)\n",
     "        d_b1 = d_l1\n",
     "        d_w1 = torch.matmul(torch.transpose(X, 0, 1), d_l1)\n",
     "\n",
@@ -184,9 +185,9 @@
     "\n",
     "        if i % 1000 == 0:\n",
     "            l1 = torch.add(torch.matmul(X_test, w1), b1)\n",
-    "            a1 = sigma(l1)\n",
+    "            a1 = sigmoid(l1)\n",
     "            l2 = torch.add(torch.matmul(a1, w2), b2)\n",
-    "            y_pred = sigma(l2)\n",
+    "            y_pred = sigmoid(l2)\n",
     "            acct_mat = torch.argmax(y_pred, 1) == Y_test\n",
     "            acct_res = acct_mat.sum()\n",
     "            print(acct_res.item())\n",
@@ -212,7 +213,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.3"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,