style fixes

Author: Igor Shilov

tutorials/building_image_classifier.ipynb

@@ -340,9 +340,9 @@
     "    module=model,\n",
     "    optimizer=optimizer,\n",
     "    data_loader=train_loader,\n",
-    "    epochs = EPOCHS,\n",
-    "    target_epsilon = EPSILON,\n",
-    "    target_delta = DELTA,\n",
+    "    epochs=EPOCHS,\n",
+    "    target_epsilon=EPSILON,\n",
+    "    target_delta=DELTA,\n",
     "    max_grad_norm=MAX_GRAD_NORM,\n",
     ")\n",
     "\n",
@@ -582,7 +582,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -596,7 +596,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.5"
+   "version": "3.7.5"
   },
   "toc": {
    "base_numbering": 1,

tutorials/building_lstm_name_classifier.ipynb

@@ -337,7 +337,7 @@
    "source": [
     "from statistics import mean\n",
     "\n",
-    "def train(model, criterion, optimizer, train_loader, epoch, device=\"cuda:0\"):\n",
+    "def train(model, criterion, optimizer, train_loader, epoch, privacy_engine, device=\"cuda:0\"):\n",
     "    accs = []\n",
     "    losses = []\n",
     "    for x, y in train_loader:\n",
@@ -361,12 +361,10 @@
     "    printstr = (\n",
     "        f\"\\t Epoch {epoch}. Accuracy: {mean(accs):.6f} | Loss: {mean(losses):.6f}\"\n",
     "    )\n",
-    "    try:\n",
-    "        privacy_engine = optimizer.privacy_engine\n",
+    "    if privacy_engine:\n",
     "        epsilon = privacy_engine.get_epsilon(delta)\n",
     "        printstr += f\" | (ε = {epsilon:.2f}, δ = {delta})\"\n",
-    "    except AttributeError:\n",
-    "        pass\n",
+    "\n",
     "    print(printstr)\n",
     "    return\n",
     "\n",
@@ -684,7 +682,7 @@
    "source": [
     "print(\"Train stats: \\n\")\n",
     "for epoch in range(epochs):\n",
-    "    train(model, criterion, optimizer, train_loader, epoch, device=device)\n",
+    "    train(model, criterion, optimizer, train_loader, epoch, privacy_engine, device=device)\n",
     "    if test_every:\n",
     "        if epoch % test_every == 0:\n",
     "            test(model, test_loader, privacy_engine, device=device)\n",
@@ -875,7 +873,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -889,7 +887,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.5"
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,

tutorials/building_text_classifier.ipynb

@@ -616,9 +616,9 @@
     "    module=model,\n",
     "    optimizer=optimizer,\n",
     "    data_loader=train_dataloader,\n",
-    "    target_delta = DELTA,\n",
-    "    target_epsilon = EPSILON, \n",
-    "    epochs = EPOCHS,\n",
+    "    target_delta=DELTA,\n",
+    "    target_epsilon=EPSILON, \n",
+    "    epochs=EPOCHS,\n",
     "    max_grad_norm=MAX_GRAD_NORM,\n",
     ")"
    ]
@@ -708,7 +708,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -722,7 +722,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.5"
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,