[MNT] improve MNIST performance

examples/mnist_add/mnist_add.ipynb

@@ -181,7 +181,7 @@
    "source": [
     "cls = LeNet5(num_classes=10)\n",
     "loss_fn = nn.CrossEntropyLoss()\n",
-    "optimizer = torch.optim.Adam(cls.parameters(), lr=0.001)\n",
+    "optimizer = torch.optim.RMSprop(cls.parameters(), lr=0.001, alpha=0.9)\n",
     "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
     "\n",
     "base_model = BasicNN(\n",
@@ -357,7 +357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -390,7 +390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -409,7 +409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -455,7 +455,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.8.18"
   },
   "orig_nbformat": 4,
   "vscode": {