update

NVIDIA · Feb 24, 2025 · d013dc9 · d013dc9
1 parent 6716ec1
commit d013dc9
Show file tree

Hide file tree

Showing 2 changed files with 39 additions and 10 deletions.
diff --git a/...ted_learning_applications/01.1_running_federated_learning_job/runing_pytorch_fl_job.ipynb b/...ted_learning_applications/01.1_running_federated_learning_job/runing_pytorch_fl_job.ipynb
@@ -24,11 +24,11 @@
     "\n",
     "We use the `FedAvg` algorithm and workflow.\n",
     "\n",
-    "```markdown\n",
+    "\n",
     "## Run Federated Learning Training\n",
     "\n",
     "The training code consists of three main scripts: `fl_job.py` for the overall job flow, `client.py` for the client-side training, and `network.py` for the network model. We use the built-in `FedAvg` algorithm for the server-side workflow.\n",
-    "```\n",
+    "\n",
     "\n",
     "To run the training in the simulator, we can simply execute `fl_job.py`.\n"
    ]
@@ -104,7 +104,7 @@
   "kernelspec": {
    "display_name": "nvflare_env",
    "language": "python",
-   "name": "python3"
+   "name": "nvflare_env"
   },
   "language_info": {
    "codemirror_mode": {

diff --git a/...1_running_federated_learning_applications/01.1_running_federated_learning_job/setup.ipynb b/...1_running_federated_learning_applications/01.1_running_federated_learning_job/setup.ipynb
@@ -73,7 +73,7 @@
     "\n",
     "The CIFAR10 data will be downloaded to the common location. To make this process easiler, we wrote an simple download program like the followings\n",
     "\n",
-    "```\n",
+    "```python\n",
     "\n",
     "import argparse\n",
     "import torchvision.datasets as datasets\n",
@@ -105,10 +105,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "87a13909",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to /tmp/nvflare/data/cifar10/cifar-10-python.tar.gz\n",
+      "100%|████████████████████████████████████████| 170M/170M [00:05<00:00, 28.6MB/s]\n",
+      "Extracting /tmp/nvflare/data/cifar10/cifar-10-python.tar.gz to /tmp/nvflare/data/cifar10\n",
+      "Files already downloaded and verified\n"
+     ]
+    }
+   ],
    "source": [
     "!python3 code/data/download.py"
    ]
@@ -123,10 +134,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "08bbe572",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[01;34m/tmp/nvflare/data/cifar10/cifar-10-batches-py/\u001b[0m\n",
+      "├── \u001b[00mbatches.meta\u001b[0m\n",
+      "├── \u001b[00mdata_batch_1\u001b[0m\n",
+      "├── \u001b[00mdata_batch_2\u001b[0m\n",
+      "├── \u001b[00mdata_batch_3\u001b[0m\n",
+      "├── \u001b[00mdata_batch_4\u001b[0m\n",
+      "├── \u001b[00mdata_batch_5\u001b[0m\n",
+      "├── \u001b[00mreadme.html\u001b[0m\n",
+      "└── \u001b[00mtest_batch\u001b[0m\n",
+      "\n",
+      "0 directories, 8 files\n"
+     ]
+    }
+   ],
    "source": [
     "!tree /tmp/nvflare/data/cifar10/cifar-10-batches-py/"
    ]
@@ -170,9 +199,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "nvflare_env",
    "language": "python",
-   "name": "python3"
+   "name": "nvflare_env"
   },
   "language_info": {
    "codemirror_mode": {