feat: make it easier to download the datasets

demo-notebooks/guided-demos/2_basic_jobs.ipynb

@@ -116,7 +116,13 @@
    "id": "83d77b74",
    "metadata": {},
    "source": [
-    "First, let's begin by submitting to Ray, training a basic NN on the MNIST dataset:"
+    "First, let's begin by submitting to Ray, training a basic NN on the MNIST dataset:\n",
+    "\n",
+    "NOTE: To test this demo in an air-gapped/ disconnected environment alter the training script to use a local dataset.\n",
+    "First we must download the MNIST dataset. We've included a helper script to do this for you. \n",
+    "\n",
+    "You can run the python script (`python download_mnist_datasets.py`) directly and then place the dataset in the same directory as this notebook. \n",
+    "The path to the dataset would be: `..guided-demos/MNIST/raw/` "
    ]
   },
   {
@@ -129,6 +135,7 @@
     "jobdef = DDPJobDefinition(\n",
     "    name=\"mnisttest\",\n",
     "    script=\"mnist.py\",\n",
+    "    # script=\"mnist_disconnected.py\", # training script for disconnected environment\n",
     "    scheduler_args={\"requirements\": \"requirements.txt\"}\n",
     ")\n",
     "job = jobdef.submit(cluster)"
@@ -302,7 +309,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.9.18"
   },
   "vscode": {
    "interpreter": {

demo-notebooks/guided-demos/mnist_disconnected.py

@@ -30,7 +30,7 @@
 BATCH_SIZE = 256 if torch.cuda.is_available() else 64
 # %%
 
-local_minst_path = os.path.dirname(os.path.abspath(__file__) + "/MNIST/raw")
+local_minst_path = os.path.dirname(os.path.abspath(__file__))
 
 print("prior to running the trainer")
 print("MASTER_ADDR: is ", os.getenv("MASTER_ADDR"))