fixed indention and enumeration for nvct (#518)

setup/03_optional-docker-environment/README.md

@@ -37,38 +37,38 @@ mv setup/03_optional-docker-environment/.devcontainer ./
 
 4. If you have a [CUDA-supported GPU](https://developer.nvidia.com/cuda-gpus), you can speed up the training and inference:
 
-   3.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2).
-
-   3.2 Add _nvidia_ as runtime in Docker Engine daemon config (see _Docker Desktop_ -> _Change settings_ -> _Docker Engine_). Add these lines to your config:
-
-   ```json
-   "runtimes": {
-       "nvidia": {
-       "path": "nvidia-container-runtime",
-       "runtimeArgs": []
-   ```
-
-   For example, the full Docker Engine daemon config json code should look like that:
-
-   ```json
-   {
-     "builder": {
-       "gc": {
-         "defaultKeepStorage": "20GB",
-         "enabled": true
-       }
-     },
-     "experimental": false,
-     "runtimes": {
-       "nvidia": {
-         "path": "nvidia-container-runtime",
-         "runtimeArgs": []
-       }
-     }
-   }
-   ```
-
-   and restart Docker Desktop.
+    4.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2).
+
+    4.2 Add _nvidia_ as runtime in Docker Engine daemon config (see _Docker Desktop_ -> _Change settings_ -> _Docker Engine_). Add these lines to your config:
+
+    ```json
+    "runtimes": {
+        "nvidia": {
+        "path": "nvidia-container-runtime",
+        "runtimeArgs": []
+    ```
+
+    For example, the full Docker Engine daemon config json code should look like that:
+
+    ```json
+    {
+      "builder": {
+        "gc": {
+          "defaultKeepStorage": "20GB",
+          "enabled": true
+        }
+      },
+      "experimental": false,
+      "runtimes": {
+        "nvidia": {
+          "path": "nvidia-container-runtime",
+          "runtimeArgs": []
+        }
+      }
+    }
+    ```
+
+    and restart Docker Desktop.
 
 5. Type `code .` in the terminal to open the project in VS Code. Alternatively, you can launch VS Code and select the project to open from the UI.