cpu only

Author: cmanzo

.github/workflows/docker-publish.yml

@@ -1,7 +1,6 @@
 name: Build & Publish Docker Image
 
 on:
-
   pull_request:
     branches: [ docker ]
     paths:
@@ -36,15 +35,6 @@ jobs:
       - uses: docker/setup-qemu-action@v3      # multi-arch emulation
       - uses: docker/setup-buildx-action@v3    # Buildx driver with cache support
 
-      # # -------- optional, but speeds repeat builds -----------
-      # - name: Restore Docker layer cache
-      #   uses: actions/cache@v4
-      #   with:
-      #     path: /tmp/.buildx-cache
-      #     key: ${{ runner.os }}-buildx-${{ github.sha }}
-      #     restore-keys: ${{ runner.os }}-buildx-
-      # # --------------------------------------------------------
-
       - name: Log in to GHCR
         uses: docker/login-action@v3
         with:
@@ -62,5 +52,3 @@ jobs:
           tags: |
               ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
               ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
-          # cache-from: type=local,src=/tmp/.buildx-cache
-          # cache-to:   type=local,dest=/tmp/.buildx-cache,mode=max

docker/Dockerfile

@@ -13,8 +13,13 @@ USER ${NB_UID}
 WORKDIR /home/jovyan/work
 COPY .. .
 
+# ---------- ensure correct ownership ---------------------------------------------
+    USER root
+    RUN chown -R ${NB_UID}:${NB_GID} /home/jovyan/work
+    USER ${NB_UID}
+
 # ---------- extra Python deps -----------------------------------------------------
-# CPU wheels only
+# CPU-only PyTorch (wheels from CPU index)
 RUN pip install --no-cache-dir \
         torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 \
         --index-url https://download.pytorch.org/whl/cpu

docker/README.md

@@ -23,41 +23,48 @@ Works on Intel & Apple-Silicon Macs, Linux ×86_64 & ARM64.
 
 
 ---
-## General use
+## Quick Start
 
-### 1. Pull the latest image
+### Open Docker Desktop
 
-```bash
+### Pull the Latest Image
+
+```
 docker pull ghcr.io/deeptrackai/deep-learning-crash-course:latest
 ```
 Docker will automatically select the correct architecture slice (amd64 or arm64).
 
-### 2. Run JupyterLab
+
+### Startup Docker Image
+
 ```docker run --rm -it \
   -p 8888:8888 \
-  -v "$(pwd)":/home/jovyan/work \
-  ghcr.io/deeptrackai/deep-learning-crash-course:latest
-  ```
-After startup you’ll see a URL with a token (e.g. http://127.0.0.1:8888/lab?token=…). Paste it into your browser.
+  ghcr.io/deeptrackai/deep-learning-crash-course:latest```
 
 --- 
 
-## Use in VS Code (Dev Containers)
+### Open in JupyterLab
+
+After startup, you’ll see a URL with a token (e.g. http://127.0.0.1:8888/lab?token=…). Paste it into your browser. You'll see the full set of Crash Course notebooks.
+
+---
 
-### 1. Install the “Dev Containers” extension in VS Code.
+### Open in VS Code (Dev Containers)
 
-### 2. Command Palette → Dev Containers: Open Folder in Container…
+After startup, in VS Code (with Dev Containers installed):
+   
+   1. Open the Command Palette. 
 
-### 3. Select your local DeepLearningCrashCourse folder.
+   2. Run ```Dev Containers: Attach to Running Container...```.
 
-### 4. In the new window:
+   3. Select your container, a new VS Code window will pop up.
 
-   - Install Python & Jupyter extensions when prompted.
+   4. In the new window:
 
-   - Open Folder → /home/jovyan/work (the repo inside the container).
+      - Install Python & Jupyter extensions when prompted.
 
-   - Select Interpreter in the bottom bar → the one at `/opt/conda/bin/python` (Python 3.11).
+      - Open Folder → /home/jovyan/work (the repo inside the container).
 
-### 5. Use the integrated terminal (`Ctrl`+``) or Run & Debug scripts (F5).
+      - Select Interpreter in the bottom bar → the one at `/opt/conda/bin/python` (Python 3.11).
 
-### 6. Open any `.ipynb` and run cells.
+   5. Open any `.ipynb` and run cells.