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--- public:docker [2025/02/23 12:11] – liang
+++ public:docker [2025/02/23 14:03] (current) – [Step 4: Work with PyTorch] liang
@@ Line 5: / Line 5: @@
 ===== Step 1: Understand docker =====
-  * Read [[https://docs.docker.com/get-started/docker-overview/|What is docker]] and understand (docker) image, container, daemon, client, hub (registry), pull, push.
+  * Read https://docs.docker.com/get-started/docker-overview/ and understand (docker) image, container, daemon, client, hub (registry), pull, push.
-  * Install docker (Linux as example. Information on other OSes are welcome too.)
+  * Install docker (Linux Mint as example. Information on other OSes are welcome too.)
     * $ sudo apt install docker.io
     * Add your username to the "docker" group (or by editing /etc/group directly).
@@ Line 16: / Line 16: @@
     * # exit
-===== Step 2 (optional): Install Nvidia GPU support =====
+===== Step 2 (if you have an NVidia GPU): Install Nvidia GPU support =====
   * Follow https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
+===== Step 3: Install PyTorch (for development) =====
+  * $ docker pull pytorch/pytorch:latest
+  * $ docker run --rm --gpus all pytorch/pytorch:latest python -c "import torch; print(torch.cuda.is_available())"
+  * If you see "True", it worked.
+===== Step 4: Work with PyTorch =====
+  * $ docker run -it --gpus all --rm pytorch/pytorch:latest bash
+  * # nvidia-smi
+  * If you see the use of your GPU, it worked.
 ===== References =====
-  * https://github.com/saikhu/Docker-Guide-for-AI-Model-Development-and-Deployment
+  * https://github.com/saikhu/Docker-Guide-for-AI-Model-Development-and-Deployment (Chapter 6 is obsolete. See the above Step 2 for the latest information)