FROM pytorch/pytorch:2.2.0-cuda12.1-cudnn8-runtime (#8104)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docker/Dockerfile

@@ -3,7 +3,7 @@
 # Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference
 
 # Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch or nvcr.io/nvidia/pytorch:23.03-py3
-FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime
+FROM pytorch/pytorch:2.2.0-cuda12.1-cudnn8-runtime
 RUN pip install --no-cache nvidia-tensorrt --index-url https://pypi.ngc.nvidia.com
 
 # Downloads to user config dir

docker/Dockerfile-cpu

@@ -48,10 +48,10 @@ RUN ln -sf /usr/bin/python3 /usr/bin/python
 # t=ultralytics/ultralytics:latest-cpu && sudo docker build -f docker/Dockerfile-cpu -t $t . && sudo docker push $t
 
 # Run
-# t=ultralytics/ultralytics:latest-cpu && sudo docker run -it --ipc=host $t
+# t=ultralytics/ultralytics:latest-cpu && sudo docker run -it --ipc=host --name NAME $t
 
 # Pull and Run
-# t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host $t
+# t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host --name NAME $t
 
 # Pull and Run with local volume mounted
 # t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t