You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

50 lines
1.7KB

  1. # Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
  2. FROM nvcr.io/nvidia/pytorch:20.03-py3
  3. RUN pip install -U gsutil
  4. # Create working directory
  5. RUN mkdir -p /usr/src/app
  6. WORKDIR /usr/src/app
  7. # Copy contents
  8. COPY . /usr/src/app
  9. # Install dependencies (pip or conda)
  10. #RUN pip install -r requirements.txt
  11. # Copy weights
  12. #RUN python3 -c "from models import *; \
  13. #attempt_download('weights/yolov5s.pt'); \
  14. #attempt_download('weights/yolov5m.pt'); \
  15. #attempt_download('weights/yolov5l.pt')"
  16. # --------------------------------------------------- Extras Below ---------------------------------------------------
  17. # Build and Push
  18. # t=ultralytics/yolov5:latest && sudo docker build -t $t . && sudo docker push $t
  19. # Pull and Run
  20. # t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host $t bash
  21. # Pull and Run with local directory access
  22. # t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/coco:/usr/src/coco $t bash
  23. # Kill all
  24. # sudo docker kill "$(sudo docker ps -q)"
  25. # Kill all image-based
  26. # sudo docker kill $(sudo docker ps -a -q --filter ancestor=ultralytics/yolov5:latest)
  27. # Run bash for loop
  28. # sudo docker run --gpus all --ipc=host ultralytics/yolov5:latest while true; do python3 train.py --evolve; done
  29. # Bash into running container
  30. # sudo docker container exec -it ba65811811ab bash
  31. # python -c "from utils.utils import *; create_pretrained('weights/last.pt')" && gsutil cp weights/pretrained.pt gs://*
  32. # Bash into stopped container
  33. # sudo docker commit 6d525e299258 user/test_image && sudo docker run -it --gpus all --ipc=host -v "$(pwd)"/coco:/usr/src/coco --entrypoint=sh user/test_image
  34. # Clean up
  35. # docker system prune -a --volumes