Overview
- uv version: 0.1.22
- Problem
- Installing
timm==0.9.7 within ngc docker container will reinstall the old version of torch.
- torch version:
- ngc docker: 2.3.0a0+ebedce2
- version requested by timm: >=1.7
Steps to Reproduce
Place the following Dockerfile and compose.yml in the current directory
FROM nvcr.io/nvidia/pytorch:24.02-py3
ARG UID=1000
ARG GID=1000
ARG USERNAME=vscode
ENV DEBIAN_FRONTEND=noninteractive \
LANG=ja_JP.UTF-8 \
TZ=Asia/Tokyo \
apt_get_server=ftp.jaist.ac.jp/pub/Linux \
PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
VIRTUAL_ENV=/usr/
WORKDIR /workspace
SHELL ["/bin/bash", "-o", "pipefail", "-c"]
RUN \
# apt
--mount=type=cache,target=/var/cache/apt \
--mount=type=cache,target=/var/lib/apt \
rm /etc/apt/apt.conf.d/docker-clean \
&& sed -i s@archive.ubuntu.com@${apt_get_server}@g /etc/apt/sources.list \
&& curl -sL https://raw.githubusercontent.com/eza-community/eza/main/deb.asc | gpg --dearmor -o /etc/apt/keyrings/gierens.gpg \
&& echo "deb [signed-by=/etc/apt/keyrings/gierens.gpg] http://deb.gierens.de stable main" | tee /etc/apt/sources.list.d/gierens.list \
&& chmod 644 /etc/apt/keyrings/gierens.gpg /etc/apt/sources.list.d/gierens.list \
&& apt-get update \
&& apt-get install -y --no-install-recommends \
bat \
fd-find \
ripgrep \
eza \
shellcheck \
tmux \
zsh \
sudo \
&& ln -s "$(which batcat)" /usr/local/bin/bat \
&& ln -s "$(which fdfind)" /usr/local/bin/fd \
# just command runner
&& curl --proto '=https' --tlsv1.2 -sSf https://just.systems/install.sh | bash -s -- --to /usr/local/bin \
# hadolint
&& curl -fSL "https://github.com/hadolint/hadolint/releases/download/$(curl -s https://api.github.com/repos/hadolint/hadolint/releases/latest | jq -r '.tag_name')/hadolint-Linux-x86_64" -o /usr/local/bin/hadolint \
&& chmod +x /usr/local/bin/hadolint \
# uv
&& pip install --no-cache-dir uv \
# add user
&& groupadd --gid ${GID} ${USERNAME} \
&& useradd -l --uid ${UID} --gid ${GID} -m ${USERNAME} \
&& echo "${USERNAME} ALL=(ALL) NOPASSWD: ALL" > /etc/sudoers.d/${USERNAME}
USER ${USERNAME}services:
kaggle:
build:
dockerfile: ./Dockerfile
args:
- UID=${UID}
- GID=${GID}
restart: always
tty: true
volumes:
- type: bind
source: .
target: /workspace
read_only: false
consistency: cached
ipc: host
ulimits:
memlock: -1
stack: -1
ports:
- "8888:8888"
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]
command: jupyter lab --ip=0.0.0.0 --port 8888 --allow-root --NotebookApp.notebook_dir=/workspace --no-browser --LabApp.token=''
Run the following command
$ docker compose up -d
$ docker compose exec kaggle sudo uv pip install timm==0.9.7
Expected Result
torch is not reinstalled because it meets the requirements of timm, only timm is installed.
Actual Result
Installed 15 packages in 187ms
+ nvidia-cublas-cu12==12.1.3.1
+ nvidia-cuda-cupti-cu12==12.1.105
+ nvidia-cuda-nvrtc-cu12==12.1.105
+ nvidia-cuda-runtime-cu12==12.1.105
+ nvidia-cudnn-cu12==8.9.2.26
+ nvidia-cufft-cu12==11.0.2.54
+ nvidia-curand-cu12==10.3.2.106
+ nvidia-cusolver-cu12==11.4.5.107
+ nvidia-cusparse-cu12==12.1.0.106
+ nvidia-nccl-cu12==2.19.3
+ nvidia-nvjitlink-cu12==12.4.99
+ nvidia-nvtx-cu12==12.1.105
+ timm==0.9.7
- torch==2.3.0a0+ebedce2 (from file:///tmp/pip/torch-2.3.0a0%2Bebedce2-cp310-cp310-linux_x86_64.whl)
+ torch==2.2.1
- torchvision==0.18.0a0 (from file:///opt/pytorch/vision)
+ torchvision==0.17.1
Overview
timm==0.9.7withinngc docker containerwill reinstall the old version of torch.Steps to Reproduce
Place the following
Dockerfileandcompose.ymlin the current directoryRun the following command
$ docker compose up -d $ docker compose exec kaggle sudo uv pip install timm==0.9.7Expected Result
torch is not reinstalled because it meets the requirements of timm, only timm is installed.
Actual Result
Installed 15 packages in 187ms + nvidia-cublas-cu12==12.1.3.1 + nvidia-cuda-cupti-cu12==12.1.105 + nvidia-cuda-nvrtc-cu12==12.1.105 + nvidia-cuda-runtime-cu12==12.1.105 + nvidia-cudnn-cu12==8.9.2.26 + nvidia-cufft-cu12==11.0.2.54 + nvidia-curand-cu12==10.3.2.106 + nvidia-cusolver-cu12==11.4.5.107 + nvidia-cusparse-cu12==12.1.0.106 + nvidia-nccl-cu12==2.19.3 + nvidia-nvjitlink-cu12==12.4.99 + nvidia-nvtx-cu12==12.1.105 + timm==0.9.7 - torch==2.3.0a0+ebedce2 (from file:///tmp/pip/torch-2.3.0a0%2Bebedce2-cp310-cp310-linux_x86_64.whl) + torch==2.2.1 - torchvision==0.18.0a0 (from file:///opt/pytorch/vision) + torchvision==0.17.1