luvres / jupyter

Tensorflow ROCm and NVIDIA for Jupyterhub

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Pull image

docker pull izone/jupyter:rocm3.5-tf2.2.0-python37

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Running

ROCm

docker run --rm --name Jupyter-rocm \
--device=/dev/kfd \
--device=/dev/dri \
-ti izone/jupyter:rocm3.5-tf2.2.0-python37

NVIDIA

docker run --gpus all -it --rm izone/jupyter:nvidia-tensorflow \
python -c "import tensorflow as tf; print('Num GPUs Available: ', len(tf.config.list_physical_devices('GPU')))"

docker run --gpus all -it --rm izone/jupyter:nvidia-tensorflow \
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

docker run --rm --gpus all --name TensorFlow \
-p 8888:8888 \
-v $HOME/notebooks:/root/notebooks \
-u root \
-ti izone/jupyter:nvidia-tensorflow \
jupyter notebook \
	--allow-root \
	--no-browser \
	--ip=0.0.0.0 \
	--port=8888 \
	--notebook-dir=/root/notebooks \
	--NotebookApp.token=''

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Builds

ROCm

docker build -t izone/jupyter:rocm3.1-tf2.1.1-python37 -f ./Dockerfile.rocm31tf211 .

docker build -t izone/jupyter:rocm3.5-tf2.2.0-python37 -f ./Dockerfile.rocm35tf220 .

docker build -t izone/jupyter:rocm3.7-tf2.3.3-python37 -f ./Dockerfile.rocm37tf233 .

NVIDIA

docker build -t izone/jupyter:cuda11.2-tf2.7-python39 -f ./Dockerfile.cuda112tf270 .

docker build -t izone/jupyter:cuda11.2-tf2.6-python39 -f ./Dockerfile.cuda112tf260 .

docker build -t izone/jupyter:cuda11.2-tf2.6-python39-29102021 -f ./Dockerfile.cuda112tf260 .