Files
Ayaz Salikhov 90224a7a99 Install latest tensorflow using pip (#2263)
* Install latest tensorflow using pip

* Allow tensorflow test to warn

* Fix another way
2025-04-13 12:11:40 +01:00

42 lines
1.5 KiB
Docker

# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
ARG REGISTRY=quay.io
ARG OWNER=jupyter
ARG BASE_IMAGE=$REGISTRY/$OWNER/scipy-notebook
FROM $BASE_IMAGE
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
# Fix: https://github.com/hadolint/hadolint/wiki/DL4006
# Fix: https://github.com/koalaman/shellcheck/wiki/SC3014
SHELL ["/bin/bash", "-o", "pipefail", "-c"]
RUN mamba install --yes \
'jupyter-server-proxy' && \
mamba clean --all -f -y && \
fix-permissions "${CONDA_DIR}" && \
fix-permissions "/home/${NB_USER}"
# Install TensorFlow, CUDA and cuDNN with pip
RUN pip install --no-cache-dir \
'tensorflow[and-cuda]' && \
fix-permissions "${CONDA_DIR}" && \
fix-permissions "/home/${NB_USER}"
COPY --chown="${NB_UID}:${NB_GID}" 20tensorboard-proxy-env.sh /usr/local/bin/before-notebook.d/
# workaround for https://github.com/tensorflow/tensorflow/issues/63362
RUN mkdir -p "${CONDA_DIR}/etc/conda/activate.d/" && \
fix-permissions "${CONDA_DIR}"
COPY --chown="${NB_UID}:${NB_GID}" nvidia-lib-dirs.sh "${CONDA_DIR}/etc/conda/activate.d/"
# https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html#dockerfiles
ENV NVIDIA_VISIBLE_DEVICES="all" \
NVIDIA_DRIVER_CAPABILITIES="compute,utility"
# Puts the nvidia-smi binary (system management interface) on path
# with associated library files to execute it
ENV PATH="${PATH}:/usr/local/nvidia/bin" \
LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64"