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Build torch and lightgbm from source. (#1083) · acrowise/docker-python@e34c886 · GitHub

/ docker-python Public
forked from Kaggle/docker-python

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Build torch and lightgbm from source. (Kaggle#1083)
* Build torch and lightgbm from source. Fixes Kaggle#984, Kaggle#1059 Introduced a new "architecture" to easily build packages from source in the main build only if needed (i.e. if the base image or the package version has changed). This enable us to: - Upgrade PyTorch which doesn't have a wheel for 1.9.1 and CUDA 11. This prevented us from upgrading torch for ~6 months. - Move the lightgbm gpu source build to this architecture to shave ~3 minutes off the build time. http://b/181966788 * Add /usr/local/cuda/compat to LD_LIBRARY_PATH * Build torchaudio and torchtext from source * Increase torch build timeout
1 parent 7cf514a commit e34c886

8 files changed

Lines changed: 344 additions & 19 deletions

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‎Dockerfile.tmpl‎

Lines changed: 34 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,33 @@
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ARG BASE_IMAGE_REPO
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ARG BASE_IMAGE_TAG
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ARG CPU_BASE_IMAGE_NAME
4+
ARG GPU_BASE_IMAGE_NAME
5+
ARG LIGHTGBM_VERSION
6+
ARG TORCH_VERSION
7+
ARG TORCHAUDIO_VERSION
8+
ARG TORCHTEXT_VERSION
9+
ARG TORCHVISION_VERSION
10+
111
{{ if eq .Accelerator "gpu" }}
2-
FROM gcr.io/deeplearning-platform-release/tf2-gpu.2-6:m80
12+
FROM gcr.io/kaggle-images/python-lightgbm-whl:${GPU_BASE_IMAGE_NAME}-${BASE_IMAGE_TAG}-${LIGHTGBM_VERSION} AS lightgbm_whl
13+
FROM gcr.io/kaggle-images/python-torch-whl:${GPU_BASE_IMAGE_NAME}-${BASE_IMAGE_TAG}-${TORCH_VERSION} AS torch_whl
14+
FROM ${BASE_IMAGE_REPO}/${GPU_BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}
315
ENV CUDA_MAJOR_VERSION=11
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ENV CUDA_MINOR_VERSION=0
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{{ else }}
6-
FROM gcr.io/deeplearning-platform-release/tf2-cpu.2-6:m80
18+
FROM ${BASE_IMAGE_REPO}/${CPU_BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}
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{{ end }}
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# Keep these variables in sync if base image is updated.
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ENV TENSORFLOW_VERSION=2.6.0
22+
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# We need to redefine the ARG here to get the ARG value defined above the FROM instruction.
24+
# See: https://docs.docker.com/engine/reference/builder/#understand-how-arg-and-from-interact
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ARG LIGHTGBM_VERSION
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ARG TORCH_VERSION
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ARG TORCHAUDIO_VERSION
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ARG TORCHTEXT_VERSION
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ARG TORCHVISION_VERSION
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# Disable pesky logs like: KMP_AFFINITY: pid 6121 tid 6121 thread 0 bound to OS proc set 0
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# See: https://stackoverflow.com/questions/57385766/disable-tensorflow-log-information
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ENV KMP_WARNINGS=0
@@ -15,6 +36,9 @@ ADD clean-layer.sh /tmp/clean-layer.sh
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ADD patches/nbconvert-extensions.tpl /opt/kaggle/nbconvert-extensions.tpl
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ADD patches/template_conf.json /opt/kaggle/conf.json
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# Adds the libcuda.so to LD_LIBRARY_PATH which is necessary for the GPU mxnet package.
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ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/compat
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{{ if eq .Accelerator "gpu" }}
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# b/200968891 Keeps horovod once torch is upgraded.
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RUN pip uninstall -y horovod && \
@@ -52,29 +76,24 @@ RUN conda install cudf=21.08 cuml=21.08 cudatoolkit=$CUDA_MAJOR_VERSION.$CUDA_MI
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# Install PyTorch
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{{ if eq .Accelerator "gpu" }}
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RUN pip install torch==1.7.1+cu$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION torchvision==0.8.2+cu$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION torchaudio==0.7.2 torchtext==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html && \
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COPY --from=torch_whl /tmp/whl/*.whl /tmp/torch/
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RUN pip install /tmp/torch/*.whl && \
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rm -rf /tmp/torch && \
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/tmp/clean-layer.sh
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{{ else }}
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RUN pip install torch==1.7.1+cpu torchvision==0.8.2+cpu torchaudio==0.7.2 torchtext==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html && \
84+
RUN pip install torch==$TORCH_VERSION+cpu torchvision==$TORCHVISION_VERSION+cpu torchaudio==$TORCHAUDIO_VERSION torchtext==$TORCHTEXT_VERSION -f https://download.pytorch.org/whl/torch_stable.html && \
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/tmp/clean-layer.sh
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{{ end }}
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# Install LightGBM
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ENV LIGHTGBM_VERSION=3.2.1
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{{ if eq .Accelerator "gpu" }}
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COPY --from=lightgbm_whl /tmp/whl/*.whl /tmp/lightgbm/
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# Install OpenCL (required by LightGBM GPU version)
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RUN apt-get install -y ocl-icd-libopencl1 clinfo && \
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mkdir -p /etc/OpenCL/vendors && \
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echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd && \
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cd /usr/local/src && \
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git clone --recursive https://github.com/microsoft/LightGBM && \
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cd LightGBM && \
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git checkout tags/v$LIGHTGBM_VERSION && \
73-
mkdir build && cd build && \
74-
cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \
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make -j$(nproc) && \
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cd /usr/local/src/LightGBM/python-package && \
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python setup.py install --precompile && \
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pip install /tmp/lightgbm/*.whl && \
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rm -rf /tmp/lightgbm && \
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/tmp/clean-layer.sh
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{{ else }}
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RUN pip install lightgbm==$LIGHTGBM_VERSION && \
@@ -386,8 +405,7 @@ RUN pip install bleach && \
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pip install widgetsnbextension && \
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pip install pyarrow && \
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pip install feather-format && \
389-
# fastai >= 2.3.1 upgrades pytorch/torchvision. upgrade of pytorch will be handled in b/181966788
390-
pip install fastai==2.2.7 && \
408+
pip install fastai && \
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pip install allennlp && \
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# https://b.corp.google.com/issues/184685619#comment9: 3.9.0 is causing a major performance degradation with spacy 2.3.5
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pip install importlib-metadata==3.4.0 && \

‎Jenkinsfile‎

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@@ -34,6 +34,42 @@ pipeline {
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'''
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}
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}
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stage('Pre-build Packages from Source') {
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parallel {
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stage('torch') {
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options {
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timeout(time: 180, unit: 'MINUTES')
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}
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steps {
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sh '''#!/bin/bash
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set -exo pipefail
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source config.txt
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cd packages/
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./build_package --base-image $BASE_IMAGE_REPO/$GPU_BASE_IMAGE_NAME:$BASE_IMAGE_TAG \
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--package torch \
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--version $TORCH_VERSION \
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--build-arg TORCHAUDIO_VERSION=$TORCHAUDIO_VERSION \
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--build-arg TORCHTEXT_VERSION=$TORCHTEXT_VERSION \
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--build-arg TORCHVISION_VERSION=$TORCHVISION_VERSION \
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--push
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'''
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}
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}
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stage('lightgbm') {
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options {
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timeout(time: 10, unit: 'MINUTES')
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}
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steps {
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sh '''#!/bin/bash
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set -exo pipefail
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source config.txt
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cd packages/
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./build_package --base-image $BASE_IMAGE_REPO/$GPU_BASE_IMAGE_NAME:$BASE_IMAGE_TAG --package lightgbm --version $LIGHTGBM_VERSION --push
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'''
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}
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}
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}
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}
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stage('Build/Test/Diff') {
3874
parallel {
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stage('CPU') {
@@ -79,7 +115,7 @@ pipeline {
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}
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stage('GPU') {
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agent { label 'ephemeral-linux-gpu' }
82-
stages {
118+
stages {
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stage('Build GPU Image') {
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options {
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timeout(time: 120, unit: 'MINUTES')

‎build‎

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Original file line numberDiff line numberDiff line change
@@ -47,14 +47,18 @@ done
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BUILD_ARGS+=" --build-arg GIT_COMMIT=$(git rev-parse HEAD)"
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BUILD_ARGS+=" --build-arg BUILD_DATE=$(date '+%Y%m%d-%H%M%S')"
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# Read build args from config.txt file.
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SRCDIR=$(dirname "${BASH_SOURCE[0]}")
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for l in `cat ${SRCDIR}/config.txt`; do
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BUILD_ARGS+=" --build-arg $l"
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done
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readonly CACHE_FLAG
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readonly DOCKERFILE
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readonly ACCELERATOR
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readonly IMAGE_TAG
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readonly BUILD_ARGS
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SRCDIR=$(dirname "${BASH_SOURCE[0]}")
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DOCKERFILE_OUTDIR="${SRCDIR}/.generated"
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mkdir -p $DOCKERFILE_OUTDIR
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DOCKERFILE_PATH="$DOCKERFILE_OUTDIR/$DOCKERFILE"

‎config.txt‎

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BASE_IMAGE_REPO=gcr.io/deeplearning-platform-release
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BASE_IMAGE_TAG=m80
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CPU_BASE_IMAGE_NAME=tf2-cpu.2-6
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GPU_BASE_IMAGE_NAME=tf2-gpu.2-6
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LIGHTGBM_VERSION=3.2.1
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TORCH_VERSION=1.9.1
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TORCHAUDIO_VERSION=0.9.1
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TORCHTEXT_VERSION=0.10.1
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TORCHVISION_VERSION=0.10.1

‎packages/README.md‎

Whitespace-only changes.

‎packages/build_package‎

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#!/bin/bash
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set -e
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usage() {
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cat << EOF
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Usage: $0 [OPTIONS]
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Build a new package ".whl".
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Options:
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-p, --package PACKAGE Package to build (e.g. lightgbm).
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-v, --version VERSION Package version to build.
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-b, --base-image IMAGE Base image tag (e.g. m80).
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-c, --use-cache Use layer cache when building a new image.
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-f, --force-rebuild Rebuild the image regardless of whether it already exist on GCR.
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-u, --push Push image to GCR.
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--build-arg ARG=VALUE Build arguments to pass to the docker build command.
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EOF
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}
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20+
PACKAGE=''
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PACKAGE_VERSION=''
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BASE_IMAGE=''
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DOCKERFILE=''
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CACHE_FLAG='--no-cache'
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FORCE_REBUILD=false
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PUSH_TO_GCR=false
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BUILD_ARGS=''
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while :; do
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case "$1" in
31+
-h|--help)
32+
usage
33+
exit
34+
;;
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-p|--package)
36+
if [[ -z $2 ]]; then
37+
usage
38+
printf 'ERROR: No IMAGE specified after the %s flag.\n' "$1" >&2
39+
exit 1
40+
fi
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PACKAGE=$2
42+
DOCKERFILE="${PACKAGE}.Dockerfile"
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shift # skip the flag value
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;;
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-v|--version)
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if [[ -z $2 ]]; then
47+
usage
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printf 'ERROR: No VERSION specified after the %s flag.\n' "$1" >&2
49+
exit 1
50+
fi
51+
PACKAGE_VERSION=$2
52+
shift # skip the flag value
53+
;;
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-t|--base-image)
55+
if [[ -z $2 ]]; then
56+
usage
57+
printf 'ERROR: No TAG specified after the %s flag.\n' "$1" >&2
58+
exit 1
59+
fi
60+
BASE_IMAGE=$2
61+
shift # skip the flag value
62+
;;
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-c|--use-cache)
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CACHE_FLAG=''
65+
;;
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-f|--force-rebuild)
67+
FORCE_REBUILD=true
68+
;;
69+
-u|--push)
70+
PUSH_TO_GCR=true
71+
;;
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--build-arg)
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if [[ -z $2 ]]; then
74+
usage
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printf 'ERROR: No ARG=VALUE specified after the %s flag.\n' "$1" >&2
76+
exit 1
77+
fi
78+
BUILD_ARGS+=" $1 $2"
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shift # skip the flag value
80+
;;
81+
-?*)
82+
usage
83+
printf 'ERROR: Unknown option: %s\n' "$1" >&2
84+
exit 1
85+
;;
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*)
87+
break
88+
esac
89+
90+
shift
91+
done
92+
93+
readonly PACKAGE
94+
readonly PACKAGE_VERSION
95+
readonly BASE_IMAGE
96+
readonly DOCKERFILE
97+
readonly CACHE_FLAG
98+
readonly FORCE_REBUILD
99+
100+
SRCDIR=$(dirname "${BASH_SOURCE[0]}")
101+
DOCKERFILE_PATH="$SRCDIR/$DOCKERFILE"
102+
103+
if [[ -z "$PACKAGE_VERSION" ]]; then
104+
printf 'ERROR: missing --version flag.\n'
105+
exit 1
106+
fi
107+
108+
if [[ -z "$BASE_IMAGE" ]]; then
109+
printf 'ERROR: missing --base-image flag.\n'
110+
exit 1
111+
fi
112+
113+
if [[ -z "$DOCKERFILE" ]]; then
114+
printf 'ERROR: missing --package flag.\n'
115+
exit 1
116+
fi
117+
118+
# Keep only `tf2-gpu.2-6:m80` in `gcr.io/deeplearning-platform-release/tf2-gpu.2-6:m80`
119+
TAG=${BASE_IMAGE/gcr.io\/deeplearning-platform-release\//}
120+
# Replace the `:` in `tf2-gpu.2-6:m80` by `-`
121+
TAG=${TAG/:/-}
122+
# Append the package version
123+
TAG=$TAG-$PACKAGE_VERSION
124+
# Add the gcr repo.
125+
TAG=gcr.io/kaggle-images/python-$PACKAGE-whl:$TAG
126+
127+
SHOULD_BUILD=true
128+
if ! $FORCE_REBUILD; then
129+
echo "Checking if $TAG exists..."
130+
docker pull $TAG && SHOULD_BUILD=false
131+
fi
132+
133+
if $SHOULD_BUILD; then
134+
echo "Building $TAG..."
135+
docker build --rm --pull $BUILD_ARGS \
136+
$CACHE_FLAG \
137+
-t $TAG \
138+
-f "$DOCKERFILE_PATH" \
139+
--build-arg BASE_IMAGE=$BASE_IMAGE \
140+
--build-arg PACKAGE_VERSION=$PACKAGE_VERSION \
141+
$SRCDIR
142+
143+
if $PUSH_TO_GCR; then
144+
echo "Pushing $TAG to GCR..."
145+
docker push $TAG
146+
fi
147+
else
148+
echo "Skipping build. $TAG already exists."
149+
echo "Use --force-rebuild if you want to build a new version anyway."
150+
fi

‎packages/lightgbm.Dockerfile‎

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ARG BASE_IMAGE
2+
3+
FROM ${BASE_IMAGE} AS builder
4+
5+
ARG PACKAGE_VERSION
6+
7+
# Build instructions: https://lightgbm.readthedocs.io/en/latest/GPU-Tutorial.html#build-lightgbm
8+
RUN apt-get update && \
9+
apt-get install -y build-essential cmake libboost-dev libboost-system-dev libboost-filesystem-dev ocl-icd-libopencl1 clinfo
10+
11+
RUN cd /usr/local/src && \
12+
git clone --recursive https://github.com/microsoft/LightGBM && \
13+
cd LightGBM && \
14+
git checkout tags/v$PACKAGE_VERSION && \
15+
mkdir build && cd build && \
16+
cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \
17+
make -j$(nproc) && \
18+
cd /usr/local/src/LightGBM/python-package && \
19+
python setup.py bdist_wheel
20+
21+
# Using multi-stage builds to ensure the output image is very small
22+
# See: https://docs.docker.com/develop/develop-images/multistage-build/
23+
FROM alpine:latest
24+
25+
RUN mkdir -p /tmp/whl/
26+
COPY --from=builder /usr/local/src/LightGBM/python-package/dist/*.whl /tmp/whl
27+
28+
# Print out the built .whl file.
29+
RUN ls -lh /tmp/whl/

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