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Use UBJ in Python checkpoint. #7828

Use UBJ in Python checkpoint.

Use UBJ in Python checkpoint. #7828

Workflow file for this run

name: XGBoost-JVM-Tests
on: [push, pull_request]
permissions:
contents: read # to fetch code (actions/checkout)
jobs:
test-with-jvm:
name: Test JVM on OS ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [windows-latest, ubuntu-latest, macos-11]
steps:
- uses: actions/checkout@e2f20e631ae6d7dd3b768f56a5d2af784dd54791 # v2.5.0
with:
submodules: 'true'
- uses: actions/setup-python@7f80679172b057fc5e90d70d197929d454754a5a # v4.3.0
with:
python-version: '3.8'
architecture: 'x64'
- uses: actions/setup-java@d202f5dbf7256730fb690ec59f6381650114feb2 # v3.6.0
with:
java-version: 1.8
- name: Install Python packages
run: |
python -m pip install wheel setuptools
python -m pip install awscli
- name: Cache Maven packages
uses: actions/cache@6998d139ddd3e68c71e9e398d8e40b71a2f39812 # v3.2.5
with:
path: ~/.m2
key: ${{ runner.os }}-m2-${{ hashFiles('./jvm-packages/pom.xml') }}
restore-keys: ${{ runner.os }}-m2-${{ hashFiles('./jvm-packages/pom.xml') }}
- name: Test XGBoost4J (Core)
run: |
cd jvm-packages
mvn test -B -pl :xgboost4j_2.12
- name: Extract branch name
shell: bash
run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF#refs/heads/})"
id: extract_branch
if: |
(github.ref == 'refs/heads/master' || contains(github.ref, 'refs/heads/release_')) &&
(matrix.os == 'windows-latest' || matrix.os == 'macos-11')
- name: Publish artifact xgboost4j.dll to S3
run: |
cd lib/
Rename-Item -Path xgboost4j.dll -NewName xgboost4j_${{ github.sha }}.dll
dir
python -m awscli s3 cp xgboost4j_${{ github.sha }}.dll s3://xgboost-nightly-builds/${{ steps.extract_branch.outputs.branch }}/libxgboost4j/ --acl public-read
if: |
(github.ref == 'refs/heads/master' || contains(github.ref, 'refs/heads/release_')) &&
matrix.os == 'windows-latest'
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID_IAM_S3_UPLOADER }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY_IAM_S3_UPLOADER }}
- name: Publish artifact libxgboost4j.dylib to S3
run: |
cd lib/
mv -v libxgboost4j.dylib libxgboost4j_${{ github.sha }}.dylib
ls
python -m awscli s3 cp libxgboost4j_${{ github.sha }}.dylib s3://xgboost-nightly-builds/${{ steps.extract_branch.outputs.branch }}/libxgboost4j/ --acl public-read
if: |
(github.ref == 'refs/heads/master' || contains(github.ref, 'refs/heads/release_')) &&
matrix.os == 'macos-11'
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID_IAM_S3_UPLOADER }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY_IAM_S3_UPLOADER }}
- name: Test XGBoost4J (Core, Spark, Examples)
run: |
rm -rfv build/
cd jvm-packages
mvn -B test
if: matrix.os == 'ubuntu-latest' # Distributed training doesn't work on Windows
env:
RABIT_MOCK: ON
- name: Build and Test XGBoost4J with scala 2.13
run: |
rm -rfv build/
cd jvm-packages
mvn -B clean install test -Pdefault,scala-2.13
if: matrix.os == 'ubuntu-latest' # Distributed training doesn't work on Windows
env:
RABIT_MOCK: ON