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Conda-GPU-Nightly #1559

Conda-GPU-Nightly

Conda-GPU-Nightly #1559

name: Conda-GPU-Nightly
on:
push:
branches:
- main
pull_request:
branches:
- main
schedule:
- cron: '10 6 * * *' # 6:10 AM UTC
jobs:
Build:
strategy:
matrix:
pkg: ['tlcpack', 'tlcpack-nightly']
config:
- cuda: '10.2'
image: 'tlcpack/package-cu102:2fddbe0'
# Conda forge is not shipping a cudnn package with support for CUDA 11.0
# - cuda: '11.0'
# image: 'tlcpack/package-cu110:2fddbe0'
- cuda: '11.1'
image: 'tlcpack/package-cu111:2fddbe0'
- cuda: '11.3'
image: 'tlcpack/package-cu113:2fddbe0'
- cuda: '11.6'
image: 'tlcpack/package-cu116:2fddbe0'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- uses: actions/cache@v1
env:
CACHE_NUMBER: 0
with:
path: ~/conda_pkgs_dir
key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles('conda/build-environment.yaml') }}
- uses: conda-incubator/setup-miniconda@v2
with:
activate-environment: tlcpack-build
channel-priority: strict
environment-file: conda/build-environment.yaml
auto-activate-base: false
use-only-tar-bz2: true
- name: Conda info
run: |
conda info
conda list
- name: TVM checkout
run: |
git clone https://github.com/apache/tvm tvm --recursive
- name: Sync Package
run: python common/sync_package.py --cuda ${{ matrix.config.cuda }} ${{ matrix.pkg }}
- name: Build
env:
IMAGE: ${{ matrix.config.image }}
CUDA: ${{ matrix.config.cuda }}
run: |
docker/bash.sh --no-gpu $IMAGE ./conda/build_cuda.sh conda/build_config.yaml --cuda $CUDA
- name: Conda-Deploy
if: github.ref == 'refs/heads/main'
shell: bash -l {0}
env:
ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_TOKEN }}
run: >-
anaconda upload --force --label main conda/pkg/linux-64/*.tar.bz2