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ssh-runner.yml
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name: SSH into our runners
on:
workflow_dispatch:
inputs:
runner_type:
description: 'Type of runner to test (a10 or t4)'
required: true
docker_image:
description: 'Name of the Docker image'
required: true
num_gpus:
description: 'Type of the number of gpus to use (`single` or `multi`)'
required: true
env:
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes # For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access. # This token is created under the bot `hf-transformers-bot`.
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
CUDA_VISIBLE_DEVICES: 0,1
RUN_PT_TF_CROSS_TESTS: 1
jobs:
ssh_runner:
name: "SSH"
runs-on: ["${{ github.event.inputs.num_gpus }}-gpu", nvidia-gpu, "${{ github.event.inputs.runner_type }}", ci]
container:
image: ${{ github.event.inputs.docker_image }}
options: --gpus all --privileged --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Update clone
working-directory: /transformers
run: |
git fetch && git checkout ${{ github.sha }}
- name: Cleanup
working-directory: /transformers
run: |
rm -rf tests/__pycache__
rm -rf tests/models/__pycache__
rm -rf reports
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Tailscale # In order to be able to SSH when a test fails
uses: huggingface/tailscale-action@main
with:
authkey: ${{ secrets.TAILSCALE_SSH_AUTHKEY }}
slackChannel: ${{ secrets.SLACK_CIFEEDBACK_CHANNEL }}
slackToken: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
waitForSSH: true