[ci] Run all tests on (self-hosted) GPU (#3020)
* Create self-hosted.yml * Update self-hosted.yml * Update self-hosted.yml * Update self-hosted.yml * Update self-hosted.yml * Update self-hosted.yml * do not run slow tests, for now * [ci] For comparison with circleci, let's also run CPU-tests * [ci] reorganize * clearer filenames * [ci] Final tweaks before merging * rm slow tests on circle ci * Trigger CI * On GPU this concurrency was way too high
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.github/workflows/self-push.yml
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47
.github/workflows/self-push.yml
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name: Self-hosted runner (push)
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on:
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push:
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branches:
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- master
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pull_request:
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jobs:
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run_tests_torch_and_tf_gpu:
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runs-on: self-hosted
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steps:
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- uses: actions/checkout@v2
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- name: Python version
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run: |
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which python
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python --version
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pip --version
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- name: Current dir
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run: pwd
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- run: nvidia-smi
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- name: Create new python env (on self-hosted runners we have to handle isolation ourselves)
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run: |
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python -m venv .env
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source .env/bin/activate
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which python
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python --version
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pip --version
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- name: Install dependencies
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run: |
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source .env/bin/activate
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pip install .[sklearn,tf,torch,testing]
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- name: Are GPUs recognized by our DL frameworks
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run: |
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source .env/bin/activate
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python -c "import torch; print(torch.cuda.is_available())"
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python -c "import tensorflow as tf; print(tf.test.is_built_with_cuda(), tf.config.list_physical_devices('GPU'))"
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- name: Run all non-slow tests on GPU
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env:
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OMP_NUM_THREADS: 1
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USE_CUDA: yes
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run: |
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source .env/bin/activate
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python -m pytest -n 2 --dist=loadfile -s -v ./tests/
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