Add Pytorch memory stats along with PyNVML #81
Workflow file for this run
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name: OnnxRuntime CUDA Training Tests | |
on: | |
workflow_dispatch: | |
pull_request: | |
types: [opened, reopened, synchronize] | |
concurrency: | |
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} | |
cancel-in-progress: true | |
jobs: | |
build_image_and_run_gpu_tests: | |
runs-on: hf-dgx-01 | |
steps: | |
- name: Checkout | |
uses: actions/checkout@v2 | |
- name: Build image | |
run: docker build | |
--file docker/cuda.dockerfile | |
--build-arg USER_ID=$(id -u) | |
--build-arg GROUP_ID=$(id -g) | |
--build-arg CUDA_VERSION=11.8.0 | |
--build-arg TORCH_CUDA=cu118 | |
--tag opt-bench-cuda:11.8.0 | |
. | |
- name: Run tests | |
run: docker run | |
--rm | |
--gpus '"device=0,1"' | |
--entrypoint /bin/bash | |
--volume $(pwd):/workspace/optimum-benchmark | |
--workdir /workspace/optimum-benchmark | |
--env TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" | |
--env USE_CUDA="1" | |
opt-bench-cuda:11.8.0 | |
-c "pip install -e .[test,onnxruntime-training,peft] && python -m torch_ort.configure && pytest -k 'cuda and onnxruntime and training' -x" |