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TorchBench Nightly

TorchBench Nightly #17

Workflow file for this run

name: TorchBench Nightly
on:
workflow_dispatch:
env:
TRITON_USE_ASSERT_ENABLED_LLVM: "TRUE"
jobs:
TorchBench-Nvidia:
runs-on: [self-hosted, A100]
steps:
- name: Checkout TorchBench
uses: actions/checkout@v4
with:
repository: 'pytorch/benchmark'
ref: '7dc8e8113f8d5dc97aaa2bef94f9d389047cfcde'
path: 'torchbench'
submodules: 'recursive'
- name: Create Python venv
run: |
python3 -m venv ${HOME}/torchbench/venv
source ${HOME}/torchbench/venv/bin/activate
echo PATH=${PATH} >> $GITHUB_ENV
# We don't want to use to use TorchBench nightlies here
- name: Install TorchBench and models
run: |
python3 -m pip install --upgrade pip
python3 -m pip install --upgrade torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
cd torchbench
python3 install.py detectron2_fasterrcnn_r_101_c4
- name: Install the latest Triton wheel
run: |
python3 -m pip install --upgrade triton-nightly --index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/Triton-Nightly/pypi/simple/
- name: Tune Nvidia GPU
run: |
sudo nvidia-smi -pm 1
sudo nvidia-smi --lock-gpu-clocks=1280,1280
nvidia-smi
- name: Run TorchBench
run: |
cd torchbench
python3 test.py -v TestBenchmark.test_detectron2_fasterrcnn_r_101_c4_train_cuda
- name: Cleanup and reset GPU clocks
if: always()
run: |
sudo nvidia-smi -i 0 -rgc