benchmark.yml

name: Benchmarking tests

on:
  workflow_dispatch:
  schedule:
    - cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM

env:
  DIFFUSERS_IS_CI: yes
  HF_HOME: /mnt/cache
  OMP_NUM_THREADS: 8
  MKL_NUM_THREADS: 8

jobs:
  torch_pipelines_cuda_benchmark_tests:
    name: Torch Core Pipelines CUDA Benchmarking Tests
    strategy:
      fail-fast: false
      max-parallel: 1
    runs-on: [single-gpu, nvidia-gpu, a10, ci]
    container:
      image: diffusers/diffusers-pytorch-cuda
      options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
    steps:
      - name: Checkout diffusers
        uses: actions/checkout@v3
        with:
          fetch-depth: 2
      - name: NVIDIA-SMI
        run: |
          nvidia-smi
      - name: Install dependencies
        run: |
          python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
          python -m uv pip install -e [quality,test]
          python -m uv pip install pandas peft
      - name: Environment
        run: |
          python utils/print_env.py
      - name: Diffusers Benchmarking
        env:
            HF_TOKEN: ${{ secrets.DIFFUSERS_BOT_TOKEN }}
            BASE_PATH: benchmark_outputs
        run: |
          export TOTAL_GPU_MEMORY=$(python -c "import torch; print(torch.cuda.get_device_properties(0).total_memory / (1024**3))")
          cd benchmarks && mkdir ${BASE_PATH} && python run_all.py && python push_results.py

      - name: Test suite reports artifacts
        if: ${{ always() }}
        uses: actions/upload-artifact@v2
        with:
          name: benchmark_test_reports
          path: benchmarks/benchmark_outputs