Benchmarking tests #4

	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: \|
	apt-get update && apt-get install libsndfile1-dev libgl1 -y
	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:
	HUGGING_FACE_HUB_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

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