lightning/.azure/gpu-benchmarks.yml

112 lines
3.4 KiB
YAML

# Python package
# Create and test a Python package on multiple Python versions.
# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
# https://docs.microsoft.com/azure/devops/pipelines/languages/python
trigger:
tags:
include: ["*"]
branches:
include:
- "master"
- "release/*"
- "refs/tags/*"
pr:
branches:
include:
- "master"
- "release/*"
paths:
include:
- ".azure/gpu-benchmarks.yml"
- "requirements/fabric/**"
- "requirements/pytorch/**"
- "src/lightning/fabric/**"
- "src/lightning/pytorch/**"
- "tests/parity_fabric/**"
- "tests/parity_pytorch/**"
exclude:
- "requirements/*/docs.txt"
- "*.md"
- "**/*.md"
schedules:
- cron: "0 0 * * *" # At the end of every day
displayName: Daily midnight benchmark
branches:
include:
- "master"
jobs:
- job: benchmarks
timeoutInMinutes: "90"
cancelTimeoutInMinutes: "2"
pool: lit-rtx-3090
variables:
DEVICES: $( python -c 'print("$(Agent.Name)".split("_")[-1])' )
container:
# TODO: Upgrade to Python 3.11
image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.2-cuda12.1.0"
options: "--gpus=all --shm-size=32g"
strategy:
matrix:
"pkg: Fabric":
PACKAGE_NAME: "fabric"
"pkg: Pytorch":
PACKAGE_NAME: "pytorch"
workspace:
clean: all
steps:
- bash: |
echo "##vso[task.setvariable variable=CUDA_VISIBLE_DEVICES]$(DEVICES)"
cuda_ver=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda.split('.')[:2])))")
echo "##vso[task.setvariable variable=TORCH_URL]https://download.pytorch.org/whl/cu${cuda_ver}/torch_stable.html"
displayName: "set env. vars"
- bash: |
echo $CUDA_VISIBLE_DEVICES
echo $TORCH_URL
whereis nvidia
nvidia-smi
which python && which pip
python --version
pip --version
pip list
displayName: "Image info & NVIDIA"
- bash: pip install -e .[dev] --find-links ${TORCH_URL}
env:
FREEZE_REQUIREMENTS: "1"
displayName: "Install package"
- bash: |
set -e
python requirements/collect_env_details.py
python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu == 2, f'GPU: {mgpu}'"
displayName: "Env details"
- bash: |
pip install -q -r .actions/requirements.txt
python .actions/assistant.py copy_replace_imports --source_dir="./tests" \
--source_import="lightning.fabric,lightning.pytorch" \
--target_import="lightning_fabric,pytorch_lightning"
displayName: "Adjust tests"
- bash: python -m pytest parity_$(PACKAGE_NAME) -v --durations=0
env:
PL_RUNNING_BENCHMARKS: "1"
PL_RUN_CUDA_TESTS: "1"
workingDirectory: tests/
displayName: "Testing: benchmarks"
- bash: bash run_standalone_tasks.sh
workingDirectory: tests/parity_fabric
# without succeeded this could run even if the job has already failed
condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'fabric'))
env:
PL_RUN_CUDA_TESTS: "1"
displayName: "Testing: fabric standalone tasks"
timeoutInMinutes: "10"