Skip to content

TorchFT 8 GPU Integration Test #733

TorchFT 8 GPU Integration Test

TorchFT 8 GPU Integration Test #733

name: TorchFT 8 GPU Integration Test
on:
push:
branches: [ main ]
tags:
- ciflow/8gpu/*
paths:
- 'torchtitan/components/ft.py'
- '.github/workflows/integration_test_8gpu_torchft.yaml'
pull_request:
paths:
- 'torchtitan/components/ft.py'
- '.github/workflows/integration_test_8gpu_torchft.yaml'
schedule:
# Runs every 6 hours
- cron: '0 */6 * * *'
concurrency:
group: unit-test${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number || github.ref }}
cancel-in-progress: true
defaults:
run:
shell: bash -l -eo pipefail {0}
permissions:
id-token: write
contents: read
jobs:
# Step 1: Dynamically compute the matrix based on conditions
set-matrix:
uses: ./.github/workflows/set-matrix.yaml
# Step 2: Use the dynamic matrix in the build-test job
build-test:
needs: set-matrix
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
strategy:
fail-fast: false
matrix: ${{ fromJSON(needs.set-matrix.outputs.matrix) }}
with:
runner: ${{ matrix.runner }}
gpu-arch-type: ${{ matrix.gpu-arch-type }}
gpu-arch-version: ${{ matrix.gpu-arch-version }}
docker-image: ${{ matrix.docker-image }}
repository: pytorch/torchtitan
upload-artifact: outputs
timeout: 45
script: |
set -eux
# The generic Linux job chooses to use base env, not the one setup by the image
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
conda activate "${CONDA_ENV}"
# Log CUDA driver version for debugging.
DRIVER_VERSION=$(nvidia-smi --query-gpu=driver_version --format=csv,noheader | head -n 1 || true)
echo "CUDA driver version: ${DRIVER_VERSION}"
pip config --user set global.progress_bar off
python -m pip install torchft-nightly
python -m pip install --force-reinstall --pre torch --index-url ${{ matrix.index-url }}
USE_CPP=0 python -m pip install --pre torchao --index-url ${{ matrix.index-url }}
sudo mkdir -p "$RUNNER_TEMP/artifacts-to-be-uploaded"
sudo chown -R $(id -u):$(id -g) "$RUNNER_TEMP/artifacts-to-be-uploaded"
echo "torchft_lighthouse"
RUST_BACKTRACE=1 torchft_lighthouse --min_replicas 1 --quorum_tick_ms 100 --join_timeout_ms 10000 > /dev/null 2>&1 &
echo "ft_integration_test"
# Getting error - Cuda failure 217 'peer access is not supported between these two devices'
python -m tests.integration_tests.ft $RUNNER_TEMP/artifacts-to-be-uploaded --ngpu 8
# pkill -9 torchft_lighthouse
rm -rf $RUNNER_TEMP/artifacts-to-be-uploaded/*/checkpoint