verl/.github/workflows/e2e_ppo_trainer_megatron_sglang_2.yml

# # Tests layout

# Each folder under tests/ corresponds to a test category for a sub-namespace in verl. For instance:
# - `tests/trainer` for testing functionality related to `verl/trainer`
# - `tests/models` for testing functionality related to `verl/models`
# - ...

# There are a few folders with `special_` prefix, created for special purposes:
# - `special_distributed`: unit tests that must run with multiple GPUs
# - `special_e2e`: end-to-end tests with training/generation scripts
# - `special_npu`: tests for NPUs
# - `special_sanity`: a suite of quick sanity tests
# - `special_standalone`: a set of test that are designed to run in dedicated environments

# Accelerators for tests
# - By default tests are run with GPU available, except for the ones under `special_npu`, and any test script whose name ends with `on_cpu.py`.
# - For test scripts with `on_cpu.py` name suffix would be tested on CPU resources in linux environment.

# # Workflow layout

# All CI tests are configured by yaml files in `.github/workflows/`. Here's an overview of all test configs:
# 1. A list of always triggered CPU sanity tests: `check-pr-title.yml`, `secrets_scan.yml`, `check-pr-title,yml`, `pre-commit.yml`, `doc.yml`
# 2. Some heavy multi-GPU unit tests, such as `model.yml`, `vllm.yml`, `sgl.yml`
# 3. End-to-end tests: `e2e_*.yml`
# 4. Unit tests
#   - `cpu_unit_tests.yml`, run pytest on all scripts with file name pattern `tests/**/test_*_on_cpu.py`
#   - `gpu_unit_tests.yml`, run pytest on all scripts with file without the `on_cpu.py` suffix.
#   - Since cpu/gpu unit tests by default runs all tests under `tests`, please make sure tests are manually excluded in them when
#     - new workflow yaml is added to `.github/workflows`
#     - new tests are added to workflow mentioned in 2.

name: e2e_ppo_trainer_megatron_sglang_2

on:
  # Trigger the workflow on push or pull request,
  # but only for the main branch.
  # For push, for now only anti-patterns are specified so it is more conservative
  # and achieves higher coverage.
  push:
    branches:
      - main
      - v0.*
    paths:
      - "**/*.py"
      # Other entrypoints
      - "!verl/trainer/fsdp_sft_trainer.py"
      # Recipes
      - "!recipe/**"
      # FSDP
      - "!verl/workers/**/*dp_*.py"
  pull_request:
    branches:
      - main
      - v0.*
    paths:
      - "**/*.py"
      # Other entrypoints
      - "!docker/**"
      # Docs
      - "!**/*.md"
      - "!docs/**"
      - "!examples/**"
      - "!tests/**"
      - "!verl/trainer/main_*.py"
      - "!verl/trainer/fsdp_sft_trainer.py"
      # Recipes
      - "!recipe/**"
      # FSDP
      - "!verl/workers/**/*dp_*.py"
      # Entrypoints
      - "verl/worksers/rollout/sglang_rollout/*"
      - ".github/workflows/e2e_ppo_trainer_megatron_sglang.yml"
      - "examples/data_preprocess/gsm8k.py"
      - "examples/data_preprocess/geo3k.py"
      - "tests/special_e2e/run_ppo_trainer_megatron.sh"
      - "verl/trainer/main_ppo.py"
      - "verl/trainer/config/ppo_megatron_trainer.yaml"

# Cancel jobs on the same ref if a new one is triggered
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}

# Declare permissions just read content.
permissions:
  contents: read

env:
  IMAGE: "verl-ci-cn-beijing.cr.volces.com/verlai/verl:app-verl0.6-transformers4.56.1-sglang0.5.2-mcore0.13.0-te2.2"
  DYNAMIC_RUNNER_ENDPOINT: "https://sd10g3clalm04ug7alq90.apigateway-cn-beijing.volceapi.com/runner"

jobs:
  setup:
    if: github.repository_owner == 'volcengine'
    runs-on: ubuntu-latest
    outputs:
      runner-label: ${{ steps.create-runner.outputs.runner-label }}
      mlp-task-id: ${{ steps.create-runner.outputs.mlp-task-id }}
    steps:
      - uses: actions/checkout@v4
      - id: create-runner
        uses: volcengine/vemlp-github-runner@v1
        with:
          mode: "create"
          faas-url: "${{ env.DYNAMIC_RUNNER_ENDPOINT }}"
          mlp-image: "${{ env.IMAGE }}"

  e2e_ppo_trainer_megatron-moe-expert-parallel:
    needs: setup
    runs-on: ["${{ needs.setup.outputs.runner-label || 'L20x8' }}"]
    timeout-minutes: 60 # Increase this timeout value as needed
    env:
      HTTP_PROXY: ${{ secrets.PROXY_HTTP }}
      HTTPS_PROXY: ${{ secrets.PROXY_HTTPS }}
      NO_PROXY: "localhost,127.0.0.1,hf-mirror.com"
      HF_ENDPOINT: "https://hf-mirror.com"
      HF_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable
    steps:
      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
        with:
          fetch-depth: 0
      - name: Install the current repository
        run: |
          pip3 install --no-deps -e .[test]
      - name: Prepare GSM8K dataset
        run: |
          python3 examples/data_preprocess/gsm8k.py --local_dataset_path ${HOME}/models/hf_data/gsm8k
      - name: Running GSM8K E2E training tests with 3D parallelism on 8 L20 GPUs with Megatron (DeepSeek)
        run: |
          ray stop --force
          MEGATRON_CI_DISABLE_EXPANDABLE_SEGMENTS=1 \
          ADV_ESTIMATOR=grpo USE_DUMMY_MODEL=True DUMMY_MODEL_CONFIG_PATH=tests/special_e2e/ppo_trainer/expert_parallel/qwen2moe_minimal.json \
          PPO_MAX_TOKEN_LEN=512 FWD_MAX_TOKEN_LEN=512 \
          MAX_PROMPT_LENGTH=256 MAX_RESPONSE_LENGTH=256 \
          MODEL_ID=Qwen/Qwen1.5-MoE-A2.7B-Chat \
          ENGINE=sglang COMMON_PP=2 COMMON_VPP=null COMMON_CP=1 COMMON_TP=4 COMMON_EP=4 COMMON_ETP=1 INFER_TP=8 \
          USE_DIST_CKPT=True ALL_OFFLOAD=True SKIP_SAVE_HF_MODEL=1 bash tests/special_e2e/run_ppo_trainer_megatron.sh
      - name: clean up
        run: |
          rm -rf checkpoints

  e2e_ppo_trainer_megatron-qwen2_5vl-3b:
    needs: setup
    runs-on: ["${{ needs.setup.outputs.runner-label || 'L20x8' }}"]
    timeout-minutes: 60 # Increase this timeout value as needed
    env:
      HTTP_PROXY: ${{ secrets.PROXY_HTTP }}
      HTTPS_PROXY: ${{ secrets.PROXY_HTTPS }}
      NO_PROXY: "localhost,127.0.0.1,hf-mirror.com"
      HF_ENDPOINT: "https://hf-mirror.com"
      HF_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable
    steps:
      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
        with:
          fetch-depth: 0
      - name: Install the current repository
        run: |
          pip3 install --no-deps -e .[test]
      - name: Prepare Geo3k dataset
        run: |
          python3 examples/data_preprocess/geo3k.py --local_dataset_path ${HOME}/models/hf_data/hiyouga/geometry3k/
      - name: Prepare dist_ckpt of Qwen2.5-VL-3B, only supports dist_ckpt
        run: |
          python3 scripts/converter_hf_to_mcore.py --hf_model_path ${HOME}/models/Qwen/Qwen2.5-VL-3B-Instruct --output_path checkpoints/verl-test/qwen2.5-vl-3b-megatron
      - name: Running Geo3k E2E training tests with 3D parallelism on 8 L20 GPUs with Megatron (Qwen)
        run: |
          ray stop --force
          ENGINE=sglang TRAIN_FILES=${HOME}/data/geo3k/train.parquet VAL_FILES=${HOME}/data/geo3k/test.parquet MAX_PROMPT_LENGTH=1024 MAX_RESPONSE_LENGTH=2048  MODEL_ID=Qwen/Qwen2.5-VL-3B-Instruct ADV_ESTIMATOR=grpo USE_DYNAMIC_BSZ=False SKIP_SAVE_HF_MODEL=1 COMMON_PP=4 COMMON_VPP=null COMMON_CP=1 COMMON_TP=2 USE_DIST_CKPT=true DIST_CKPT_PATH=checkpoints/verl-test/qwen2.5-vl-3b-megatron bash tests/special_e2e/run_ppo_trainer_megatron.sh
      - name: clean up
        run: |
          rm -rf checkpoints

  e2e_ppo_trainer_sglang:
    needs: setup
    runs-on: [ "${{ needs.setup.outputs.runner-label || 'L20x8' }}" ]
    timeout-minutes: 40 # Increase this timeout value as needed
    env:
      HTTP_PROXY: ${{ secrets.PROXY_HTTP }}
      HTTPS_PROXY: ${{ secrets.PROXY_HTTPS }}
      NO_PROXY: "localhost,127.0.0.1,hf-mirror.com"
      HF_ENDPOINT: "https://hf-mirror.com"
      HF_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable
    steps:
      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
        with:
          fetch-depth: 0
      - name: Install the current repository
        run: |
          pip3 install -e .[test,gpu,sglang]
      - name: Prepare gsm8k dataset
        run: |
          ray stop --force
          python3 examples/data_preprocess/gsm8k.py --local_dataset_path ${HOME}/models/hf_data/gsm8k
      - name: Running GSM8K E2E training tests on 8 L20 GPUs with rmpad using function rm and save ckpt
        run: |
          ray stop --force
          ENGINE=sglang bash tests/special_e2e/ppo_trainer/run_function_reward.sh
      - name: Running GSM8K E2E training tests on sglang async
        run: |
          ray stop --force
          TOTAL_TRAIN_STEPS=2 ENGINE=sglang ROLLOUT_MODE=async bash tests/special_e2e/ppo_trainer/run_function_reward.sh

  e2e_ppo_trainer_sglang_vlm:
    needs: setup
    runs-on: [ "${{ needs.setup.outputs.runner-label || 'L20x8' }}" ]
    timeout-minutes: 60 # Increase this timeout value as needed
    env:
      HTTP_PROXY: ${{ secrets.PROXY_HTTP }}
      HTTPS_PROXY: ${{ secrets.PROXY_HTTPS }}
      NO_PROXY: "localhost,127.0.0.1,hf-mirror.com"
      HF_ENDPOINT: "https://hf-mirror.com"
      HF_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable
    steps:
      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
        with:
          fetch-depth: 0
      - name: Install the current repository
        run: |
          pip3 install -e .[test,geo,gpu,sglang] --no-deps
      # Geo3k
      - name: Prepare GEO3K dataset
        run: |
          ray stop --force
          python3 examples/data_preprocess/geo3k.py --local_dataset_path ${HOME}/models/hf_data/hiyouga/geometry3k/
      - name: Running GEO3K VLM E2E training tests on 8 L20 GPUs with rmpad using function rm
        run: |
          ray stop --force
          TRAIN_FILES=$HOME/data/geo3k/train.parquet VAL_FILES=$HOME/data/geo3k/test.parquet \
            MAX_PROMPT_LEN=1536 MAX_RESPONSE_LEN=1536 \
            MODEL_ID=Qwen/Qwen2-VL-2B-Instruct \
            ADV_ESTIMATOR=grpo RM_PAD=True USE_KL=True ENABLE_CHUNKED_PREFILL=False \
            ENGINE=sglang GPU_MEMORY_UTILIZATION=0.6 ACTOR_FSDP_PARAM_OFFLOAD=True \
            ACTOR_FSDP_OPTIMIZER_OFFLOAD=True REF_FSDP_PARAM_OFFLOAD=True \
            bash tests/special_e2e/ppo_trainer/run_function_reward.sh
      - name: Running GEO3K VLM E2E with rmpad using torch fused kernel (Qwen2.5-VL)
        run: |
          ray stop --force
          FUSED_KERNELS=True TRAIN_FILES=$HOME/data/geo3k/train.parquet VAL_FILES=$HOME/data/geo3k/test.parquet \
            MAX_PROMPT_LEN=1536 MAX_RESPONSE_LEN=1536 \
            MODEL_ID=Qwen/Qwen2.5-VL-3B-Instruct \
            ADV_ESTIMATOR=grpo RM_PAD=True USE_KL=True ENABLE_CHUNKED_PREFILL=False \
            ENGINE=sglang GPU_MEMORY_UTILIZATION=0.6 ACTOR_FSDP_PARAM_OFFLOAD=True \
            ACTOR_FSDP_OPTIMIZER_OFFLOAD=True REF_FSDP_PARAM_OFFLOAD=True \
            bash tests/special_e2e/ppo_trainer/run_function_reward.sh
      - name: Running GEO3K VLM E2E with rmpad using triton fused kernel (Qwen2.5-VL)
        run: |
          ray stop --force
          FUSED_KERNELS=True FUSED_KERNEL_BACKEND=triton \
            TRAIN_FILES=$HOME/data/geo3k/train.parquet VAL_FILES=$HOME/data/geo3k/test.parquet \
            MAX_PROMPT_LEN=1536 MAX_RESPONSE_LEN=1536 \
            MODEL_ID=Qwen/Qwen2.5-VL-3B-Instruct \
            ADV_ESTIMATOR=grpo RM_PAD=True USE_KL=True ENABLE_CHUNKED_PREFILL=False \
            ENGINE=sglang GPU_MEMORY_UTILIZATION=0.6 ACTOR_FSDP_PARAM_OFFLOAD=True \
            ACTOR_FSDP_OPTIMIZER_OFFLOAD=True REF_FSDP_PARAM_OFFLOAD=True \
            bash tests/special_e2e/ppo_trainer/run_function_reward.sh


  cleanup:
    runs-on: ubuntu-latest
    needs:
      [
        setup,
        e2e_ppo_trainer_megatron-moe-expert-parallel,
        e2e_ppo_trainer_megatron-qwen2_5vl-3b,
        e2e_ppo_trainer_sglang,
        e2e_ppo_trainer_sglang_vlm
      ]
    if: always()
    steps:
      - id: destroy-runner
        uses: volcengine/vemlp-github-runner@v1
        with:
          mode: "destroy"
          faas-url: "${{ env.DYNAMIC_RUNNER_ENDPOINT }}"
          mlp-task-id: "${{ needs.setup.outputs.mlp-task-id }}"