# # 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: checkpoint_converter # latest version: Megatron-LM core_r0.11.0 https://github.com/NVIDIA/Megatron-LM/tree/core_r0.11.0 on: # Trigger the workflow on push or pull request, # but only for the main branch push: branches: - main - v0.* pull_request: branches: - main - v0.* paths: - "**/*.py" # Other entrypoints - "!examples/**" - "!tests/**" - "!verl/trainer/main_*.py" - "!verl/trainer/fsdp_sft_trainer.py" # Recipes - "!recipe/**" # FSDP - "!verl/workers/**/*dp_*.py" # Entrypoints - ".github/workflows/checkpoint_converter.yml" - ".github/workflows/e2e_ppo_trainer_megatron.yml" - "examples/data_preprocess/gsm8k.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 jobs: checkpoint_converter: runs-on: [L20x8] timeout-minutes: 20 # 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_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable container: image: verlai/verl:app-verl0.5-sglang0.4.8-mcore0.12.2-te2.2 options: --gpus all --shm-size=10g steps: - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2 with: fetch-depth: 0 - name: Install the current repository run: | pip3 install -e .[test] - name: Download Model to Use run: | huggingface-cli download Qwen/Qwen2.5-0.5B --local-dir ${HOME}/models/Qwen/Qwen2.5-0.5B huggingface-cli download deepseek-ai/deepseek-coder-1.3b-instruct --local-dir ${HOME}/models/deepseek-ai/deepseek-coder-1.3b-instruct export HF_HUB_OFFLINE=1 - name: Running Huggingface to Megatron dist_ckpt converter (Qwen/Qwen2.5-0.5B) run: | ray stop --force python scripts/converter_hf_to_mcore.py --hf_model_path=${HOME}/models/Qwen/Qwen2.5-0.5B --output_path checkpoints/Qwen/Qwen2.5-0.5B --test - name: Running Huggingface to Megatron dist_ckpt converter (deepseek-ai/deepseek-coder-1.3b-instruct) run: | ray stop --force python scripts/converter_hf_to_mcore.py --hf_model_path=${HOME}/models/deepseek-ai/deepseek-coder-1.3b-instruct --output_path checkpoints/deepseek-ai/deepseek-coder-1.3b-instruct --test - name: Clean up run: | rm -rf checkpoints checkpoint_converter_large_moe_models: runs-on: [L20x8] timeout-minutes: 30 # 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_HUB_ENABLE_HF_TRANSFER: "0" # This is more stable HF_ENDPOINT: "https://hf-mirror.com" container: image: verlai/verl:app-verl0.5-sglang0.4.8-mcore0.12.2-te2.2 options: --gpus all --shm-size=10g steps: - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2 with: fetch-depth: 0 - name: Install the current repository run: | pip3 install -e .[test] - name: Download Model to Use run: | huggingface-cli download Qwen/Qwen1.5-MoE-A2.7B-Chat --local-dir ${HOME}/models/Qwen/Qwen1.5-MoE-A2.7B-Chat export HF_HUB_OFFLINE=1 - name: Running Huggingface to Megatron dist_ckpt CPU converter (Qwen/Qwen1.5-MoE-A2.7B-Chat) run: | ray stop --force python scripts/converter_hf_to_mcore.py --hf_model_path=${HOME}/models/Qwen/Qwen1.5-MoE-A2.7B-Chat --output_path checkpoints/Qwen/Qwen1.5-MoE-A2.7B-Chat --use_cpu_initialization - name: Running distributed Huggingface to Megatron dist_ckpt CPU converter (Qwen/Qwen1.5-MoE-A2.7B-Chat) run: | ray stop --force torchrun --nproc_per_node 8 --nnodes 1 scripts/converter_hf_to_mcore.py --hf_model_path=${HOME}/models/Qwen/Qwen1.5-MoE-A2.7B-Chat --output_path checkpoints/Qwen/Qwen1.5-MoE-A2.7B-Chat_dist --use_cpu_initialization - name: clean up run: | rm -rf checkpoints