Files
vllm-omni/docs/contributing/ci/tests_markers.md
T

161 lines
7.1 KiB
Markdown

# Markers for Tests
By adding markers before test functions, tests can later be executed uniformly by simply declaring the corresponding marker type.
## Current Markers
Defined in `pyproject.toml`:
| Marker | Description |
| ------------------ | ------------------------------------------------------- |
| `core_model` | Core model tests (run in each PR) |
| `diffusion` | Diffusion model tests |
| `omni` | Omni model tests |
| `cache` | Cache backend tests |
| `parallel` | Parallelism/distributed tests |
| `cpu` | Tests that run on CPU |
| `gpu` | Tests that run on GPU (auto-added) |
| `cuda` | Tests that run on CUDA (auto-added) |
| `rocm` | Tests that run on AMD/ROCm (auto-added) |
| `npu` | Tests that run on NPU/Ascend (auto-added) |
| `H100` | Tests that require H100 GPU |
| `L4` | Tests that require L4 GPU |
| `MI325` | Tests that require MI325 GPU (AMD/ROCm) |
| `A2` | Tests that require A2 NPU |
| `A3` | Tests that require A3 NPU |
| `distributed_cuda` | Tests that require multi cards on CUDA platform |
| `distributed_rocm` | Tests that require multi cards on ROCm platform |
| `distributed_npu` | Tests that require multi cards on NPU platform |
| `skipif_cuda` | Skip if the num of CUDA cards is less than the required |
| `skipif_rocm` | Skip if the num of ROCm cards is less than the required |
| `skipif_npu` | Skip if the num of NPU cards is less than the required |
| `slow` | Slow tests (may skip in quick CI) |
| `benchmark` | Benchmark tests |
For those markers shown as auto-added, they will be added by the `@hardware_test` decorator.
### Example usage for markers
```python
from tests.utils import hardware_test
@pytest.mark.core_model
@pytest.mark.omni
@hardware_test(
res={"cuda": "L4", "rocm": "MI325", "npu": "A2"},
num_cards=2,
)
@pytest.mark.parametrize("omni_server", test_params, indirect=True)
def test_video_to_audio()
...
```
### Decorator: `@hardware_test`
This decorator is intended to make hardware-aware, cross-platform test authoring easier and more robust for CI/CD environments. The `hardware_test` decorator in `vllm-omni/tests/utils.py` performs the following actions:
1. **Applies platform and resource markers**
Adds the appropriate pytest markers for each specified hardware platform (e.g., `cuda`, `rocm`, `npu`) and resource type (e.g., `L4`, `H100`, `MI325`, `A2`, `A3`).
```
@pytest.mark.cuda
@pytest.mark.L4
```
2. **Handles multi-card (distributed) scenarios**
For tests requiring multiple cards, it automatically adds distributed markers such as `distributed_cuda`, `distributed_rocm`, or `distributed_npu`.
```
@pytest.mark.distributed_cuda(num_cards=num_cards)
```
3. **Supports flexible card requirements**
Accepts `num_cards` as either a single integer for all platforms or as a dictionary with per-platform values. If not specified, defaults to 1 card per platform.
4. **Integrates resource validation**
On CUDA, adds a skip marker (`skipif_cuda`) if the system does not have the required number of devices.
Support for `skipif_rocm` and `skipif_npu` will be implemented later.
5. **Runs each test in a new process**
Automatically wraps the distributed test with a decorator (`@create_new_process_for_each_test`) to ensure isolation and compatibility with multi-process hardware backends.
6. **Works with pytest filtering**
Allows tests to be filtered and selected at runtime using standard pytest marker expressions (e.g., `-m "distributed_cuda and L4"`).
#### Example usage for decorator
- Single call for multiple platforms:
```python
@hardware_test(
res={"cuda": "L4", "rocm": "MI325", "npu": "A2"},
num_cards={"cuda": 2, "rocm": 2, "npu": 2},
)
```
or
```python
@hardware_test(
res={"cuda": "L4", "rocm": "MI325", "npu": "A2"},
num_cards=2,
)
```
- `res` must be a dict; supported resources: CUDA (L4/H100), ROCm (MI325), NPU (A2/A3)
- `num_cards` can be int (all platforms) or dict (per platform); defaults to 1 when missing
- `hardware_test` automatically applies `@create_new_process_for_each_test` for distributed tests.
- Distributed markers (`distributed_cuda`, `distributed_rocm`, `distributed_npu`) are auto-added for multi-card cases
- Filtering examples:
- CUDA only: `pytest -m "distributed_cuda and L4"`
- ROCm only: `pytest -m "distributed_rocm and MI325"`
- NPU only: `pytest -m "distributed_npu"`
## Add Support for a New Platform
If you want to add support for a new platform (e.g., "tpu" for a new accelerator), follow these steps:
1. **Extend the marker list in your pytest config** so that platform/resource markers are defined:
```toml
# In pyproject.toml or pytest.ini
[tool.pytest.ini_options]
markers = [
# ... existing markers ...
"tpu: Tests that require TPU device",
"TPU_V3: Tests that require TPU v3 hardware",
"distributed_tpu: Tests that require multiple TPU devices",
]
```
2. **Implement a marker construction function for your platform** in `vllm-omni/tests/utils.py`:
```python
# In vllm-omni/tests/utils.py
def tpu_marks(*, res: str, num_cards: int):
test_platform = pytest.mark.tpu
if res == "TPU_V3":
test_resource = pytest.mark.TPU_V3
else:
raise ValueError(
f"Invalid TPU resource type: {res}. Supported: TPU_V3")
if num_cards == 1:
return [test_platform, test_resource]
else:
test_distributed = pytest.mark.distributed_tpu(num_cards=num_cards)
# Optionally: add skipif_tpu when implemented
return [test_platform, test_resource, test_distributed]
```
3. **Update `hardware_test` to recognize your new platform**:
In the relevant place (see the `hardware_test` implementation), add:
```python
if platform == "tpu":
marks = tpu_marks(res=resource, num_cards=cards)
```
4. **(Recommended) Add a test using your new markers**:
```python
@hardware_test(
res={"tpu": "TPU_V3"},
num_cards=2,
)
def test_my_tpu_feature():
...
```
**Summary**:
- Add pytest markers for your new platform/resources
- Implement a marker function (`xxx_marks`)
- Plug into `hardware_test`
- You're done: tests decorated with `@hardware_test` using your platform now automatically get the correct markers, distribution, and isolation!
See code in `vllm-omni/tests/utils.py` for existing examples (`cuda_marks`, `rocm_marks`, `npu_marks`).