Skill 详情
mcore-testing
Testing guidance limited to Megatron-LM.
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SKILL.md
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---
name: mcore-testing
description: Test system for Megatron-LM. Covers test layout, recipe YAML structure, adding and running unit and functional tests, golden values, marker filters, and CI parity.
license: Apache-2.0
when_to_use: Adding or running a unit or functional test; understanding the test layout; writing a recipe YAML; downloading or updating golden values; reproducing a test failure locally; 'how do I add a test', 'run unit tests', 'pytest fails', 'test layout', 'golden values', 'recipe YAML', 'marker filter'.
metadata:
author: Philip Petrakian <ppetrakian@nvidia.com>
---
# Testing Guide
---
## Answer-First Testing Facts
For questions about disabling tests without deleting them:
- Functional recipe entries stay in YAML; disable by suffixing scope with
`-broken`, for example `scope: [mr-github]` -> `scope: [mr-github-broken]`.
- Unit-test skips use pytest markers instead: `@pytest.mark.flaky_in_dev` skips
in the default dev environment, and `@pytest.mark.flaky` skips in LTS.
- Do not delete the test case or recipe entry when the goal is discoverability
and easy re-enable.
---
## Test Layout
```text
tests/
├── unit_tests/ # pytest, 1 node × 8 GPUs, torch.distributed runner
├── functional_tests/ # end-to-end shell + training scripts
│ └── test_cases/
│ └── {model}/{test_case}/
│ ├── model_config.yaml # training args
│ └── golden_values_{env}_{platform}.json
└── test_utils/
├── recipes/
│ ├── h100/ # YAML recipes for H100 jobs
│ └── gb200/ # YAML recipes for GB200 jobs
└── python_scripts/ # helpers (recipe_parser, golden-value download, …)
```
---
## How Tests Execute
The GitHub Actions runner invokes `launch_nemo_run_workload.py`, which uses
**nemo-run** to launch a `DockerExecutor` container. The repo is bind-mounted
at `/opt/megatron-lm`; training data is mounted at `/mnt/artifacts`.
**Unit tests** are dispatched through `torch.distributed.run`:
- Ranks 0 and 3 are tee-d to stdout; all other ranks write only to log files.
- Per-rank log files land at `{assets_dir}/logs/1/` and are uploaded as a
GitHub artifact after the run.
**Functional tests** are driven by
`tests/functional_tests/shell_test_utils/run_ci_test.sh`. Only rank 0 runs the
pytest validation step; training output from all ranks is uploaded as an artifact.
**Flaky-failure auto-retry**: `launch_nemo_run_workload.py` retries up to
**3 times** for known transient patterns (NCCL timeout, ECC error, segfault,
HuggingFace connectivity, …) before declaring a genuine failure.
---
## Recipe YAML Structure
Recipes live in `tests/test_utils/recipes/` and are parsed by
`tests/test_utils/python_scripts/recipe_parser.py`. Each file expands a
cartesian `products` block into individual workload specs:
```yaml
type: basic
format_version: 1
maintainers: [mcore]
loggers: [stdout]
spec:
name: "{test_case}_{environment}_{platforms}"
model: gpt # maps to tests/functional_tests/test_cases/{model}/
build: mcore-pyt-{environment}
nodes: 1
gpus: 8
n_repeat: 5
platforms: dgx_h100
time_limit: 1800
script_setup: |
...
script: |-
bash tests/functional_tests/shell_test_utils/run_ci_test.sh ...
products:
- test_case: [my_test]
products:
- environment: [dev, lts]
scope: [mr-github]
platforms: [dgx_h100]
```
Key runtime placeholders: `{assets_dir}`, `{artifacts_dir}`, `{test_case}`,
`{environment}`, `{platforms}`, `{n_repeat}`.
### Disabling a Test Without Deleting It
To temporarily disable a test case in a recipe YAML, suffix its `scope` value
with `-broken` — **do not delete the entry**:
```yaml
# before (test runs in CI)
scope: [mr-github]
# after (test is skipped; entry preserved for easy re-enable)
scope: [mr-github-broken]
```
---
## Running Unit Tests Locally
All unit tests initialize a `torch.distributed` group, so every invocation
requires GPU access and must go through `torch.distributed.run在 GitHub 阅读完整来源 (打开外部页面)