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# Description
This PR implements and integrates the **Metax (MACA)** workflow into
TransformerEngine-FL. It enables automated CI/CD pipelines, functional
training tests, and unit tests specifically optimized for Metax hardware
environments.
**Key updates in this version:** Successful TE compilation on Metax and
alignment with NVIDIA's standard QA workflows.
Fixes # (issue_number_if_applicable)
## Type of change
- [x] New feature (non-breaking change which adds functionality)
- [x] Infra/Build change (changes to CI/CD workflows or build scripts)
- [ ] Documentation change
- [ ] Bug fix
- [ ] Code refactoring
## Changes
### 1. Build & Compilation
- **TE Build Completion**: Successfully completed the compilation and
build process for TransformerEngine on the Metax platform.
- **Workflow Alignment**: Designed the Metax testing workflow based on
NVIDIA's `qa-l0-te-cpp-unittest-pytorch-lint` standard to ensure parity
with upstream quality gates.
### 2. CI/CD Infrastructure & Test Modules
- **Metax Platform Support**: Added `configs/metax.yml` to define
Metax-specific runner labels, images, and device configurations.
- **Verified Workflow Modules**: The following modules have been
implemented and verified on the Metax platform:
- **pytorch-lint**: Static code analysis and linting.
- **pytorch-debug**: Debug-level build and basic functional
verification.
- **pytorch-unittest**: Core unit testing for Metax-adapted operators.
- **Workflow Modularization**:
- Introduced `configs/all_tests_common.yml` and
`configs/unit_tests_common.yml` for reusable test logic.
- Added `configs/all_tests_metax.yml` as the dedicated entry point for
Metax functional testing.
### 3. Environment & Runtime Fixes
- **Image Management**: Implemented `image-pull-policy: never` and
`--pull never` options to force the use of local registry images
(localhost:5000), optimizing startup time in local cluster environments.
- **Dynamic Resource Scaling**:
- Adapted `torchrun` and training scripts to support dynamic
GPU/Accelerator counts (specifically for C500 clusters).
- Removed hardcoded GPU host configurations to improve portability
across different Metax nodes.
### 4. Cleanup
- Removed legacy CUDA/Ascend specific configurations from the Metax
workflow path to prevent environment contamination.
## Hardware/Environment Verified
- **Platform**: Metax MACA
- **Accelerator**: C500
- **Registry**: Local Registry (localhost:5000)
---
## TODO / Next Steps
- [ ] Integrate the Metax-specific adaptation workflow into the central
platform.
- [ ] Generate and upload comprehensive Benchmark and Performance test
reports.
# Checklist:
- [x] I have read and followed the contributing guidelines.
- [x] The functionality is complete and verified on Metax hardware.
- [x] I have commented my code, particularly in hardware-specific
adaptation areas.
- [x] My changes generate no new warnings.
- [x] I have added/updated tests that prove my feature works on the MACA
platform.
- [x] New and existing unit tests (Lint, Debug, Unittest) pass locally
with Metax environment.
---------
Co-authored-by: 爱洗澡 qq <aixizaoqq@aixizaodeMacBook-Air.local>
Co-authored-by: zhoujiamei <2867770387@qq.com>
Co-authored-by: zhoujiamei <zjm>
Co-authored-by: peiyu <peiyu@jinglong.ai>
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