Instructions to use KexuanShi/Megatron-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use KexuanShi/Megatron-LM with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
API Backward Compatibility Checking
Overview
Megatron Core uses automated API compatibility checking to ensure stable interfaces between releases. This prevents accidental breaking changes that could affect users upgrading between versions.
How It Works
The compatibility checker:
- Compares the current code against the latest release
- Detects breaking changes in function signatures
- Fails CI if breaking changes are found (unless explicitly exempted)
- Runs automatically on every PR that modifies
megatron/core
What Gets Checked
✅ Breaking Changes Detected
- Parameter removed - Removing a function parameter
- Parameter added without default - Adding a required parameter
- Parameter order changed - Changing the order of parameters
- Optional→Required - Removing a default value from a parameter
- Function removed - Deleting a public function
- Return type changed - Changing the return type annotation (warning)
⏭️ What Gets Skipped
- Test functions - Functions starting with
test_ - Exempt decorators - Functions marked with
@internal_api,@experimental_api, or@deprecated - Excluded paths - Code in
tests/,experimental/,legacy/
✅ Allowed Changes
- Adding optional parameters - Adding parameters with default values
- Adding new functions - New public APIs
- Making parameters optional - Adding default values to required parameters
For Developers
Running Locally
# Install griffe
pip install griffe
# Check against latest release
python scripts/check_api_backwards_compatibility.py --baseline core_r0.8.0
# Check with verbose output
python scripts/check_api_backwards_compatibility.py --baseline core_r0.8.0 -v
# Compare two specific branches
python scripts/check_api_backwards_compatibility.py --baseline core_r0.8.0 --current main
Marking Functions as Exempt
If you need to make breaking changes to internal or experimental APIs:
Internal API (for internal implementation details)
from megatron.core.utils import internal_api
@internal_api
def experimental_feature(x, y):
"""
This API is experimental and may change.
NOT FOR EXTERNAL USE.
"""
pass
When to use @internal_api:
- Internal APIs not documented for external use
- Experimental features explicitly marked as unstable
- Functions in development that haven't been released yet
Experimental API (for experimental features)
from megatron.core.utils import experimental_api
@experimental_api
def new_experimental_feature(x, y):
"""
This API is experimental and may change without notice.
"""
pass
When to use @experimental_api:
- Experimental features explicitly marked as unstable
- New APIs under active development
- Features that haven't been stabilized yet
Deprecating APIs
For planned API changes, use the deprecation workflow:
from megatron.core.backwards_compatibility_decorators import deprecated
@deprecated(
version="1.0.0", # When deprecation starts
removal_version="2.0.0", # When it will be removed
alternative="new_function", # Recommended replacement
reason="Improved performance and cleaner API"
)
def old_function(x):
"""This function is deprecated."""
pass
Deprecation Timeline:
- Version N - Add
@deprecateddecorator, function still works - Version N+1 - Keep function with deprecation warnings
- Version N+2 - Remove function (users have been warned)
Handling CI Failures
If the compatibility check fails on your PR:
- Review the breaking changes in the CI logs
- Choose an action:
- Fix the code - Revert the breaking change
- Add exemption - Use
@internal_apiif intentional - Use deprecation - For planned API changes
- Update your PR with the fix
Examples
Example 1: Compatible Change
# ✅ BEFORE (v1.0)
def train_model(config, dataloader):
pass
# ✅ AFTER (v1.1) - Added optional parameter
def train_model(config, dataloader, optimizer="adam"):
pass
Result: ✅ Check passes
Example 2: Breaking Change
# BEFORE (v1.0)
def train_model(config, dataloader, optimizer="adam"):
pass
# ❌ AFTER (v1.1) - Removed parameter
def train_model(config, dataloader):
pass
Result: ❌ Check fails - "Parameter 'optimizer' removed"
Example 3: Exempt Internal API
from megatron.core.utils import internal_api
# BEFORE (v1.0)
@internal_api
def _internal_compute(x, y):
pass
# ✅ AFTER (v1.1) - Can change freely
@internal_api
def _internal_compute(x, y, z): # Added parameter
pass
Result: ✅ Check passes (function is exempt)
Example 4: Deprecation Workflow
from megatron.core.utils import deprecated
# Version 1.0 - Add deprecation
@deprecated(
version="1.0.0",
removal_version="2.0.0",
alternative="train_model_v2"
)
def train_model(config):
"""Old training function - DEPRECATED"""
pass
def train_model_v2(config, **options):
"""New improved training function"""
pass
# Version 1.1 - Keep both (users migrate)
# Version 2.0 - Remove train_model()
Architecture
Developer commits code
↓
GitHub Actions triggers
↓
CI runs check_api_backwards_compatibility.py
↓
Script loads code via griffe:
• Baseline: latest release (e.g., core_r0.8.0)
• Current: PR branch
↓
Apply filtering:
• Skip @internal_api, @experimental_api, and @deprecated
• Skip private functions (_prefix)
• Skip test/experimental paths
↓
Griffe compares signatures:
• Parameters
• Types
• Return types
• Defaults
↓
Report breaking changes
↓
Exit: 0=pass, 1=fail
↓
CI fails if breaking changes detected
Configuration
Customizing Filters
Edit scripts/check_api_backwards_compatibility.py:
# Add more exempt decorators
EXEMPT_DECORATORS = [
"internal_api",
"experimental_api",
"deprecated",
]
# Add more path exclusions
EXCLUDE_PATHS = {
"tests",
"experimental",
"legacy",
"your_custom_path", # ← Add here
}
Changing the Baseline
The workflow auto-detects the latest core_r* tag. To manually specify:
# In .github/workflows/check_api_backwards_compatibility_workflow.yml
- name: Run compatibility check
run: |
python scripts/check_api_backwards_compatibility.py \
--baseline your_custom_baseline
FAQ
Q: Why did my PR fail the compatibility check?
A: Your code introduced breaking changes compared to the last release. Review the CI logs to see what changed.
Q: Can I disable the check for my PR?
A: No, but you can mark specific functions as exempt using @internal_api or @experimental_api.
Q: What if I need to make a breaking change?
A: Use the @deprecated decorator for a gradual transition, or mark the function as exempt using @internal_api (for internal code) or @experimental_api (for experimental features).
Q: Does this check all of Megatron-LM?
A: No, only megatron/core/** (Megatron Core). Legacy code is excluded.
Q: What about class methods?
A: Yes, class methods are checked just like functions.
Q: Can I run this locally before pushing?
A: Yes! Run python scripts/check_api_backwards_compatibility.py --baseline core_r0.8.0
Q: What if there's no release tag yet?
A: The workflow will use main as the baseline. Update it once you have release tags.
Troubleshooting
Error: "griffe is not installed"
pip install griffe
Error: "No core_r* tags found"
The repository doesn't have release tags yet. The workflow will fall back to main.
False Positives
If the checker reports a breaking change that isn't actually breaking, file an issue and use @internal_api as a temporary workaround.
References
- Script:
scripts/check_api_backwards_compatibility.py - Workflow:
.github/workflows/check_api_backwards_compatibility_workflow.yml - Decorators:
megatron/core/backwards_compatibility_decorators.py - Griffe Documentation: https://mkdocstrings.github.io/griffe/
Support
For questions or issues:
- Check this documentation
- Review existing PRs with compatibility checks
- Ask in the Megatron-LM Slack/Discord
- File an issue on GitHub