* Merged PR 1686010: Bump version to 2.3.5.post2, Distribute source and wheel, Fix license-file, Only log better models
- Fix license-file
- Bump version to 2.3.5.post2
- Distribute source and wheel
- Log better models only
- Add artifact_path to register_automl_pipeline
- Improve logging of _automl_user_configurations
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This pull request fixes the project’s configuration by updating the license metadata for compliance with FLAML OSS 2.3.5.
The changes in `/pyproject.toml` update the project’s license and readme metadata by replacing deprecated keys with the new structured fields.
- `/pyproject.toml`: Replaced `license_file` with `license = { text = "MIT" }`.
- `/pyproject.toml`: Replaced `description-file` with `readme = "README.md"`.
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Related work items: #4252053
* Merged PR 1688479: Handle feature_importances_ is None, Catch RuntimeError and wait for spark cluster to recover
- Add warning message when feature_importances_ is None (#3982120)
- Catch RuntimeError and wait for spark cluster to recover (#3982133)
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Bug fix.
This pull request prevents an AttributeError in the feature importance plotting function by adding a check for a `None` value with an informative warning message.
- `flaml/fabric/visualization.py`: Checks if `result.feature_importances_` is `None`, logs a warning with possible reasons, and returns early.
- `flaml/fabric/visualization.py`: Imports `logger` from `flaml.automl.logger` to support the warning message.
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Related work items: #3982120, #3982133
* Removed deprecated metadata section
* Fix log_params, log_artifact doesn't support run_id in mlflow 2.6.0
* Remove autogen
* Remove autogen
* Remove autogen
* Merged PR 1776547: Fix flaky test test_automl
Don't throw error when time budget is not enough
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#### AI description (iteration 1)
#### PR Classification
Bug fix addressing a failing test in the AutoML notebook example.
#### PR Summary
This PR fixes a flaky test by adding a conditional check in the AutoML test that prints a message and exits early if no best estimator is set, thereby preventing unpredictable test failures.
- `test/automl/test_notebook_example.py`: Introduced a check to print "Training budget is not sufficient" and return if `automl.best_estimator` is not found.
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Related work items: #4573514
* Merged PR 1777952: Fix unrecognized or malformed field 'license-file' when uploading wheel to feed
Try to fix InvalidDistribution: Invalid distribution metadata: unrecognized or malformed field 'license-file'
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Bug fix addressing package metadata configuration.
This pull request fixes the error with unrecognized or malformed license file fields during wheel uploads by updating the setup configuration.
- In `setup.py`, added `license="MIT"` and `license_files=["LICENSE"]` to provide proper license metadata.
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Related work items: #4560034
* Cherry-pick Merged PR 1879296: Add support to python 3.12 and spark 4.0
* Cherry-pick Merged PR 1890869: Improve time_budget estimation for mlflow logging
* Cherry-pick Merged PR 1879296: Add support to python 3.12 and spark 4.0
* Disable openai workflow
* Add python 3.12 to test envs
* Manually trigger openai
* Support markdown files with underscore-prefixed file names
* Improve save dependencies
* SynapseML is not installed
* Fix syntax error:Module !flaml/autogen was never imported
* macos 3.12 also hangs
* fix syntax error
* Update python version in actions
* Install setuptools for using pkg_resources
* Fix test_automl_performance in Github actions
* Fix test_nested_run
* Refactor into automl subpackage
Moved some of the packages into an automl subpackage to tidy before the
task-based refactor. This is in response to discussions with the group
and a comment on the first task-based PR.
Only changes here are moving subpackages and modules into the new
automl, fixing imports to work with this structure and fixing some
dependencies in setup.py.
* Fix doc building post automl subpackage refactor
* Fix broken links in website post automl subpackage refactor
* Fix broken links in website post automl subpackage refactor
* Remove vw from test deps as this is breaking the build
* Move default back to the top-level
I'd moved this to automl as that's where it's used internally, but had
missed that this is actually part of the public interface so makes sense
to live where it was.
* Re-add top level modules with deprecation warnings
flaml.data, flaml.ml and flaml.model are re-added to the top level,
being re-exported from flaml.automl for backwards compatability. Adding
a deprecation warning so that we can have a planned removal later.
* Fix model.py line-endings
* Pin pytorch-lightning to less than 1.8.0
We're seeing strange lightning related bugs from pytorch-forecasting
since the release of lightning 1.8.0. Going to try constraining this to
see if we have a fix.
* Fix the lightning version pin
Was optimistic with setting it in the 1.7.x range, but that isn't
compatible with python 3.6
* Remove lightning version pin
* Revert dependency version changes
* Minor change to retrigger the build
* Fix line endings in ml.py and model.py
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: EgorKraevTransferwise <egor.kraev@transferwise.com>
