* 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
* Fix typos, upgrade yarn packages, add some improvements
* Fix joblib 1.4.0 breaks joblib-spark
* Fix xgboost test error
* Pin xgboost<2.0.0
* Try update prophet to 1.5.1
* Update github workflow
* Revert prophet version
* Update github workflow
* Update install libomp
* Fix test errors
* Fix test errors
* Add retry to test and coverage
* Revert "Add retry to test and coverage"
This reverts commit ce13097cd5.
* Increase test budget
* Add more data to test_models, try fixing ValueError: Found array with 0 sample(s) (shape=(0, 252)) while a minimum of 1 is required.
* notebook test
* add ipykernel, remove except
* only create dir if not empty
* Stop sequential tuning when result is None
* fix reproducibility of global search
* save gs seed
* use get to avoid KeyError
* test
* categorical choice can be ordered or unordered
* ordered -> order
* move choice into utils
* version comparison
* packaging -> setuptools
* import version
* version_parse
* test order for choice
* support latest xgboost version
* Update test_classification.py
* Update
Exists problems when installing xgb1.6.1 in py3.6
* cleanup
* xgboost version
* remove time_budget_s in test
* remove redundancy
* stop support of python 3.6
Co-authored-by: zsk <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* add bs restore test
* use default metric when not provided
* update documentation
* remove print
* period
* remove bs restore test
* Update website/docs/Use-Cases/Task-Oriented-AutoML.md
* handle non-flaml scheduler in flaml.tune
* revise time budget
* Update website/docs/Use-Cases/Tune-User-Defined-Function.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update website/docs/Use-Cases/Tune-User-Defined-Function.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/tune/tune.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* add docstr
* remove random seed
* StopIteration
* StopIteration format
* format
* Update flaml/tune/tune.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* revise docstr
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
