autogen/flaml/automl/__init__.py

from flaml.automl.automl import AutoML, size
from flaml.automl.logger import logger_formatter
from flaml.automl.state import SearchState, AutoMLState

__all__ = ["AutoML", "AutoMLState", "SearchState", "logger_formatter", "size"]
Extract task class from automl (#857) * 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 * WIP * WIP - Notes below Got to the point where the methods from AutoML are pulled to GenericTask. Started removing private markers and removing the passing of automl to these methods. Done with decide_split_type, started on prepare_data. Need to do the others after * Re-add generic_task * Fix tests: add Task.__str__ * Fix tests: test for ray.ObjectRef * Hotwire TS_Sklearn wrapper to fix test fail * Remove unused data size field from Task * Fix import for CLASSIFICATION in notebook * Update flaml/automl/data.py Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Fix review comments * Fix task -> str in custom learner constructor * Remove unused CLASSIFICATION imports * Hotwire TS_Sklearn wrapper to fix test fail by setting optimizer_for_horizon == False * Revert changes to the automl_classification and pin FLAML version * Fix imports in reverted notebook * Fix FLAML version in automl notebooks * Fix ml.py line endings * Fix CLASSIFICATION task import in automl_classification notebook * Uncomment pip install in notebook and revert import Not convinced this will work because of installing an older version of the package into the environment in which we're running the tests, but let's see. * Revert c6a5dd1a0 * Revert "Revert c6a5dd1a0" This reverts commit e55e35adea03993de87b23f092b14c6af623d487. * Black format model.py * Bump version to 1.1.2 in automl_xgboost * Add docstrings to the Task ABC * Fix import in custom_learner * fix 'optimize_for_horizon' for ts_sklearn * remove debugging print statements * Check for is_forecast() before is_classification() in decide_split_type * Attempt to fix formatting fail * Another attempt to fix formatting fail * And another attempt to fix formatting fail * Add type annotations for task arg in signatures and docstrings * Fix formatting * Fix linting --------- Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu> Co-authored-by: EgorKraevTransferwise <egor.kraev@transferwise.com> Co-authored-by: Chi Wang <wang.chi@microsoft.com> Co-authored-by: Kevin Chen <chenkevin.8787@gmail.com> 2023-03-11 02:39:08 +00:00			`from flaml.automl.automl import AutoML, size`
			`from flaml.automl.logger import logger_formatter`
			`from flaml.automl.state import SearchState, AutoMLState`
Refactor into automl subpackage (#809) * 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> 2022-12-06 20:46:08 +00:00
			`__all__ = ["AutoML", "AutoMLState", "SearchState", "logger_formatter", "size"]`