зеркало из https://github.com/microsoft/LightGBM.git
[python] rename `print_evaluation()` into `log_evaluation()` (#4604)
* Update __init__.py * Update Python-API.rst * Update engine.py * Update test_utilities.py * Update sklearn.py * Update callback.py * Update callback.py * Update callback.py
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@ -53,7 +53,7 @@ Callbacks
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:toctree: pythonapi/
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early_stopping
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print_evaluation
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log_evaluation
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record_evaluation
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reset_parameter
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@ -6,7 +6,7 @@ Contributors: https://github.com/microsoft/LightGBM/graphs/contributors.
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from pathlib import Path
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from .basic import Booster, Dataset, Sequence, register_logger
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from .callback import early_stopping, print_evaluation, record_evaluation, reset_parameter
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from .callback import early_stopping, log_evaluation, print_evaluation, record_evaluation, reset_parameter
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from .engine import CVBooster, cv, train
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try:
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@ -32,5 +32,5 @@ __all__ = ['Dataset', 'Booster', 'CVBooster', 'Sequence',
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'train', 'cv',
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'LGBMModel', 'LGBMRegressor', 'LGBMClassifier', 'LGBMRanker',
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'DaskLGBMRegressor', 'DaskLGBMClassifier', 'DaskLGBMRanker',
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'print_evaluation', 'record_evaluation', 'reset_parameter', 'early_stopping',
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'log_evaluation', 'print_evaluation', 'record_evaluation', 'reset_parameter', 'early_stopping',
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'plot_importance', 'plot_split_value_histogram', 'plot_metric', 'plot_tree', 'create_tree_digraph']
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@ -52,6 +52,16 @@ def _format_eval_result(value: list, show_stdv: bool = True) -> str:
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def print_evaluation(period: int = 1, show_stdv: bool = True) -> Callable:
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"""Create a callback that logs the evaluation results.
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Deprecated, use ``log_evaluation()`` instead.
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"""
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_log_warning("'print_evaluation()' callback is deprecated and will be removed in a future release of LightGBM. "
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"Use 'log_evaluation()' callback instead.")
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return log_evaluation(period=period, show_stdv=show_stdv)
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def log_evaluation(period: int = 1, show_stdv: bool = True) -> Callable:
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"""Create a callback that logs the evaluation results.
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By default, standard output resource is used.
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Use ``register_logger()`` function to register a custom logger.
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@ -238,16 +238,16 @@ def train(
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# Most of legacy advanced options becomes callbacks
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if verbose_eval != "warn":
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_log_warning("'verbose_eval' argument is deprecated and will be removed in a future release of LightGBM. "
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"Pass 'print_evaluation()' callback via 'callbacks' argument instead.")
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"Pass 'log_evaluation()' callback via 'callbacks' argument instead.")
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else:
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if callbacks: # assume user has already specified print_evaluation callback
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if callbacks: # assume user has already specified log_evaluation callback
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verbose_eval = False
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else:
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verbose_eval = True
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if verbose_eval is True:
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callbacks.add(callback.print_evaluation())
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callbacks.add(callback.log_evaluation())
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elif isinstance(verbose_eval, int):
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callbacks.add(callback.print_evaluation(verbose_eval))
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callbacks.add(callback.log_evaluation(verbose_eval))
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if early_stopping_rounds is not None and early_stopping_rounds > 0:
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callbacks.add(callback.early_stopping(early_stopping_rounds, first_metric_only, verbose=bool(verbose_eval)))
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@ -619,11 +619,11 @@ def cv(params, train_set, num_boost_round=100,
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callbacks.add(callback.early_stopping(early_stopping_rounds, first_metric_only, verbose=False))
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if verbose_eval is not None:
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_log_warning("'verbose_eval' argument is deprecated and will be removed in a future release of LightGBM. "
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"Pass 'print_evaluation()' callback via 'callbacks' argument instead.")
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"Pass 'log_evaluation()' callback via 'callbacks' argument instead.")
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if verbose_eval is True:
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callbacks.add(callback.print_evaluation(show_stdv=show_stdv))
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callbacks.add(callback.log_evaluation(show_stdv=show_stdv))
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elif isinstance(verbose_eval, int):
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callbacks.add(callback.print_evaluation(verbose_eval, show_stdv=show_stdv))
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callbacks.add(callback.log_evaluation(verbose_eval, show_stdv=show_stdv))
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callbacks_before_iter = {cb for cb in callbacks if getattr(cb, 'before_iteration', False)}
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callbacks_after_iter = callbacks - callbacks_before_iter
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@ -7,7 +7,7 @@ from typing import Callable, Dict, Optional, Union
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import numpy as np
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from .basic import Dataset, LightGBMError, _choose_param_value, _ConfigAliases, _log_warning
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from .callback import print_evaluation, record_evaluation
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from .callback import log_evaluation, record_evaluation
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from .compat import (SKLEARN_INSTALLED, LGBMNotFittedError, _LGBMAssertAllFinite, _LGBMCheckArray,
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_LGBMCheckClassificationTargets, _LGBMCheckSampleWeight, _LGBMCheckXY, _LGBMClassifierBase,
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_LGBMComputeSampleWeight, _LGBMLabelEncoder, _LGBMModelBase, _LGBMRegressorBase, dt_DataTable,
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@ -731,13 +731,13 @@ class LGBMModel(_LGBMModelBase):
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if verbose != 'warn':
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_log_warning("'verbose' argument is deprecated and will be removed in a future release of LightGBM. "
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"Pass 'print_evaluation()' callback via 'callbacks' argument instead.")
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"Pass 'log_evaluation()' callback via 'callbacks' argument instead.")
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else:
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if callbacks: # assume user has already specified print_evaluation callback
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if callbacks: # assume user has already specified log_evaluation callback
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verbose = False
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else:
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verbose = True
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callbacks.append(print_evaluation(int(verbose)))
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callbacks.append(log_evaluation(int(verbose)))
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evals_result = {}
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callbacks.append(record_evaluation(evals_result))
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@ -33,7 +33,7 @@ def test_register_logger(tmp_path):
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eval_records = {}
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callbacks = [
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lgb.record_evaluation(eval_records),
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lgb.print_evaluation(2),
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lgb.log_evaluation(2),
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lgb.early_stopping(4)
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]
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lgb.train({'objective': 'binary', 'metric': ['auc', 'binary_error']},
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