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[python-package] fix mypy errors in sklearn.py #4837

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merged 4 commits into from
Dec 2, 2021
Merged

[python-package] fix mypy errors in sklearn.py #4837

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49aede2
[python-package] fix mypy errors in sklearn.py
jameslamb Nov 30, 2021
acf9495
Merge branch 'master' into mypy-sklearn
jameslamb Dec 1, 2021
6e34201
use ignore comments
jameslamb Dec 1, 2021
ffcbbbf
Merge branch 'master' into mypy-sklearn
jameslamb Dec 2, 2021
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18 changes: 9 additions & 9 deletions python-package/lightgbm/sklearn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,11 +2,11 @@
"""Scikit-learn wrapper interface for LightGBM."""
import copy
from inspect import signature
from typing import Callable, Dict, List, Optional, Tuple, Union
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import numpy as np

from .basic import Dataset, LightGBMError, _ArrayLike, _choose_param_value, _ConfigAliases, _log_warning
from .basic import Booster, Dataset, LightGBMError, _ArrayLike, _choose_param_value, _ConfigAliases, _log_warning
from .callback import log_evaluation, record_evaluation
from .compat import (SKLEARN_INSTALLED, LGBMNotFittedError, _LGBMAssertAllFinite, _LGBMCheckArray,
_LGBMCheckClassificationTargets, _LGBMCheckSampleWeight, _LGBMCheckXY, _LGBMClassifierBase,
Expand Down Expand Up @@ -514,11 +514,11 @@ def __init__(
self.random_state = random_state
self.n_jobs = n_jobs
self.importance_type = importance_type
self._Booster = None
self._Booster: Optional[Booster] = None
self._evals_result = None
self._best_score = None
self._best_iteration = None
self._other_params = {}
self._other_params: Dict[str, Any] = {}
self._objective = objective
self.class_weight = class_weight
self._class_weight = None
Expand Down Expand Up @@ -855,7 +855,7 @@ def n_estimators_(self) -> int:
"""
if not self.__sklearn_is_fitted__():
raise LGBMNotFittedError('No n_estimators found. Need to call fit beforehand.')
return self._Booster.current_iteration()
return self._Booster.current_iteration() # type: ignore

@property
def n_iter_(self) -> int:
Expand All @@ -866,7 +866,7 @@ def n_iter_(self) -> int:
"""
if not self.__sklearn_is_fitted__():
raise LGBMNotFittedError('No n_iter found. Need to call fit beforehand.')
return self._Booster.current_iteration()
return self._Booster.current_iteration() # type: ignore

@property
def booster_(self):
Expand Down Expand Up @@ -920,7 +920,7 @@ def fit(self, X, y,
categorical_feature=categorical_feature, callbacks=callbacks, init_model=init_model)
return self

_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMRegressor")
_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMRegressor") # type: ignore
_base_doc = (_base_doc[:_base_doc.find('group :')] # type: ignore
+ _base_doc[_base_doc.find('eval_set :'):]) # type: ignore
_base_doc = (_base_doc[:_base_doc.find('eval_class_weight :')]
Expand Down Expand Up @@ -987,7 +987,7 @@ def fit(self, X, y,
callbacks=callbacks, init_model=init_model)
return self

_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMClassifier")
_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMClassifier") # type: ignore
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warnings about .__doc__ being Optional[str] could be avoided by changing this to something like getattr(LGBMModel.fit, "__doc__", ""), but I think this is preferable, so that .replace() raises an exception in CI if something is accidentally changed that results in the docs being empty for a method.

_base_doc = (_base_doc[:_base_doc.find('group :')] # type: ignore
+ _base_doc[_base_doc.find('eval_set :'):]) # type: ignore
fit.__doc__ = (_base_doc[:_base_doc.find('eval_group :')]
Expand Down Expand Up @@ -1086,7 +1086,7 @@ def fit(self, X, y,
categorical_feature=categorical_feature, callbacks=callbacks, init_model=init_model)
return self

_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMRanker")
_base_doc = LGBMModel.fit.__doc__.replace("self : LGBMModel", "self : LGBMRanker") # type: ignore
fit.__doc__ = (_base_doc[:_base_doc.find('eval_class_weight :')] # type: ignore
+ _base_doc[_base_doc.find('eval_init_score :'):]) # type: ignore
_base_doc = fit.__doc__
Expand Down