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[dask] passed through verbose for dask fit (#5413)

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Jan Borchmann 2020-03-13 18:33:53 -04:00 committed by GitHub
parent 45a97ddf32
commit bb8c8df39d
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1 changed files with 12 additions and 6 deletions
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18
python-package/xgboost/dask.py
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@ -540,7 +540,8 @@ class DaskScikitLearnBase(XGBModel):
y, y,
sample_weights=None, sample_weights=None,
eval_set=None, eval_set=None,
sample_weight_eval_set=None): sample_weight_eval_set=None,
verbose=True):
'''Fit the regressor. '''Fit the regressor.
Parameters Parameters
@ -557,7 +558,10 @@ class DaskScikitLearnBase(XGBModel):
Validation metrics will help us track the performance of the model. Validation metrics will help us track the performance of the model.
sample_weight_eval_set : list, optional sample_weight_eval_set : list, optional
A list of the form [L_1, L_2, ..., L_n], where each L_i is a list A list of the form [L_1, L_2, ..., L_n], where each L_i is a list
of group weights on the i-th validation set.''' of group weights on the i-th validation set.
verbose : bool
If `verbose` and an evaluation set is used, writes the evaluation
metric measured on the validation set to stderr.'''
raise NotImplementedError raise NotImplementedError
def predict(self, data): # pylint: disable=arguments-differ def predict(self, data): # pylint: disable=arguments-differ
@ -589,7 +593,8 @@ class DaskXGBRegressor(DaskScikitLearnBase):
y, y,
sample_weights=None, sample_weights=None,
eval_set=None, eval_set=None,
sample_weight_eval_set=None): sample_weight_eval_set=None,
verbose=True):
_assert_dask_support() _assert_dask_support()
dtrain = DaskDMatrix(client=self.client, dtrain = DaskDMatrix(client=self.client,
data=X, label=y, weight=sample_weights) data=X, label=y, weight=sample_weights)
@ -599,7 +604,7 @@ class DaskXGBRegressor(DaskScikitLearnBase):
results = train(self.client, params, dtrain, results = train(self.client, params, dtrain,
num_boost_round=self.get_num_boosting_rounds(), num_boost_round=self.get_num_boosting_rounds(),
evals=evals) evals=evals, verbose_eval=verbose)
# pylint: disable=attribute-defined-outside-init # pylint: disable=attribute-defined-outside-init
self._Booster = results['booster'] self._Booster = results['booster']
# pylint: disable=attribute-defined-outside-init # pylint: disable=attribute-defined-outside-init
@ -627,7 +632,8 @@ class DaskXGBClassifier(DaskScikitLearnBase, XGBClassifierBase):
y, y,
sample_weights=None, sample_weights=None,
eval_set=None, eval_set=None,
sample_weight_eval_set=None): sample_weight_eval_set=None,
verbose=True):
_assert_dask_support() _assert_dask_support()
dtrain = DaskDMatrix(client=self.client, dtrain = DaskDMatrix(client=self.client,
data=X, label=y, weight=sample_weights) data=X, label=y, weight=sample_weights)
@ -650,7 +656,7 @@ class DaskXGBClassifier(DaskScikitLearnBase, XGBClassifierBase):
eval_set, sample_weight_eval_set) eval_set, sample_weight_eval_set)
results = train(self.client, params, dtrain, results = train(self.client, params, dtrain,
num_boost_round=self.get_num_boosting_rounds(), num_boost_round=self.get_num_boosting_rounds(),
evals=evals) evals=evals, verbose_eval=verbose)
self._Booster = results['booster'] self._Booster = results['booster']
# pylint: disable=attribute-defined-outside-init # pylint: disable=attribute-defined-outside-init
self.evals_result_ = results['history'] self.evals_result_ = results['history']