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Correct deprecate positional args decorator for CalVer #3784

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merged 2 commits into from
Jun 1, 2021
Merged

Correct deprecate positional args decorator for CalVer #3784

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8b3484c
Switch version to 21.06
lowener Apr 22, 2021
58c1c1d
Merge branch 'branch-21.06' into 020-switch-21.06
lowener May 29, 2021
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34 changes: 17 additions & 17 deletions python/cuml/_thirdparty/sklearn/preprocessing/_data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def _handle_zeros_in_scale(scale, copy=True):
return scale


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def scale(X, *, axis=0, with_mean=True, with_std=True, copy=True):
"""Standardize a dataset along any axis
Expand Down Expand Up @@ -289,7 +289,7 @@ class MinMaxScaler(TransformerMixin,
data_max_ = CumlArrayDescriptor()
data_range_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, feature_range=(0, 1), *, copy=True):
self.feature_range = feature_range
self.copy = copy
Expand Down Expand Up @@ -434,7 +434,7 @@ def inverse_transform(self, X) -> CumlArray:
return X


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def minmax_scale(X, feature_range=(0, 1), *, axis=0, copy=True):
"""Transform features by scaling each feature to a given range.
Expand Down Expand Up @@ -613,7 +613,7 @@ class StandardScaler(TransformerMixin,
mean_ = CumlArrayDescriptor()
var_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, copy=True, with_mean=True, with_std=True):
self.with_mean = with_mean
self.with_std = with_std
Expand Down Expand Up @@ -918,7 +918,7 @@ class MaxAbsScaler(TransformerMixin,
n_samples_seen_ = CumlArrayDescriptor()
max_abs_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, copy=True):
self.copy = copy

Expand Down Expand Up @@ -1040,7 +1040,7 @@ def inverse_transform(self, X) -> SparseCumlArray:
return X


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def maxabs_scale(X, *, axis=0, copy=True):
"""Scale each feature to the [-1, 1] range without breaking the sparsity.
Expand Down Expand Up @@ -1175,7 +1175,7 @@ class RobustScaler(TransformerMixin,
center_ = CumlArrayDescriptor()
scale_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, with_centering=True, with_scaling=True,
quantile_range=(25.0, 75.0), copy=True):
self.with_centering = with_centering
Expand Down Expand Up @@ -1301,7 +1301,7 @@ def inverse_transform(self, X) -> SparseCumlArray:
return X


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def robust_scale(X, *, axis=0, with_centering=True, with_scaling=True,
quantile_range=(25.0, 75.0), copy=True):
Expand Down Expand Up @@ -1448,7 +1448,7 @@ class PolynomialFeatures(TransformerMixin,
exponentially in the degree. High degrees can cause overfitting.
"""

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, degree=2, *, interaction_only=False, include_bias=True,
order='C'):
self.degree = degree
Expand Down Expand Up @@ -1662,7 +1662,7 @@ def transform(self, X) -> SparseCumlArray:
return XP # TODO keep order


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def normalize(X, norm='l2', *, axis=1, copy=True, return_norm=False):
"""Scale input vectors individually to unit norm (vector length).
Expand Down Expand Up @@ -1808,7 +1808,7 @@ class Normalizer(TransformerMixin,
normalize: Equivalent function without the estimator API.
"""

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, norm='l2', *, copy=True):
self.norm = norm
self.copy = copy
Expand Down Expand Up @@ -1842,7 +1842,7 @@ def transform(self, X, copy=None) -> SparseCumlArray:
return normalize(X, norm=self.norm, axis=1, copy=copy)


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
@api_return_generic(get_output_type=True)
def binarize(X, *, threshold=0.0, copy=True):
"""Boolean thresholding of array-like or sparse matrix
Expand Down Expand Up @@ -1937,7 +1937,7 @@ class Binarizer(TransformerMixin,
binarize: Equivalent function without the estimator API.
"""

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, threshold=0.0, copy=True):
self.threshold = threshold
self.copy = copy
Expand Down Expand Up @@ -2235,7 +2235,7 @@ class QuantileTransformer(TransformerMixin,
<sphx_glr_auto_examples_preprocessing_plot_all_scaling.py>`.
"""

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, n_quantiles=1000, output_distribution='uniform',
ignore_implicit_zeros=False, subsample=int(1e5),
random_state=None, copy=True):
Expand Down Expand Up @@ -2565,7 +2565,7 @@ def inverse_transform(self, X):
return self._transform(X, inverse=True)


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def quantile_transform(X, *, axis=0, n_quantiles=1000,
output_distribution='uniform',
ignore_implicit_zeros=False,
Expand Down Expand Up @@ -2767,7 +2767,7 @@ class PowerTransformer(TransformerMixin,
of the Royal Statistical Society B, 26, 211-252 (1964).

"""
@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, method='yeo-johnson', *, standardize=True, copy=True):
self.method = method
self.standardize = standardize
Expand Down Expand Up @@ -3035,7 +3035,7 @@ def _check_input(self, X, in_fit, check_positive=False, check_shape=False,
return X


@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def power_transform(X, method='yeo-johnson', *, standardize=True, copy=True):
"""
Power transforms are a family of parametric, monotonic transformations
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/_thirdparty/sklearn/preprocessing/_discretization.py
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Expand Up @@ -135,7 +135,7 @@ class KBinsDiscretizer(TransformerMixin,
bin_edges_ = CumlArrayDescriptor()
n_bins_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, n_bins=5, *, encode='onehot', strategy='quantile'):
self.n_bins = n_bins
self.encode = encode
Expand Down
4 changes: 2 additions & 2 deletions python/cuml/_thirdparty/sklearn/preprocessing/_imputation.py
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Expand Up @@ -230,7 +230,7 @@ class SimpleImputer(_BaseImputer, BaseEstimator,

statistics_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, missing_values=np.nan, strategy="mean",
fill_value=None, copy=True, add_indicator=False):
super().__init__(
Expand Down Expand Up @@ -534,7 +534,7 @@ class MissingIndicator(TransformerMixin,
"""
features_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, *, missing_values=np.nan, features="missing-only",
sparse="auto", error_on_new=True):
self.missing_values = missing_values
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/ensemble/randomforest_common.pyx
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Expand Up @@ -93,7 +93,7 @@ class BaseRandomForestModel(Base):
"random_state is set")
if quantile_per_tree:
warnings.warn("The 'quantile_per_tree' parameter is deprecated "
"and will be removed in 0.20 release. Instead use "
"and will be removed in 21.06 release. Instead use "
"higher number of global quantile bins.")
if handle is None:
handle = Handle(n_streams)
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/internals/base_helpers.py
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Expand Up @@ -172,7 +172,7 @@ def __new__(cls, classname, bases, classDict):
# If attributeName is `__init__`, wrap in the decorator to
# deprecate positional args
if (attributeName == "__init__"):
attribute = _check_and_wrap_init(attribute, version="0.20")
attribute = _check_and_wrap_init(attribute, version="21.06")
classDict[attributeName] = attribute

# For now, skip all additional processing if we are a dask
Expand Down
6 changes: 3 additions & 3 deletions python/cuml/multiclass/multiclass.py
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Expand Up @@ -83,7 +83,7 @@ class MulticlassClassifier(Base, ClassifierMixin):
Number of classes.

"""
@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self,
estimator,
*,
Expand Down Expand Up @@ -208,7 +208,7 @@ class OneVsRestClassifier(MulticlassClassifier):
module level, `cuml.global_settings.output_type`.
See :ref:`output-data-type-configuration` for more info.
"""
@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self,
estimator,
*args,
Expand Down Expand Up @@ -274,7 +274,7 @@ class OneVsOneClassifier(MulticlassClassifier):
module level, `cuml.global_settings.output_type`.
See :ref:`output-data-type-configuration` for more info.
"""
@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self,
estimator,
*args,
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/tsa/arima.pyx
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Expand Up @@ -274,7 +274,7 @@ class ARIMA(Base):
sma_ = CumlArrayDescriptor()
sigma2_ = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self,
endog,
*,
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/tsa/auto_arima.pyx
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Expand Up @@ -175,7 +175,7 @@ class AutoARIMA(Base):

d_y = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self,
endog,
*,
Expand Down
2 changes: 1 addition & 1 deletion python/cuml/tsa/holtwinters.pyx
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Expand Up @@ -183,7 +183,7 @@ class ExponentialSmoothing(Base):
season = CumlArrayDescriptor()
SSE = CumlArrayDescriptor()

@_deprecate_pos_args(version="0.20")
@_deprecate_pos_args(version="21.06")
def __init__(self, endog, *, seasonal="additive",
seasonal_periods=2, start_periods=2,
ts_num=1, eps=2.24e-3, handle=None,
Expand Down