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Commit 5a89f4d

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alegonzalegonz
committed
Refactored get_params and set_params into a GetSetParamsMixin and
changed BaseEstimator and gaussian_process.kernels.Kernel to inherit from it. Also added InvalidParameterError to pass the parameter name and print the proper error message in set_params depending on the class.
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‎sklearn/base.py

Copy file name to clipboardExpand all lines: sklearn/base.py
+65-31Lines changed: 65 additions & 31 deletions
Original file line numberDiff line numberDiff line change
@@ -13,7 +13,7 @@
1313
import numpy as np
1414

1515
from . import __version__
16-
from .exceptions import SignatureError
16+
from .exceptions import InvalidParameterError, SignatureError
1717
from .utils import _IS_32BIT, get_param_names_from_constructor
1818

1919
_DEFAULT_TAGS = {
@@ -141,18 +141,9 @@ def _update_if_consistent(dict1, dict2):
141141
return dict1
142142

143143

144-
class BaseEstimator:
145-
"""Base class for all estimators in scikit-learn
146-
147-
Notes
148-
-----
149-
All estimators should specify all the parameters that can be set
150-
at the class level in their ``__init__`` as explicit keyword
151-
arguments (no ``*args`` or ``**kwargs``).
152-
"""
153-
144+
class GetSetParamsMixin:
154145
def _get_params_from(self, param_names, deep=True):
155-
"""Get parameters for this estimator from the given names"""
146+
"""Get parameters for this object from the given names"""
156147
out = dict()
157148
for key in param_names:
158149
value = getattr(self, key, None)
@@ -163,35 +154,26 @@ def _get_params_from(self, param_names, deep=True):
163154
return out
164155

165156
def get_params(self, deep=True):
166-
"""Get parameters for this estimator.
157+
"""Get parameters for this object.
167158
168159
Parameters
169160
----------
170161
deep : boolean, optional
171-
If True, will return the parameters for this estimator and
172-
contained subobjects that are estimators.
162+
If True, will return the parameters for this object and
163+
contained subobjects that implement ``get_params``.
173164
174165
Returns
175166
-------
176167
params : mapping of string to any
177168
Parameter names mapped to their values.
178169
"""
179-
try:
180-
param_names = get_param_names_from_constructor(self.__class__)
181-
except SignatureError as e:
182-
raise SignatureError("scikit-learn estimators should always "
183-
"specify their parameters in the signature"
184-
" of their __init__ (no varargs)."
185-
" %s with constructor %s doesn't "
186-
" follow this convention."
187-
% (self.__class__, e.signature))
188-
170+
param_names = get_param_names_from_constructor(self.__class__)
189171
return self._get_params_from(param_names, deep=deep)
190172

191173
def set_params(self, **params):
192-
"""Set the parameters of this estimator.
174+
"""Set the parameters of this object.
193175
194-
The method works on simple estimators as well as on nested objects
176+
The method works on simple objects as well as on nested objects
195177
(such as pipelines). The latter have parameters of the form
196178
``<component>__<parameter>`` so that it's possible to update each
197179
component of a nested object.
@@ -209,10 +191,7 @@ def set_params(self, **params):
209191
for key, value in params.items():
210192
key, delim, sub_key = key.partition('__')
211193
if key not in valid_params:
212-
raise ValueError('Invalid parameter %s for estimator %s. '
213-
'Check the list of available parameters '
214-
'with `estimator.get_params().keys()`.' %
215-
(key, self))
194+
raise InvalidParameterError(key)
216195

217196
if delim:
218197
nested_params[key][sub_key] = value
@@ -225,6 +204,61 @@ def set_params(self, **params):
225204

226205
return self
227206

207+
208+
class BaseEstimator(GetSetParamsMixin):
209+
"""Base class for all estimators in scikit-learn
210+
211+
Notes
212+
-----
213+
All estimators should specify all the parameters that can be set
214+
at the class level in their ``__init__`` as explicit keyword
215+
arguments (no ``*args`` or ``**kwargs``).
216+
"""
217+
218+
def get_params(self, deep=True):
219+
"""Get parameters for this estimator.
220+
221+
Parameters
222+
----------
223+
deep : boolean, optional
224+
If True, will return the parameters for this estimator and
225+
contained subobjects that are estimators.
226+
227+
Returns
228+
-------
229+
params : mapping of string to any
230+
Parameter names mapped to their values.
231+
"""
232+
try:
233+
return super().get_params(deep=deep)
234+
except SignatureError as e:
235+
raise SignatureError("scikit-learn estimators should always "
236+
"specify their parameters in the signature"
237+
" of their __init__ (no varargs)."
238+
" %s with constructor %s doesn't "
239+
" follow this convention."
240+
% (self.__class__, e.signature))
241+
242+
def set_params(self, **params):
243+
"""Set the parameters of this estimator.
244+
245+
The method works on simple estimators as well as on nested objects
246+
(such as pipelines). The latter have parameters of the form
247+
``<component>__<parameter>`` so that it's possible to update each
248+
component of a nested object.
249+
250+
Returns
251+
-------
252+
self
253+
"""
254+
try:
255+
return super().set_params(**params)
256+
except InvalidParameterError as e:
257+
raise InvalidParameterError('Invalid parameter %s for estimator %s. '
258+
'Check the list of available parameters '
259+
'with `estimator.get_params().keys()`.' %
260+
(e.param_name, self))
261+
228262
def __repr__(self, N_CHAR_MAX=700):
229263
# N_CHAR_MAX is the (approximate) maximum number of non-blank
230264
# characters to render. We pass it as an optional parameter to ease

‎sklearn/exceptions.py

Copy file name to clipboardExpand all lines: sklearn/exceptions.py
+9Lines changed: 9 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -4,6 +4,7 @@
44
"""
55

66
__all__ = ['NotFittedError',
7+
'InvalidParameterError',
78
'SignatureError',
89
'ChangedBehaviorWarning',
910
'ConvergenceWarning',
@@ -38,6 +39,14 @@ class NotFittedError(ValueError, AttributeError):
3839
"""
3940

4041

42+
class InvalidParameterError(ValueError):
43+
""" TODO
44+
"""
45+
46+
def __init__(self, param_name):
47+
self.param_name = param_name
48+
49+
4150
class SignatureError(RuntimeError):
4251
""" TODO
4352
"""

‎sklearn/gaussian_process/kernels.py

Copy file name to clipboardExpand all lines: sklearn/gaussian_process/kernels.py
+13-40Lines changed: 13 additions & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -27,10 +27,9 @@
2727
from scipy.special import kv, gamma
2828
from scipy.spatial.distance import pdist, cdist, squareform
2929

30-
from ..base import clone
31-
from ..exceptions import SignatureError
30+
from ..base import clone, GetSetParamsMixin
31+
from ..exceptions import InvalidParameterError, SignatureError
3232
from ..metrics.pairwise import pairwise_kernels
33-
from ..utils import get_param_names_from_constructor
3433

3534

3635
def _check_length_scale(X, length_scale):
@@ -116,7 +115,7 @@ def __eq__(self, other):
116115
self.fixed == other.fixed)
117116

118117

119-
class Kernel(metaclass=ABCMeta):
118+
class Kernel(GetSetParamsMixin, metaclass=ABCMeta):
120119
"""Base class for all kernels.
121120
122121
.. versionadded:: 0.18
@@ -127,31 +126,23 @@ def get_params(self, deep=True):
127126
128127
Parameters
129128
----------
130-
deep : boolean, optional
131-
If True, will return the parameters for this estimator and
132-
contained subobjects that are estimators.
129+
deep : Ignored
133130
134131
Returns
135132
-------
136133
params : mapping of string to any
137134
Parameter names mapped to their values.
138135
"""
139-
params = dict()
140-
141-
# introspect the constructor arguments to find the model parameters
142-
# to represent
143136
try:
144-
param_names = get_param_names_from_constructor(self.__class__)
137+
# for Kernels, get_params is always shallow
138+
return super().get_params(deep=False)
145139
except SignatureError as e:
146140
raise SignatureError("scikit-learn kernels should always "
147141
"specify their parameters in the signature"
148142
" of their __init__ (no varargs)."
149143
" %s with constructor %s doesn't "
150144
" follow this convention."
151145
% (self.__class__, e.signature))
152-
for key in param_names:
153-
params[key] = getattr(self, key, None)
154-
return params
155146

156147
def set_params(self, **params):
157148
"""Set the parameters of this kernel.
@@ -164,31 +155,13 @@ def set_params(self, **params):
164155
-------
165156
self
166157
"""
167-
if not params:
168-
# Simple optimisation to gain speed (inspect is slow)
169-
return self
170-
valid_params = self.get_params(deep=True)
171-
for key, value in params.items():
172-
split = key.split('__', 1)
173-
if len(split) > 1:
174-
# nested objects case
175-
name, sub_name = split
176-
if name not in valid_params:
177-
raise ValueError('Invalid parameter %s for kernel %s. '
178-
'Check the list of available parameters '
179-
'with `kernel.get_params().keys()`.' %
180-
(name, self))
181-
sub_object = valid_params[name]
182-
sub_object.set_params(**{sub_name: value})
183-
else:
184-
# simple objects case
185-
if key not in valid_params:
186-
raise ValueError('Invalid parameter %s for kernel %s. '
187-
'Check the list of available parameters '
188-
'with `kernel.get_params().keys()`.' %
189-
(key, self.__class__.__name__))
190-
setattr(self, key, value)
191-
return self
158+
try:
159+
return super().set_params(**params)
160+
except InvalidParameterError as e:
161+
raise InvalidParameterError('Invalid parameter %s for kernel %s. '
162+
'Check the list of available parameters '
163+
'with `kernel.get_params().keys()`.' %
164+
(e.param_name, self))
192165

193166
def clone_with_theta(self, theta):
194167
"""Returns a clone of self with given hyperparameters theta.

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