E56C Add set_param check and test · scikit-learn/scikit-learn@7a7743a · GitHub
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Add set_param check and test
Add check_set_params to test_common
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‎sklearn/utils/estimator_checks.py‎

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Original file line numberDiff line numberDiff line change
@@ -225,6 +225,7 @@ def _yield_all_checks(name, estimator):
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yield check_fit1d_1feature
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yield check_fit1d_1sample
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yield check_get_params_invariance
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yield check_set_params
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yield check_dict_unchanged
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yield check_dont_overwrite_parameters
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@@ -1704,6 +1705,47 @@ def transform(self, X):
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shallow_params.items()))
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@ignore_warnings(category=DeprecationWarning)
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def check_set_params(name, estimator_orig):
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if name in META_ESTIMATORS:
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return
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estimator = clone(estimator_orig)
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# Trivial check to make sure set_params is working
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params = estimator.get_params()
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estimator.set_params(**params)
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# Check that get_params() returns the same thing
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# before and after set_params() with some fuzz
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# values
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estimator = clone(estimator_orig)
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test_values = [-np.inf, np.inf, None,
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-100, 100, -0.5, 0.5, 0,
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"", "value",
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('a', 'b'), {'key': 'value'}]
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for param_name in params.keys():
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for value in test_values:
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try:
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estimator.set_params(**{param_name: value})
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get_value = estimator.get_params()[param_name]
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except:
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# triggered some parameter validation
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# continue checking other test values
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pass
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else:
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errmsg = ("get_params does not match set_params: "
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"called set_params of {0} with {1}={2} "
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"but get_params returns {1}={3}")
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errmsg = errmsg.format(name, param_name, value,
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get_value)
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assert_equal(value, get_value, errmsg)
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estimator = clone(estimator_orig)
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@ignore_warnings(category=DeprecationWarning)
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def check_classifiers_regression_target(name, estimator_orig):
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# Check if classifier throws an exception when fed regression targets

‎sklearn/utils/tests/test_estimator_checks.py‎

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Original file line numberDiff line numberDiff line change
@@ -71,6 +71,39 @@ def fit(self, X, y=None):
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return self
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class NoSetter(BaseEstimator):
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def __init__(self, p=0):
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self._p = p
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@property
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def p(self):
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return self._p
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def fit(self, X, y=None):
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X, y = check_X_y(X, y)
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return self
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class BadGetter(BaseEstimator):
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def __init__(self, p=0):
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self._p = p
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@property
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def p(self):
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if self._p < 0:
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return 0
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else:
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return self._p
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@p.setter
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def p(self, value):
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self._p = value
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def fit(self, X, y=None):
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X, y = check_X_y(X, y)
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return self
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class NoCheckinPredict(BaseBadClassifier):
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def fit(self, X, y):
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X, y = check_X_y(X, y)
@@ -129,6 +162,11 @@ def test_check_estimator():
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msg = "it does not implement a 'get_params' methods"
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assert_raises_regex(TypeError, msg, check_estimator, object)
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assert_raises_regex(TypeError, msg, check_estimator, object())
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# check that properties can be set
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msg = "can't set attribute"
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assert_raises_regex(AttributeError, msg, check_estimator, NoSetter)
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msg = "get_params does not match set_params"
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assert_raises_regex(AssertionError, msg, check_estimator, BadGetter())
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# check that we have a fit method
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msg = "object has no attribute 'fit'"
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assert_raises_regex(AttributeError, msg, check_estimator, BaseEstimator)

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