[scikit-learn] Fwd: Custom transformer failing check_estimator test
Andreas Mueller
t3kcit at gmail.com
Wed Jul 26 10:54:49 EDT 2017
Hm, it would be nice to do this in a way that relies less on pytest, but
I guess that would be tricky.
One way would be to use assert_raise_message to make clear what the
expected error is.
But that would make the current test more strict - not necessarily that
bad, I guess?
It looks like all asserts in unittest have a "msg" argument... apart
from assertRaises:
https://docs.python.org/2/library/unittest.html#unittest.TestCase.assertRaises
That has been fixed in Python 3.3, though:
https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertRaises
So maybe we should just do a backport for assert_raises and
assert_raises_regex?
On 07/25/2017 07:58 PM, Joel Nothman wrote:
> One advantage of moving to pytest is that we can put messages into
> pytest.raises, and we should emphasise this in moving the
> check_estimator assertions to pytest. But I'm also not sure how we do
> the deprecation of nosetests for check_estimator in a way that is
> friendly to our contribbers...
>
> On 26 July 2017 at 06:31, Andreas Mueller <t3kcit at gmail.com
> <mailto:t3kcit at gmail.com>> wrote:
>
> Indeed, it makes sure that the transform is applied to data with
> the same number of samples as the input.
> PR welcome to provide a better error message on this!
>
> On 07/25/2017 08:15 AM, Sam Barnett wrote:
>> Apologies: I've since worked out what the problem was and have
>> resolved this issue. This was what I was missing in my code:
>>
>>
>> # Check that the input is of the same shape as the one passed
>> # during fit.
>> if X.shape != self.input_shape_:
>> raise ValueError('Shape of input is different from what was seen'
>> 'in `fit`')
>>
>>
>> On Tue, Jul 25, 2017 at 9:41 AM, Sam Barnett
>> <sambarnett95 at gmail.com <mailto:sambarnett95 at gmail.com>> wrote:
>>
>> This is the Traceback I get:
>>
>>
>> AssertionErrorTraceback (most recent call last)
>> <ipython-input-5-166b8f0141db> in <module>()
>> ----> 1 check_estimator(OK.Sqizer)
>>
>> /Users/Sam/anaconda/lib/python2.7/site-packages/sklearn/utils/estimator_checks.pyc
>> in check_estimator(Estimator)
>> 253 check_parameters_default_constructible(name, Estimator)
>> 254 for check in _yield_all_checks(name, Estimator):
>> --> 255 check(name, Estimator)
>> 256
>> 257
>>
>> /Users/Sam/anaconda/lib/python2.7/site-packages/sklearn/utils/testing.pyc
>> in wrapper(*args, **kwargs)
>> 353 with warnings.catch_warnings():
>> 354 warnings.simplefilter("ignore",
>> self.category)
>> --> 355 return fn(*args, **kwargs)
>> 356
>> 357 return wrapper
>>
>> /Users/Sam/anaconda/lib/python2.7/site-packages/sklearn/utils/estimator_checks.pyc
>> in check_transformer_general(name, Transformer)
>> 578 X = StandardScaler().fit_transform(X)
>> 579 X -= X.min()
>> --> 580 _check_transformer(name, Transformer, X, y)
>> 581 _check_transformer(name, Transformer, X.tolist(), y.tolist())
>> 582
>>
>> /Users/Sam/anaconda/lib/python2.7/site-packages/sklearn/utils/estimator_checks.pyc
>> in _check_transformer(name, Transformer, X, y)
>> 671 if hasattr(X, 'T'):
>> 672 # If it's not an array, it does not have a
>> 'T' property
>> --> 673 assert_raises(ValueError, transformer.transform, X.T)
>> 674
>> 675
>>
>> /Users/Sam/anaconda/lib/python2.7/unittest/case.pyc in
>> assertRaises(self, excClass, callableObj, *args, **kwargs)
>> 471 return context
>> 472 with context:
>> --> 473 callableObj(*args, **kwargs)
>> 474
>> 475 def _getAssertEqualityFunc(self, first, second):
>>
>> /Users/Sam/anaconda/lib/python2.7/unittest/case.pyc in
>> __exit__(self, exc_type, exc_value, tb)
>> 114 exc_name = str(self.expected)
>> 115 raise self.failureException(
>> --> 116 "{0} not raised".format(exc_name))
>> 117 if not issubclass(exc_type, self.expected):
>> 118 # let unexpected exceptions pass through
>>
>> AssertionError: ValueError not raised
>>
>>
>> On Tue, Jul 25, 2017 at 12:54 AM, Joel Nothman
>> <joel.nothman at gmail.com <mailto:joel.nothman at gmail.com>> wrote:
>>
>> what is the failing test? please provide the full traceback.
>>
>> On 24 Jul 2017 10:58 pm, "Sam Barnett"
>> <sambarnett95 at gmail.com <mailto:sambarnett95 at gmail.com>>
>> wrote:
>>
>> Dear scikit-learn developers,
>>
>> I am developing a transformer, named |Sqizer|, that
>> has the ultimate goal of modifying a kernel for use
>> with the |sklearn.svm| package. When given an input
>> data array |X|, |Sqizer.transform(X)| should have as
>> its output the Gram matrix for |X| using the modified
>> version of the kernel. Here is the code for the class
>> so far:
>>
>> |classSqizer(BaseEstimator,TransformerMixin):def__init__(self,C=1.0,kernel='rbf',degree=3,gamma=1,coef0=0.0,cut_ord_pair=(2,1)):self.C
>> =C self.kernel =kernel self.degree =degree self.gamma
>> =gamma self.coef0 =coef0 self.cut_ord_pair
>> =cut_ord_pair deffit(self,X,y=None):# Check that X
>> and y have correct shapeX,y =check_X_y(X,y)# Store
>> the classes seen during fitself.classes_
>> =unique_labels(y)self.X_ =X self.y_ =y returnself
>> deftransform(self,X):X
>> =check_array(X,warn_on_dtype=True)"""Returns Gram
>> matrix corresponding to X, once
>> sqized."""defkPolynom(x,y):return(self.coef0+self.gamma*np.inner(x,y))**self.degree
>> defkGauss(x,y):returnnp.exp(-self.gamma*np.sum(np.square(x-y)))defkLinear(x,y):returnnp.inner(x,y)defkSigmoid(x,y):returnnp.tanh(self.gamma*np.inner(x,y)+self.coef0)defkernselect(kername):switcher
>> ={'linear':kPolynom,'rbf':kGauss,'sigmoid':kLinear,'poly':kSigmoid,}returnswitcher.get(kername,"nothing")cut_off
>> =self.cut_ord_pair[0]order
>> =self.cut_ord_pair[1]fromSeqKernelimporthiSeqKernEval
>> defgetGram(Y):gram_matrix =np.zeros((Y.|
>>
>> ...
>>
>> [Message clipped]
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>> https://mail.python.org/mailman/listinfo/scikit-learn
>> <https://mail.python.org/mailman/listinfo/scikit-learn>
>>
>>
>>
>>
>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>> https://mail.python.org/mailman/listinfo/scikit-learn
>> <https://mail.python.org/mailman/listinfo/scikit-learn>
>
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org <mailto:scikit-learn at python.org>
> https://mail.python.org/mailman/listinfo/scikit-learn
> <https://mail.python.org/mailman/listinfo/scikit-learn>
>
>
>
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20170726/45122f20/attachment-0001.html>
More information about the scikit-learn
mailing list