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ts: don't run DNN tests with large models (valgrind)

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This commit is contained in:
Alexander Alekhin 2017-07-24 19:24:46 +03:00
parent 1516103a15
commit d17b099994
1 changed files with 3 additions and 4 deletions
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7
modules/ts/misc/run_long.py
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@ -7,6 +7,7 @@ from pprint import PrettyPrinter as PP
LONG_TESTS_DEBUG_VALGRIND = [
('calib3d', 'Calib3d_InitUndistortRectifyMap.accuracy', 2017.22),
('dnn', 'Reproducibility*', 1000), # large DNN models
('features2d', 'Features2d_Feature2d.no_crash', 1235.68),
('ml', 'ML_RTrees.regression', 1423.47),
('optflow', 'DenseOpticalFlow_DeepFlow.ReferenceAccuracy', 1360.95),
@ -43,10 +44,8 @@ LONG_TESTS_DEBUG_VALGRIND = [
]
def longTestFilter(data):
res = ['*', '-']
for _, v, _ in data:
res.append(v)
def longTestFilter(data, module = None):
res = ['*', '-'] + [v for _, v, m in data if module is None or m == module]
return '--gtest_filter={}'.format(':'.join(res))