I have installed theano on ubuntu 18.04 LTS when I test numpy as given in
http://deeplearning.net/software/theano/troubleshooting.html#test-blas >> numpy.test() it gives the below error and Fails. I have no idea what needs to be changed..... Any suggestions to resolve this problem are highly appreciated. my environment: *ubuntu 18.04 LTS* *Miniconda3* *virtualenv which has python3.5* *additional installations: Intel Distribution for python with conda* *numpy version 1.15.2* ========================= ERROR CONTENT ============================================ >>> numpy.test() NumPy version 1.15.2 NumPy relaxed strides checking option: True .................x.................................................................... [ 1%] ...................................................................................... [ 3%] ...................................................................................... [ 5%] ......s................x.x............................................................ [ 6%] ..................................................................... ...............................................................................sss.... [ 98%] ....................................................... [100%] ========================================== FAILURES ========================================== __________________________________ TestSeterr.test_default ___________________________________ self = <numpy.core.tests.test_numeric.TestSeterr object at 0x7fa3e3c67860> def test_default(self): err = np.geterr() assert_equal(err, dict(divide='warn', invalid='warn', over='warn', > under='ignore') ) E AssertionError: E Items are not equal: E key='over' E E ACTUAL: 'raise' E DESIRED: 'warn' err = {'divide': 'ignore', 'invalid': 'ignore', 'over': 'raise', 'under': 'ignore'} self = <numpy.core.tests.test_numeric.TestSeterr object at 0x7fa3e3c67860> miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_numeric.py:455: Assertr __________________________________ TestNegative.test_result __________________________________ self = <numpy.core.tests.test_scalarmath.TestNegative object at 0x7fa3e3aa5898> def test_result(self): types = np.typecodes['AllInteger'] + np.typecodes['AllFloat'] with suppress_warnings() as sup: sup.filter(RuntimeWarning) for dt in types: a = np.ones((), dtype=dt)[()] > assert_equal(operator.neg(a) + a, 0) E FloatingPointError: overflow encountered in ubyte_scalars a = 1 dt = 'B' self = <numpy.core.tests.test_scalarmath.TestNegative object at 0x7fa3e3aa5898> sup = <numpy.testing._private.utils.suppress_warnings object at 0x7fa423bff710> types = 'bBhHiIlLqQpPefdgFDG' miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_scalarmath.py:623: Flor _____________________________________ TestUfunc.test_sum _____________________________________ self = <numpy.core.tests.test_ufunc.TestUfunc object at 0x7fa40083a9e8> def test_sum(self): for dt in (int, np.float16, np.float32, np.float64, np.longdouble): for v in (0, 1, 2, 7, 8, 9, 15, 16, 19, 127, 128, 1024, 1235): tgt = dt(v * (v + 1) / 2) d = np.arange(1, v + 1, dtype=dt) # warning if sum overflows, which it does in float16 overflow = not np.isfinite(tgt) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") > assert_almost_equal(np.sum(d), tgt) d = array([1.000e+00, 2.000e+00, 3.000e+00, ..., 1.022e+03, 1.023e+03, 1.024e+03], dtype=float16) dt = <class 'numpy.float16'> overflow = True self = <numpy.core.tests.test_ufunc.TestUfunc object at 0x7fa40083a9e8> tgt = inf v = 1024 w = [] miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_ufunc.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/fromnumeric.py:1930: in sum initial=initial) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ obj = array([1.000e+00, 2.000e+00, 3.000e+00, ..., 1.022e+03, 1.023e+03, 1.024e+03], dtype=float16) ufunc = <ufunc 'add'>, method = 'sum', axis = None, dtype = None, out = None kwargs = {'initial': <no value>, 'keepdims': <no value>}, passkwargs = {}, k = 'initial' v = <no value> def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs): passkwargs = {} for k, v in kwargs.items(): if v is not np._NoValue: passkwargs[k] = v if type(obj) is not mu.ndarray: try: reduction = getattr(obj, method) except AttributeError: pass else: # This branch is needed for reductions like any which don't # support a dtype. if dtype is not None: return reduction(axis=axis, dtype=dtype, out=out, **passkwargs) else: return reduction(axis=axis, out=out, **passkwargs) > return ufunc.reduce(obj, axis, dtype, out, **passkwargs) E FloatingPointError: overflow encountered in reduce axis = None dtype = None k = 'initial' kwargs = {'initial': <no value>, 'keepdims': <no value>} method = 'sum' obj = array([1.000e+00, 2.000e+00, 3.000e+00, ..., 1.022e+03, 1.023e+03, 1.024e+03], dtype=float16) out = None passkwargs = {} ufunc = <ufunc 'add'> v = <no value> miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/fromnumeric.py:83: FloatingPointEr _________________________________ TestLog2.test_log2_special _________________________________ self = <numpy.core.tests.test_umath.TestLog2 object at 0x7fa402a55e80> def test_log2_special(self): assert_equal(np.log2(1.), 0.) assert_equal(np.log2(np.inf), np.inf) assert_(np.isnan(np.log2(np.nan))) with warnings.catch_warnings(record=True) as w: warnings.filterwarnings('always', '', RuntimeWarning) assert_(np.isnan(np.log2(-1.))) assert_(np.isnan(np.log2(-np.inf))) assert_equal(np.log2(0.), -np.inf) assert_(w[0].category is RuntimeWarning) > assert_(w[1].category is RuntimeWarning) E IndexError: list index out of range self = <numpy.core.tests.test_umath.TestLog2 object at 0x7fa402a55e80> w = [<warnings.WarningMessage object at 0x7fa402a55fd0>] miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_umath.py:570: IndexErrr ________________________________ TestMinMax.test_reduce_warns ________________________________ self = <numpy.core.tests.test_umath.TestMinMax object at 0x7fa423ad2828> def test_reduce_warns(self): # gh 10370, 11029 Some compilers reorder the call to npy_getfloatstatus # and put it before the call to an intrisic function that causes # invalid status to be set. Also make sure warnings are emitted for n in (2, 4, 8, 16, 32): with suppress_warnings() as sup: sup.record(RuntimeWarning) for r in np.diagflat([np.nan] * n): assert_equal(np.min(r), np.nan) > assert_equal(len(sup.log), n) E AssertionError: E Items are not equal: E ACTUAL: 0 E DESIRED: 2 n = 2 r = array([ 0., nan]) self = <numpy.core.tests.test_umath.TestMinMax object at 0x7fa423ad2828> sup = <numpy.testing._private.utils.suppress_warnings object at 0x7fa423ad2630> miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_umath.py:1340: Assertir _______________________________ TestMinMax.test_minimize_warns _______________________________ self = <numpy.core.tests.test_umath.TestMinMax object at 0x7fa42424c2b0> def test_minimize_warns(self): # gh 11589 > assert_warns(RuntimeWarning, np.minimum, np.nan, 1) self = <numpy.core.tests.test_umath.TestMinMax object at 0x7fa42424c2b0> miniconda3/envs/py35/lib/python3.5/site-packages/numpy/core/tests/test_umath.py:1344: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ miniconda3/envs/py35/lib/python3.5/site-packages/numpy/testing/_private/utils.py:1697: in asss return func(*args, **kwargs) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <contextlib._GeneratorContextManager object at 0x7fa42424cbe0>, type = None value = None, traceback = None def __exit__(self, type, value, traceback): if type is None: try: > next(self.gen) E AssertionError: No warning raised when calling minimum self = <contextlib._GeneratorContextManager object at 0x7fa42424cbe0> traceback = None type = None value = None miniconda3/envs/py35/lib/python3.5/contextlib.py:66: AssertionError ====================================== warnings summary ====================================== /home/d/miniconda3/envs/py35/lib/python3.5/site-packages/numpy/fft/tests/test_fft.py:51: Compt a = a.astype(t1) -- Docs: https://docs.pytest.org/en/latest/warnings.html 6 failed, 4635 passed, 393 skipped, 88 deselected, 9 xfailed, 1 warnings in 171.06 seconds False ====================================================================================================== -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. 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