[SciPy-Dev] Lapack alignment test in linalg failing

Warren Weckesser warren.weckesser@enthought....
Mon Apr 12 15:34:28 CDT 2010


Anne Archibald wrote:
> On 12 April 2010 12:22, Warren Weckesser <warren.weckesser@enthought.com> wrote:
>   
>> I created a ticket: http://projects.scipy.org/scipy/ticket/1152
>>
>> If any of the original authors or editors of the code that tests
>> misaligned arrays are still around, some feedback would be appreciated,
>> especially about why the misalignment is being done twice.  I'm not sure
>> if that is intentional.
>>     
>
> That code is my fault, and it's a mess. I think the correct way to
> handle this is to catch the "NaNs/Infs present" exception, or possibly
> to edit the misaligned arrays to remove any NaNs/Infs. Unfortunately
> the bug this was attempting to tickle is deep in the bowels of ATLAS,
> and is very difficult to trigger correctly; in particular, an identity
> matrix does not trigger the bug. This is the reason S is misaligned
> twice: it takes that kind of bizarre data to trigger the bug. Since
> the symptom of the bug is a segfault, raising a "no NaNs" error
> qualifies as a pass (though I'm a little surprised you got any NaNs -
> what platform are you using?)
>
>   

Using scipy 0.8.0 r6120 or later, I get the same error on Mac OSX, Linux 
(RH 64 bit), and Windows XP.

Does the test really need to reuse the output of the first call of 
solve() as the input to the second call? That is, does it really need 
overwrite enabled?  If so, then catching the exception and calling that 
a "pass" doesn't seem right, because that prevents the underlying lapack 
routine from being called the second time.


Warren


> Anne
>
>   
>> Cheers,
>>
>> Warren
>>
>>
>> Warren Weckesser wrote:
>>     
>>> I am getting a failure of an alignment test in test_decomp.py in the linalg
>>> test suite.  I just made several changes in linalg, but this failure has
>>> been occurring since before those changes.
>>>
>>> Here is the error message:
>>>
>>> ======================================================================
>>> ERROR: test_decomp.test_lapack_misaligned(<function solve at 0x4160c70>,
>>> (array([[  1.73394741e-255,   8.18880997e-217,   4.02522535e-178,
>>> ----------------------------------------------------------------------
>>> Traceback (most recent call last):
>>>   File
>>> "/Library/Frameworks/Python.framework/Versions/6.1/lib/python2.6/site-packages/nose/case.py",
>>> line 183, in runTest
>>>     self.test(*self.arg)
>>>   File
>>> "/Users/warren/scipy_src_cho_solveh_banded/scipy/linalg/tests/test_decomp.py",
>>> line 1074, in check_lapack_misaligned
>>>     func(*a,**kwargs)
>>>   File
>>> "/Users/warren/scipy_src_cho_solveh_banded/build/lib.macosx-10.5-i386-2.6/scipy/linalg/basic.py",
>>> line 47, in solve
>>>     a1, b1 = map(asarray_chkfinite,(a,b))
>>>   File
>>> "/Library/Frameworks/Python.framework/Versions/6.1/lib/python2.6/site-packages/numpy/lib/function_base.py",
>>> line 586, in asarray_chkfinite
>>>     raise ValueError, "array must not contain infs or NaNs"
>>> ValueError: array must not contain infs or NaNs
>>>
>>> ----------------------------------------------------------------------
>>>
>>> The file test_decomp.py in linalg/tests contains the following code:
>>>
>>> -----
>>> def check_lapack_misaligned(func, args, kwargs):
>>>     args = list(args)
>>>     for i in range(len(args)):
>>>         a = args[:]
>>>         if isinstance(a[i],np.ndarray):
>>>             # Try misaligning a[i]
>>>             aa = np.zeros(a[i].size*a[i].dtype.itemsize+8, dtype=np.uint8)
>>>             aa = np.frombuffer(aa.data, offset=4, count=a[i].size,
>>> dtype=a[i].dtype)
>>>             aa.shape = a[i].shape
>>>             aa[...] = a[i]
>>>             a[i] = aa
>>>             func(*a,**kwargs)
>>>             if len(a[i].shape)>1:
>>>                 a[i] = a[i].T
>>>                 func(*a,**kwargs)
>>>
>>>
>>> def test_lapack_misaligned():
>>>     M = np.eye(10,dtype=float)
>>>     R = np.arange(100)
>>>     R.shape = 10,10
>>>     S = np.arange(20000,dtype=np.uint8)
>>>     S = np.frombuffer(S.data, offset=4, count=100, dtype=np.float)
>>>     S.shape = 10, 10
>>>     b = np.ones(10)
>>>     v = np.ones(3,dtype=float)
>>>     LU, piv = lu_factor(S)
>>>     for (func, args, kwargs) in [
>>>             (eig,(S,),dict(overwrite_a=True)), # crash
>>>             (eigvals,(S,),dict(overwrite_a=True)), # no crash
>>>             (lu,(S,),dict(overwrite_a=True)), # no crash
>>>             (lu_factor,(S,),dict(overwrite_a=True)), # no crash
>>>             (lu_solve,((LU,piv),b),dict(overwrite_b=True)),
>>>             (solve,(S,b),dict(overwrite_a=True,overwrite_b=True)),
>>>             (svd,(M,),dict(overwrite_a=True)), # no crash
>>>             (svd,(R,),dict(overwrite_a=True)), # no crash
>>>             (svd,(S,),dict(overwrite_a=True)), # crash
>>>             (svdvals,(S,),dict()), # no crash
>>>             (svdvals,(S,),dict(overwrite_a=True)), #crash
>>>             (cholesky,(M,),dict(overwrite_a=True)), # no crash
>>>             (qr,(S,),dict(overwrite_a=True)), # crash
>>>             (rq,(S,),dict(overwrite_a=True)), # crash
>>>             (hessenberg,(S,),dict(overwrite_a=True)), # crash
>>>             (schur,(S,),dict(overwrite_a=True)), # crash
>>>             ]:
>>>         yield check_lapack_misaligned, func, args, kwargs
>>> ---
>>>
>>> The error occurs when `solve` is called from within
>>> check_lapack_misaligned.  Since `solve` has two array arguments,
>>> check_lapack_misaligned will try to call `solve` four times.
>>> The problem is that the first call results in NaNs in the arrays,
>>> which causes the next call to to `solve` to fail.  Apparently the NaNs
>>> result from the data in the array being random junk with exponents
>>> ranging all over.
>>>
>>> If I add these lines after setting `S.shape` in test_lapack_misaligned,
>>> the error does not occur:
>>>
>>>     S[...] = 0.0
>>>     S[range(10),range(10)] = 1.0
>>>
>>> In other words, keep S misaligned, but make it the identity matrix.
>>>
>>> Is that a "saner" test?
>>>
>>> The error can also be avoided by setting the overwrite arguments
>>> to False.  However, I don't know if the values of these arguments
>>> are an important part of the test.
>>>
>>> I don't really understand the logic in these two functions.
>>> test_lapack_misaligned misaligns `S`, but then check_lapack_misaligned
>>> further misaligns its arguments.  Why do this twice?
>>>
>>> Warren
>>>
>>> _______________________________________________
>>> SciPy-Dev mailing list
>>> SciPy-Dev@scipy.org
>>> http://mail.scipy.org/mailman/listinfo/scipy-dev
>>>
>>>       
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