[Numpy-discussion] Fwd: Package: scipy-0.11.0-0.1.rc2.fc18 Tag: f18-updates-candidate Status: failed Built by: orion

Ondřej Čertík ondrej.certik@gmail....
Wed Feb 13 18:18:58 CST 2013


Orion,

On Wed, Feb 13, 2013 at 4:06 PM, Orion Poplawski <orion@cora.nwra.com> wrote:
> On 09/21/2012 11:41 AM, Ondřej Čertík wrote:
>>
>> Hi Orion,
>>
>> On Thu, Sep 20, 2012 at 2:56 PM, Orion Poplawski <orion@cora.nwra.com>
>> wrote:
>>>
>>> This is a plea for some help.  We've been having trouble getting scipy to
>>> pass all of the tests in the Fedora 18 build with python 3.3 (although it
>>> seems to build okay in Fedora 19).  Below are the logs of the build.
>>> There
>>> appears to be some kind of memory corruption that manifests itself a
>>> little
>>> differently on 32-bit vs. 64-bit.  I really have no idea myself how to
>>> pursue debugging this, though I'm happy to provide any more needed
>>> information.
>>
>>
>> Thanks for testing the latest beta2 release.
>>
>>> Task 4509077 on buildvm-35.phx2.fedoraproject.org
>>> Task Type: buildArch (scipy-0.11.0-0.1.rc2.fc18.src.rpm, i686)
>>> logs:
>>>
>>> http://koji.fedoraproject.org/koji/getfile?taskID=4509077&name=build.log
>>
>>
>> This link has the following stacktrace:
>>
>> /lib/libpython3.3m.so.1.0(PyMem_Free+0x1c)[0xbf044c]
>>
>> /usr/lib/python3.3/site-packages/numpy/core/multiarray.cpython-33m.so(+0x4d52b)[0x42252b]
>>
>> /usr/lib/python3.3/site-packages/numpy/core/multiarray.cpython-33m.so(+0xcb7c5)[0x4a07c5]
>>
>> /usr/lib/python3.3/site-packages/numpy/core/multiarray.cpython-33m.so(+0xcbc5e)[0x4a0c5e]
>>
>> Which indeed looks like in NumPy. Would you be able to obtain full
>> stacktrace?
>>
>> There has certainly been segfaults in Python 3.3 with NumPy, but we've
>> fixed all that we could reproduce. That doesn't mean there couldn't be
>> more. If you could nail it down a little bit more, that would be
>> great. I'll help once I can reproduce it somehow.
>>
>> Ondrej
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>
> Trying to get back to this as we still see it with numpy 1.7.0 and scipy
> 0.11.
>
> I'm seeing a segfault in malloc_consolidate(), which seems like would only
> occur if there were problems earlier, so I'm not sure a stack trace is all
> that useful.
>
> Starting program: /usr/bin/python3
> /export/home/orion/redhat/BUILDROOT/scipy-0.11.0-3.fc19.x86_64/usr/lib64/python3.3/site-packages/scipy/linalg/tests/test_decomp.py
> [Thread debugging using libthread_db enabled]
> Using host libthread_db library "/lib64/libthread_db.so.1".
> ..............
> Program received signal SIGSEGV, Segmentation fault.
> 0x0000003d8d67bdad in malloc_consolidate (av=av@entry=0x3d8d9b1740
> <main_arena>)
>     at malloc.c:4151
> 4151                  unlink(av, nextchunk, bck, fwd);
>
> Here's some:
> #0  0x0000003d8d67bdad in malloc_consolidate (av=av@entry=0x3d8d9b1740
> <main_arena>)
>     at malloc.c:4151
> #1  0x0000003d8d67d09e in _int_malloc (av=0x3d8d9b1740 <main_arena>,
> bytes=<optimized out>)
>     at malloc.c:3422
> #2  0x0000003d8d67f443 in __GI___libc_malloc (bytes=2632) at malloc.c:2862
> #3  0x00007ffff121816c in PyArray_IterNew (obj=<numpy.ndarray at remote
> 0xe02fd0>)
>     at numpy/core/src/multiarray/iterators.c:385
> #4  0x00007ffff1218201 in PyArray_IterAllButAxis (obj=obj@entry=
>     <numpy.ndarray at remote 0xe02fd0>, inaxis=inaxis@entry=0x7fffffff873c)
>     at numpy/core/src/multiarray/iterators.c:488
> #5  0x00007ffff1257970 in _new_argsort (which=NPY_QUICKSORT, axis=0,
> op=0xe02fd0)
>     at numpy/core/src/multiarray/item_selection.c:815
> #6  PyArray_ArgSort (op=op@entry=0xe02fd0, axis=0, which=NPY_QUICKSORT)
>     at numpy/core/src/multiarray/item_selection.c:1104
> #7  0x00007ffff125873a in array_argsort (self=0xe02fd0, args=<optimized
> out>,
>     kwds=<optimized out>) at numpy/core/src/multiarray/methods.c:1213
> #8  0x0000003b74d0cc8e in call_function (oparg=<optimized out>,
> pp_stack=0x7fffffff8998)
>     at /usr/src/debug/Python-3.3.0/Python/ceval.c:4091
> #9  PyEval_EvalFrameEx (f=f@entry=
>     Frame 0xd3ecb0, for file
> /usr/lib64/python3.3/site-packages/numpy/core/fromnumeric.py, line 681, in
> argsort (a=<numpy.ndarray at remote 0xe02fd0>, axis=-1, kind='quicksort',
> order=None, argsort=<built-in method argsort of numpy.ndarray object at
> remote 0xe02fd0>),
>     throwflag=throwflag@entry=0) at
> /usr/src/debug/Python-3.3.0/Python/ceval.c:2703
> #10 0x0000003b74d0de63 in PyEval_EvalCodeEx (_co=_co@entry=<code at remote
> 0x7ffff1a8ac00>,
>     globals=<optimized out>, locals=locals@entry=0x0, args=<optimized out>,
>     argcount=argcount@entry=1, kws=0xe23ab8, kwcount=kwcount@entry=0,
> defs=0x7ffff1a965b8,
>     defcount=3, kwdefs=0x0, closure=0x0) at
> /usr/src/debug/Python-3.3.0/Python/ceval.c:3462
> #11 0x0000003b74d0c707 in fast_function (nk=0, na=1, n=<optimized out>,
> pp_stack=
>     0x7fffffff8c88, func=<function at remote 0x7ffff1160320>)
>     at /usr/src/debug/Python-3.3.0/Python/ceval.c:4189
> #12 call_function (oparg=<optimized out>, pp_stack=0x7fffffff8c88)
>     at /usr/src/debug/Python-3.3.0/Python/ceval.c:4112
>
>
> (gdb) up 3
> #3  0x00007ffff121816c in PyArray_IterNew (obj=<numpy.ndarray at remote
> 0xe02fd0>)
>     at numpy/core/src/multiarray/iterators.c:385
> 385         it = (PyArrayIterObject
> *)PyArray_malloc(sizeof(PyArrayIterObject));
> (gdb) print *obj
> $4 = {ob_refcnt = 5, ob_type = 0x7ffff14c6900 <PyArray_Type>}
> (gdb) list
> 380             PyErr_BadInternalCall();
> 381             return NULL;
> 382         }
> 383         ao = (PyArrayObject *)obj;
> 384
> 385         it = (PyArrayIterObject
> *)PyArray_malloc(sizeof(PyArrayIterObject));
> 386         PyObject_Init((PyObject *)it, &PyArrayIter_Type);
> 387         /* it = PyObject_New(PyArrayIterObject, &PyArrayIter_Type);*/
> 388         if (it == NULL) {
> 389             return NULL;


^^^ This is very useful, thanks! How can it segfault on the line 385 though?

That would suggest that something has gone terribly wrong before and
this call to malloc simply is the final nail to the coffin.
Otherwise I thought that malloc can't really segfault like this, can it?

Ondrej


More information about the NumPy-Discussion mailing list