Better error checking during initialization

Commencez par suivre l'initialisation du backend depuis arrayfire.backend.name() en passant par arrayfire.Array() et le chemin safe_call indiqué dans le traceback. Confirmez comment la disponibilité du périphérique est actuellement vérifiée et faites en sorte que le rapport d'erreur signale une erreur utile du pilote ou du périphérique ; vérifiez le comportement avec le scénario d'initialisation décrit dans l'issue.

Today I came across the following cryptic error message when trying to use arrayfire-python:

In [1]: import arrayfire
In [2]: arrayfire.backend.name()
Out[2]: 'cuda'
In [5]: arrayfire.Array()
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-5-6dffbbbc7abd> in <module>()
----> 1 arrayfire.Array()

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/array.pyc in __init__(self, src, dims, dtype, is_device)
    422             for n in range(numdims):
    423                 idims[n] = dims[n]
--> 424             self.arr = _create_empty_array(numdims, idims, to_dtype[type_char])
    425
    426     def as_type(self, ty):

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/array.pyc in _create_empty_array(numdims, idims, dtype)
     36     c_dims = dim4(idims[0], idims[1], idims[2], idims[3])
     37     safe_call(backend.get().af_create_handle(ct.pointer(out_arr),
---> 38                                              numdims, ct.pointer(c_dims), dtype.value))
     39     return out_arr
     40

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/util.pyc in safe_call(af_error)
     73         err_len = ct.c_longlong(0)
     74         backend.get().af_get_last_error(ct.pointer(err_str), ct.pointer(err_len))
---> 75         raise RuntimeError(to_str(err_str), af_error)
     76
     77 def get_version():

RuntimeError: ('Error in /var/lib/jenkins-slave/workspace/arrayfire-linux-mkl-graphics-installer/src/api/c/data.cpp(197):\n\n\n', 998)

The error was caused by a bad driver version:

$ nvidia-smi
Failed to initialize NVML: GPU access blocked by the operating system

I think it could be useful if arrayfire would test if a device is really available, instead of just checking if it can dlopen the relevant library. For example by calling arrayfire.Array(). If that would fail a more useful error could be returned to the user.