Better error checking during initialization
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 38/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- backend-api-design, hpc
Research direction
Start by tracing backend initialization from arrayfire.backend.name() through arrayfire.Array() and the safe_call path shown in the traceback. Confirm how device availability is currently checked and make the failure report a useful driver or device error; verify the behavior with the initialization scenario described in the issue.
Written by the indexing model from the issue text.
Description
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.
- Dominant language
- Python
- Stars
- 422
- Forks
- 63
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
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- Open a pull request that references the issue number.
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