arrayfire / arrayfire/arrayfire-python

Better error checking during initialization

オープン
#51 コメント 6 件 リアクション 0 件 担当者 0 名 GitHub で見る
主要言語
Python
スター
422
フォーク
63
PR マージ指標
30日以内にマージされた PR はありません

説明

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

``` python

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

``` shell
$ 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.

コントリビューションガイド

このリポジトリのコントリビューションガイドは索引されていません

調査の方向性

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.

索引モデルが issue の本文から書いたものです。

評価

技術スタック
python
領域
backend-api-design, hpc
issue の種類
バグ
難易度
4/5
見積もり時間
3〜5日
活発さ
停滞
明瞭さ
おおむね明確
初心者へのやさしさ
38/100

新しい issue をメールで受け取る

初心者向けの GitHub issue を短くまとめたダイジェスト。