Python,theano Runtimeerror:无法初始化元素支持

4

如果这个问题太简单了,那是因为我对这些东西还很陌生。我在Ubuntu Trusty Tahr上设置theano使用我的GPU进行计算。我有AMD Radeon HD 7670M GPU。当我尝试运行测试脚本以检查theano与GPU的功能时,我遇到以下错误:

Mapped name None to device opencl0:0: Turks
Traceback (most recent call last):
  File "test.py", line 11, in <module>
    f = function([], T.exp(x))
  File "/home/sachu/git/Theano/theano/compile/function.py", line 322, in function
    output_keys=output_keys)
  File "/home/sachu/git/Theano/theano/compile/pfunc.py", line 480, in pfunc
    output_keys=output_keys)
  File "/home/sachu/git/Theano/theano/compile/function_module.py", line 1784, in orig_function
    defaults)
  File "/home/sachu/git/Theano/theano/compile/function_module.py", line 1648, in create
    input_storage=input_storage_lists, storage_map=storage_map)
  File "/home/sachu/git/Theano/theano/gof/link.py", line 699, in make_thunk
    storage_map=storage_map)[:3]
  File "/home/sachu/git/Theano/theano/gof/vm.py", line 1042, in make_all
    no_recycling))
  File "/home/sachu/git/Theano/theano/gof/op.py", line 975, in make_thunk
    no_recycling)
  File "/home/sachu/git/Theano/theano/gof/op.py", line 875, in make_c_thunk
    output_storage=node_output_storage)
  File "/home/sachu/git/Theano/theano/gof/cc.py", line 1189, in make_thunk
    keep_lock=keep_lock)
  File "/home/sachu/git/Theano/theano/gof/cc.py", line 1130, in __compile__
    keep_lock=keep_lock)
  File "/home/sachu/git/Theano/theano/gof/cc.py", line 1602, in cthunk_factory
    *(in_storage + out_storage + orphd))
RuntimeError: ('The following error happened while compiling the node', GpuElemwise{exp,no_inplace}(<GpuArrayType<None>(float64, (False,))>), '\n', 'Could not initialize elemwise support')

我运行的脚本是网站上提供的:http://deeplearning.net/software/theano/tutorial/using_gpu.html是否配置有误?我相信所有依赖项都设置正确,但我可能犯了一些错误,但我可能会遇到其他问题而不是运行时错误。我在github上搜索了很多与此相关的信息,但没有找到任何信息。在stackoverflow上搜索后也得到了同样的结果,因此我在这里发布了这个帖子。感谢任何帮助。 附加信息:python3.4,theano bleeding edge版本。Libgpuarray、clblas、openblas都是从git源主分支构建的。64位架构。
1个回答

1
Theano目前还不支持OpenCL,而且开发团队似乎也没有将其作为优先事项来解决(参见this issue)。因此,您需要耐心等待或使用nvidia GPU运行CUDA。

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