You don't need to delete them. You could just add the device number in them
and so they get reused. Reusing them help speed up the compilation.

I just made a PR that would help having different compiledir for different
device:

https://github.com/Theano/Theano/pull/4831

If you use it with this flag, it will happend automatically and they will
get reused:

compiledir_format="compiledir_%(short_platform)s-%(processor)s-%(python_version)s-%(python_bitwidth)s-%(device)s"

Parallel compilation on the same compiledir seem to only work on linux and
have problems on window. Do you want to investigate that? I don't have time
for that.

Fred

On Sat, Aug 6, 2016 at 12:11 PM, <[email protected]> wrote:

> It sounds great.
> And if I set several different compile directories, do I need to delete
> them after running?
> Thanks
>
> 在 2016年8月6日星期六 UTC-4上午11:45:35,nouiz写道:
>>
>> Can you try using different Theano cache? This will make them
>> independent. Just give each process a different compiledir or
>> base_compiledir Theano flag:
>>
>> http://deeplearning.net/software/theano/library/config.html#
>> config.base_compiledir
>> http://deeplearning.net/software/theano/library/config.html#
>> config.compiledir
>>
>> That should do the trick.
>>
>> On Fri, Aug 5, 2016 at 4:43 PM, <[email protected]> wrote:
>>
>>> Hi, everyone,
>>> I encounter a strange problem.
>>> When I run two similar programs in the same GPU at the same time, one of
>>> them will finally encounter the error as following when it comes to the
>>> theano function compiling.
>>>
>>> IOError:[Error2]No such file or Directory: compiledir_Liunx-4.1--MANJARO-
>>> x86_64-with-glibc2.2.5--2.7.12-64/tempFDXRY9/key.pkl
>>>
>>> In my program, there is a loop for average in which I redefine the net
>>> and the functions in it. In the first loop of both programs it performs
>>> well, but when it comes to the second loop some gonna fail.
>>>
>>> I really appreciate it for any idea about it.
>>>
>>> Dylan
>>>
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>>>
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>>
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