But at the same time, why you want to do that? Make sure to delete all
Theano shared variable and theano function that was created, this should do
it. Maybe you need to force python gc, to have it run right now and not
being deleyed:

import gc; for i in range(3): gc.collect()

On Tue, Aug 16, 2016 at 8:04 AM, Frédéric Bastien <
[email protected]> wrote:

> killing a process request killing python. If you use ipython (and not
> ipython notebook) I don't know how to do it without killing ipython.
>
> For ipython notebook, you can go in the menu and "restart" the kernel.
> There is an option for that.
>
> Fred
>
> On Tue, Aug 16, 2016 at 5:51 AM, Yossi Singer <[email protected]> wrote:
>
>> This is an old post, but having the same issue!
>>
>> How do you properly kill the process? I have been using 'ctrl+c' which
>> stops the process, but this does not free the memory on the GPU. The only
>> way I have been able to free up the memory has been to kill iPython and
>> restart it. Is there another way to do this without having to restart
>> iPython?
>>
>> On Tuesday, September 2, 2014 at 8:56:26 PM UTC+1, Muneeb Saleem wrote:
>>>
>>> I think I figured out my mistake. I wasn't properly killing the
>>> processes after stopping them.
>>>
>>> On Tuesday, September 2, 2014 12:59:13 PM UTC-5, Arnaud Bergeron wrote:
>>>>
>>>> Which version of cuda is this?
>>>>
>>>>
>>>> 2014-09-01 0:36 GMT-04:00 Muneeb Saleem <[email protected]>:
>>>>
>>>>> Whenever I manually kill my program/process, the GPU memory under use
>>>>> by it (using Theano shared variables with borrow=True) does not get freed
>>>>> automatically. Since I'm training with large chunks of data, after a few
>>>>> subsequent run-time terminations, the whole GPU memory gets full. The only
>>>>> way to clear that then is to restart the system since my Titan Black on
>>>>> Ubuntu does not have any memory reset functions. Is there a way to clear
>>>>> this memory since I have to manually shut down my program often?
>>>>>
>>>>> --
>>>>>
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>>>>
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>
>

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