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GPU #1
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Hi, I have not used google colab so I am not familiar with it. Which part is time-consuming? Data processing or optimization? |
Thank you so much for your reply, All of that is time consuming. I changed
the code to print the number of each step and it took more than 4 hours for
137 steps in training (and the 'steps' in config is 10000!). And I saw that
the tf.device_name() shows nothing which means it doesn't use the gpu.
Should I install sth special for that? I install all the requirements as
you said in the readme file(for example you said tensorflow>=1.4.0 and I
install tensorflow=1.4.0).
Would you please tell me a good config to train faster? Or give me a brief
explanation for each config parameters so I change them properly.
Regards
…On Sun, Aug 8, 2021, 6:53 PM vanint ***@***.***> wrote:
Hi, I have not used google colab so I am not familiar with it. Which part
is time-consuming? Data processing or optimization?
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In fact, I did not encounter this problem, where I conduct experiments on the sever with four Titan X GPUs. I think the reasons may lie on the gpu platform or python packages. Can you find any private server to verify the first factor? Moreover, have you tried to install tensorflow-gpu? |
I installed tensorflow-gpu=1.4
And cuda 8 and cudnn 6
But still doesn't work:(
Did I install right versions?
…On Sun, Aug 8, 2021, 7:37 PM vanint ***@***.***> wrote:
In fact, I did not encounter this problem, where I conduct experiments on
the sever with four Titan X GPUs. I think the reasons may lie on the gpu
platform or python packages. Can you find any private server to verify the
first factor? Moreover, have you tried to install tensorflow-gpu?
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I guess so. Since I have left the previous school, the server I used has been modified, so I cannot access it to confirm the details. In addition to finding a private server, one more suggestion is that you can first try the code in EIIE (https://github.com/ZhengyaoJiang/PGPortfolio), since our method is developed based on this repository. If it works, then you can change the method part to our method. |
Aha, thanks a lot.
Can I use other versions of tensorflow?Should tensorflow-gpu version be 1.4?
…On Sun, Aug 8, 2021, 8:10 PM vanint ***@***.***> wrote:
I guess so. Since I have left the previous school, the server I used has
been modified, so I cannot access it to confirm the details. In addition to
finding a private server, one more suggestion is that you can first try the
code in EIIE (https://github.com/ZhengyaoJiang/PGPortfolio), since our
method is developed based on this repository. If it works, then you can
change the method part to our method.
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Sure, if it works. |
Thanks a lot for your guides.
Wish you always be happy and healthy :)
…On Sun, Aug 8, 2021, 8:34 PM vanint ***@***.***> wrote:
Sure, if it works.
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hello. regards |
Hi, the performance depends on many reasons, like data split (sometimes network may learn shortcut, which is hard to explain in Deep RL), training scheme, and so on. Therefore, I have no idea about the real reason, since it, at least, does not collapse. How about downloading another piece of data for finding a more reasonable benchmark (i.e., modifying operations can lead to more significant change), which may be a solution if you cannot handle it in the end. Yes, the negative portfolio weight is due to the leverage operation; removing it leads to all positive values. |
thank you so much |
Hi again😅
I tried the code with another period of time of S&P500 prices, still I just
got 1.5 for portfolio value:( AND it converges so fast in about 500 steps!
Is it normal? Do you have any suggestion please?
…On Tue, Sep 14, 2021, 6:02 AM vanint ***@***.***> wrote:
Hi, the performance depends on many reasons, like data split (sometimes
network may learn shortcut, which is hard to explain in Deep RL), training
scheme, and so on. Therefore, I have no idea about the real reason, since
it, at least, does not collapse. How about downloading another piece of
data for finding a more reasonable benchmark (i.e., modifying operations
can lead to more significant change), which may be a solution if you cannot
handle it in the end.
Yes, the negative portfolio weight is due to the leverage operation;
removing it leads to all positive values.
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I cannot remember the convergence speed exactly, since it is quite an old project. |
Thanks, in the paper it said 100000 steps! 15 hours!
…On Wed, Nov 3, 2021, 6:00 AM vanint ***@***.***> wrote:
I cannot remember the convergence speed exactly, since it is quite an old
project.
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hello.
very sorry for commenting here, my question is from ppn portfolio which its issues is closed and I had no other way to ask from you.
i tried to run that project on google colab but it took so much time which colab doesn't accept. i figured out that tensorflow 1.4.0 doesn't use gpu. is there any solution for that? i tried so much but i got no answer. please help me.
and if there is anything that i should consider while using colab for that project, please remind me.
regards
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