When training a Keras model is there a way to have the GPU to take small breaks (sleeps) in between set...












0















My Keras model is currently looking at a lot of data and I personally don't feel comfortable letting my GPU reach 85 degrees...is there a way during a set amount epochs to tell my GPU to take a break?



I understand I could just break down the process into multiple training cycles but because I am using a ReduceLROnPlateau in my callback on an RNN model I would still like the entire training process to be done in one training cycle with the GPU taking small breaks to allow for longer training times with less risk to my personal hardware.



(Not adding code due to this just being a general question.)










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  • 2





    The GPU is just fine at 85 degrees and it has overheating protection anyway.

    – ivan_pozdeev
    Jan 2 at 2:00








  • 1





    It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

    – Chinmay Kanchi
    Jan 2 at 2:06











  • Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

    – Eric C 0114
    Jan 2 at 2:45













  • I just added e!=0 and it worked exactly as I needed thanks again!

    – Eric C 0114
    Jan 2 at 3:10
















0















My Keras model is currently looking at a lot of data and I personally don't feel comfortable letting my GPU reach 85 degrees...is there a way during a set amount epochs to tell my GPU to take a break?



I understand I could just break down the process into multiple training cycles but because I am using a ReduceLROnPlateau in my callback on an RNN model I would still like the entire training process to be done in one training cycle with the GPU taking small breaks to allow for longer training times with less risk to my personal hardware.



(Not adding code due to this just being a general question.)










share|improve this question


















  • 2





    The GPU is just fine at 85 degrees and it has overheating protection anyway.

    – ivan_pozdeev
    Jan 2 at 2:00








  • 1





    It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

    – Chinmay Kanchi
    Jan 2 at 2:06











  • Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

    – Eric C 0114
    Jan 2 at 2:45













  • I just added e!=0 and it worked exactly as I needed thanks again!

    – Eric C 0114
    Jan 2 at 3:10














0












0








0








My Keras model is currently looking at a lot of data and I personally don't feel comfortable letting my GPU reach 85 degrees...is there a way during a set amount epochs to tell my GPU to take a break?



I understand I could just break down the process into multiple training cycles but because I am using a ReduceLROnPlateau in my callback on an RNN model I would still like the entire training process to be done in one training cycle with the GPU taking small breaks to allow for longer training times with less risk to my personal hardware.



(Not adding code due to this just being a general question.)










share|improve this question














My Keras model is currently looking at a lot of data and I personally don't feel comfortable letting my GPU reach 85 degrees...is there a way during a set amount epochs to tell my GPU to take a break?



I understand I could just break down the process into multiple training cycles but because I am using a ReduceLROnPlateau in my callback on an RNN model I would still like the entire training process to be done in one training cycle with the GPU taking small breaks to allow for longer training times with less risk to my personal hardware.



(Not adding code due to this just being a general question.)







python tensorflow machine-learning keras artificial-intelligence






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Jan 2 at 1:57









Eric C 0114Eric C 0114

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  • 2





    The GPU is just fine at 85 degrees and it has overheating protection anyway.

    – ivan_pozdeev
    Jan 2 at 2:00








  • 1





    It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

    – Chinmay Kanchi
    Jan 2 at 2:06











  • Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

    – Eric C 0114
    Jan 2 at 2:45













  • I just added e!=0 and it worked exactly as I needed thanks again!

    – Eric C 0114
    Jan 2 at 3:10














  • 2





    The GPU is just fine at 85 degrees and it has overheating protection anyway.

    – ivan_pozdeev
    Jan 2 at 2:00








  • 1





    It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

    – Chinmay Kanchi
    Jan 2 at 2:06











  • Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

    – Eric C 0114
    Jan 2 at 2:45













  • I just added e!=0 and it worked exactly as I needed thanks again!

    – Eric C 0114
    Jan 2 at 3:10








2




2





The GPU is just fine at 85 degrees and it has overheating protection anyway.

– ivan_pozdeev
Jan 2 at 2:00







The GPU is just fine at 85 degrees and it has overheating protection anyway.

– ivan_pozdeev
Jan 2 at 2:00






1




1





It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

– Chinmay Kanchi
Jan 2 at 2:06





It looks like you could simply add a LambdaCallback and define on_epoch_begin as lambda e, l: time.sleep(10) if e % 10 == 0 else None or similar.

– Chinmay Kanchi
Jan 2 at 2:06













Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

– Eric C 0114
Jan 2 at 2:45







Usually, it is my friend told me how his own personal hit 85+ degrees in a 2 day period and crashed losing all his progress. So I am just worried and saving 20 minutes or so to save 7-12 hours is a pretty good deal in my book. Regardless thank you for reassurance. But I am interested in this LambdaCallback now...

– Eric C 0114
Jan 2 at 2:45















I just added e!=0 and it worked exactly as I needed thanks again!

– Eric C 0114
Jan 2 at 3:10





I just added e!=0 and it worked exactly as I needed thanks again!

– Eric C 0114
Jan 2 at 3:10












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