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Augmentated data up to 15G? #24

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YNX940214 opened this issue Jun 17, 2018 · 6 comments
Open

Augmentated data up to 15G? #24

YNX940214 opened this issue Jun 17, 2018 · 6 comments

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@YNX940214
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I generated the augmentated date with the matlab script and 291 images, and the train.h5 is about 15GB.
In the paper the training procedure "takes roughly 4 hours on GPU Titan Z", but it takes far more than 4 hours on my device: GeForce GTX 1080 Ti.
Is it because the device or the augmentated data is too big?

@YNX940214 YNX940214 reopened this Jun 17, 2018
@twtygqyy
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Hi @YNX940214 The size you mentioned about the augmented data is correct, and it does take longer than 4 hours to train in this implementation. The reason is mainly about I didn't use on the fly augmentation during training since I have to use the matlab for bicubic interpolation. Please feel free to modify the code : )

@MingSun-Tse
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@YNX940214 hi, may I ask, how many hours it takes to train the model for 50 epochs? My GPU is TitanX, it seems slow as well. Thx.

@YNX940214
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@MingSun-Tse
Sorry, I forgot. I haven't touch vdsr for a long time. But I may check it a few days later.

@MingSun-Tse
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@YNX940214 okay, never mind. Thank you still.

@YNX940214
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@MingSun-Tse It takes about 20 mins for one epoch on GTX 1080 Ti.

@zymize
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zymize commented Mar 17, 2020

@twtygqyy hello,I use your code to generated the augmentated date with the matlab script and 291 images, and the train.h5 is about 7GB.I see @YNX940214 train.h5 is about 15G. Could you tell me reason? thanks.

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4 participants