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Can't resume training from a preview checkpoint #62

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oxmah opened this issue Jan 12, 2017 · 9 comments
Closed

Can't resume training from a preview checkpoint #62

oxmah opened this issue Jan 12, 2017 · 9 comments

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@oxmah
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oxmah commented Jan 12, 2017

Hello guys !

It maybe an easy question. When I close then try to relaunch the training, it's start from 0 again. Is that a bug or is there something I'm missing ? I didn't find a command from (re)pointing a checkpoint to start from.

Thanks for your answer and sorry if it's a silly question.

@oxmah oxmah closed this as completed Jan 13, 2017
@rjpeart
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rjpeart commented Feb 22, 2017

@mathieuarbezhermoso did you resolve this? I'd also like to know how to continue from a particular checkpoint.

@danieleghisi
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@mathieuarbezhermoso I'd like to know this too!

@danieleghisi
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I think I managed to do that, it should be relatively simple. I've added netD and netG options in the opt = { ... } portion of main.lua, and then simply

if (opt.netD ~= '') then
  print('Initializing discriminator network from' .. opt.netD)
  netD = torch.load(opt.netD)
else 
  netD = nn.Sequential()
 ....
end

and same thing for opt.netG.
That should work, but you should hard code the epoch count by hand if you need to change it; also not sure about how the adam learning rates will behave, but I assume they'll be just reset as if you started from scratch.

@rjpeart
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rjpeart commented Mar 1, 2017

@danieleghisi oh great! I'm gonna try this tonight. Thanks for sharing your findings!

@maryam089
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@rjpeart did you able to update that solution in the code ? If yesh then kindly help me too

@rjpeart
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rjpeart commented Dec 25, 2017 via email

@maryam089
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Thanks so much for quick response. Well i am stuck at resuming epoch from a certain value. Could you explain me the solution mentioned above? I would be extremely thankful to you.

@rjpeart
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rjpeart commented Dec 25, 2017 via email

@maryam089
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Yeah sure well I found one solution... will check it first thing in the morning (since its 2:30 am at my place).Anyway I truly appreciate your concern and kind words. Thank you so much !

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4 participants