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dpfksDeepFaceLab 2.0 - General Overview and Discussion
#11
(01-23-2020, 03:30 AM)tutsmybarreh Wrote: You are not allowed to view links. Register or Login to view.
(01-23-2020, 03:29 AM)frosty3907 Wrote: You are not allowed to view links. Register or Login to view.I'd taken a timeout to give the program some time to mature... guess it's time to jump back in!

Wait a bit, there will be more updates shortly so don't train to much Wink

Are you saying that models using 2.0 will likely not be compatible with future releases?  Trying to decide to stick with version 1 for a while until 2 matures, or try out 2.  I hate re-training models from scratch, so don't want to have to do it too often. Smile
#12
(01-25-2020, 02:31 AM)sharital Wrote: You are not allowed to view links. Register or Login to view.
(01-23-2020, 03:30 AM)tutsmybarreh Wrote: You are not allowed to view links. Register or Login to view.
(01-23-2020, 03:29 AM)frosty3907 Wrote: You are not allowed to view links. Register or Login to view.I'd taken a timeout to give the program some time to mature... guess it's time to jump back in!

Wait a bit, there will be more updates shortly so don't train to much Wink

Are you saying that models using 2.0 will likely not be compatible with future releases?  Trying to decide to stick with version 1 for a while until 2 matures, or try out 2.  I hate re-training models from scratch, so don't want to have to do it too often. Smile

Models from 1.0 are not compatible with 2.0 and new models trained on 2.0 might be rendered useless by future updates, that's just the nature of in-development software. You can wait or you can start working on it, I doubt there will be any model breaking changes in the near future.

(01-25-2020, 01:52 AM)kilerb Wrote: You are not allowed to view links. Register or Login to view.I agree that it should play.  But I have 3 computers and all of them need VLC player for 265 files.  I don't think they have viruses.  One of them is really new.  I'll have to investigate more.
I wasn't saying VLC is a virus... I was saying you shouldn't be paying for h265, reffering to what you wrote: "Maybe a codec download will fix that?  It's asking for money in Windows.  No biggie..."
Raising money for a new GPU, if you enjoy my fakes or my work on forums consider donating via bitcoin, tokens or paypal/patreon, any amount helps!
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#13
I just downloaded DeepFaceLab_NVIDIA_build_01_23_2020. is this 2.0 version?
#14
(01-25-2020, 06:48 PM)tobe2d Wrote: You are not allowed to view links. Register or Login to view.I just downloaded DeepFaceLab_NVIDIA_build_01_23_2020. is this  2.0 version?

Yep.


Question for the experts. Wink

In 2.0, in terms of plain-language anticipated results, what is the difference between using DFL and DFLHD if you are using 128 resolution on both?  Typically "HD" refers to a higher resolution, but if you are using a 128x128 pic on both, then it isn't really higher res...... so what does DFLHD do that is "HD" that DFL does not in 2.0?  Thanks in advance for the explanation.

Purpose:  trying to figure out if it is worth it to run DFLHD over DFL even though DFLHD is slower and can run less batches.
#15
(01-25-2020, 06:58 PM)sharital Wrote: You are not allowed to view links. Register or Login to view.
(01-25-2020, 06:48 PM)tobe2d Wrote: You are not allowed to view links. Register or Login to view.I just downloaded DeepFaceLab_NVIDIA_build_01_23_2020. is this  2.0 version?

Yep.


Question for the experts. Wink

In 2.0, in terms of plain-language anticipated results, what is the difference between using DFL and DFLHD if you are using 128 resolution on both?  Typically "HD" refers to a higher resolution, but if you are using a 128x128 pic on both, then it isn't really higher res...... so what does DFLHD do that is "HD" that DFL does not in 2.0?  Thanks in advance for the explanation.

Purpose:  trying to figure out if it is worth it to run DFLHD over DFL even though DFLHD is slower and can run less batches.

There is no "DFLHD", I think you're reffering to different architectures such as DF/LIAE and DFHD/LIAEHD - answer to this you can find in the 3rd post (1st page) in this thread.
If you want to know what's the real difference well, for that you'd have to ask Iperov but it's probably what I wrote, it only reffers to the fact that HD versions are what was SAEHD in the old one and DF is SAE but with features of SAEHD (sort of what @Fappenberg modded into his SAE+ mod). It's something to do with additional layers in the neural network.
Raising money for a new GPU, if you enjoy my fakes or my work on forums consider donating via bitcoin, tokens or paypal/patreon, any amount helps!
Paypal/Patreon: You are not allowed to view links. Register or Login to view.
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#16
Yeah, I meant DFHD vs DF, not DFLHD. Just added an extra L in there.

So basically the answer is "DFHD has mysterious internal stuff that makes it better that only Iperov knows and we don't."

I'll just continue to play around with them. Right now I think I'm forming the opinion that even the new DFHD is too slow on a GTX 1070, so probably will try/use 2.0 DF. (Was previously using SAE+ mod in version 1.)
#17
(01-25-2020, 08:12 PM)sharital Wrote: You are not allowed to view links. Register or Login to view.Yeah, I meant DFHD vs DF, not DFLHD.  Just added an extra L in there.

So basically the answer is "DFHD has mysterious internal stuff that makes it better that only Iperov knows and we don't."  

I'll just continue to play around with them.  Right now I think I'm forming the opinion that even the new DFHD is too slow on a GTX 1070, so probably will try/use 2.0 DF. (Was previously using SAE+ mod in version 1.)

No, it's not mysterious, you just have to know how neural networks and machine learning works to understand it, I don't know it perfectly either but I've read a bit about it and talked with @fappenberg and really the only difference between DF/LIAE and their HD counterparts (now) is number of layers in the network, rest is the same, before SAE and SAEHD was separate and DF in SAE didn't have all the features and was working in a different way than DF in SAEHD but now they share almost everything except for that thing. As I said we already had this (expect for layers) hacked in SAE+, the reason why it now works better is that iperov further optimised the whole thing so it runs faster.

If you want run HD variants, they should offer more realistic results but DF is still a good option if you don't have the power or want to train your fakes faster. And on that let's end all debates about differences between two, there is no reason to spam it more and I think I explained it as good as I can, the only one who can give you better answer is Iperov but he is busy so I wouldn't bother him with these question.
Raising money for a new GPU, if you enjoy my fakes or my work on forums consider donating via bitcoin, tokens or paypal/patreon, any amount helps!
Paypal/Patreon: You are not allowed to view links. Register or Login to view.
Bitcoin: 1C3dq9zF2DhXKeu969EYmP9UTvHobKKNKF
Want to request a paid deepfake or have any questions reagarding the forums or deepfake creation using DeepFaceLab? Write me a message.
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#18
(01-24-2020, 07:30 PM)jknight Wrote: You are not allowed to view links. Register or Login to view.================== Model Summary ==================
==                                               ==
==            Model name: m_SAEHD                ==
==                                               ==
==     Current iteration: 22563                  ==
==                                               ==
==---------------- Model Options ----------------==
==                                               ==
==            autobackup: False                  ==
== write_preview_history: False                  ==
==           target_iter: 0                      ==
==           random_flip: False                  ==
==            resolution: 256                    ==
==             face_type: f                      ==
==     models_opt_on_gpu: False                  ==
==                 archi: dfhd                   ==
==               ae_dims: 512                    ==
==                e_dims: 28                     ==
==                d_dims: 28                     ==
==           d_mask_dims: 28                     ==
==            learn_mask: True                   ==
==            lr_dropout: False                  ==
==           random_warp: True                   ==
==    true_face_training: False                  ==
==      face_style_power: 0.0                    ==
==        bg_style_power: 0.0                    ==
==               ct_mode: none                   ==
==              clipgrad: False                  ==
==              pretrain: False                  ==
==            batch_size: 4                      ==
==                                               ==
==----------------- Running On ------------------==
==                                               ==
==          Device index: 0                      ==
==                  Name: GeForce RTX 2080 SUPER ==
==                  VRAM: 8.00GB                 ==
==                                               ==
===================================================

Getting one OOM after loading models and packs. After that no OOM's. I do however get OOM's and full stop if I turn OFF learn mask. This seems odd as I assume that this would cause less VRAM usage. Anyone else have this issue?

Thanks for sharing a starting point to fiddle around with for RTX 8 GB GPUs. Keen to share your pretrained model?
#19
New Version out. And retrain all again :D
#20
Definitely going to give this a try, both CUDA and mutli-CPU.

Request: Could you add a parameter that specifies how many CPU cores will be used? When running the OpenCL / CPU-only version it appears the default number of CPUs invoked by TensorFlow is still 8. I've tried some suggested hacks to config files in the past but they only increased the number of CPUs used for about half of the .bat functions. My CPU-only virtual machine has 24 CPU cores available to it so it would be wonderful to be able to utilize all of them.

Thank you for all your amazing work!
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