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Autohelper generates the same pictures #103

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miasik opened this issue Jan 13, 2024 · 9 comments
Open

Autohelper generates the same pictures #103

miasik opened this issue Jan 13, 2024 · 9 comments
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@miasik
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miasik commented Jan 13, 2024

I've been trying to understand how AutoMergerHelpper works but noticed that it produces the same pictures with 0.5 merge ratio instead of variable rates. Looks like its default merging function overrides AMH and makes the default 0.5 merge after each iteration.
if i noticed correctly it renders the first image from the folder with the current variable ratio and all other images with simple 0.5 ratio

@wkpark wkpark self-assigned this Jan 15, 2024
@wkpark wkpark added the bug Something isn't working label Jan 15, 2024
@wkpark
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wkpark commented Jan 15, 2024

did you try to use MBW mode? Internally, Auto merger helper utilizes MBW weights.
(simple alpha weight will not work currently)

@miasik
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miasik commented Jan 15, 2024

Could you please give a screenshot with settings to try?

@miasik miasik changed the title Autohelper generatуs the same pictures Autohelper generates the same pictures Jan 15, 2024
@miasik
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miasik commented Jan 15, 2024

did you try to use MBW mode? Internally, Auto merger helper utilizes MBW weights. (simple alpha weight will not work currently)

Yes. i did. If it had resolved the issue I haven't reported here -)
I'm sure that AutoHelper has to ignore the simple mode because using it is almost useless.

@wkpark
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wkpark commented Jan 17, 2024

non MBW mode fixed now. thank you for your reporting

wkpark added a commit that referenced this issue Jan 17, 2024
wkpark added a commit that referenced this issue Jan 17, 2024
@wkpark wkpark closed this as completed Jan 25, 2024
@Enferlain
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I'm not sure why, but same issue for me. I did mbw for 7 hours and it made 2200 images but it just repeated the same 10 pics sadge

I ran "A × (1 - α0) + B × α0 + dare_weights(diff C) × α1" with normal calcmode, use advanced mbw mode, and selected blocks "ALL" 0.5 with pattern search and simulated annealing optimizer

@wkpark
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wkpark commented Mar 8, 2024

mbw mode with 7 hours? wow. I didn't do that much.

all possible optimizers are not tested yet. some optimizer won't work at all. other optimizer will work as expected.
and image scoring method also important factor.

anyway, I guess, there are some bug exist to prevent it from working correctly.

I recommend you partial optimizing, for example:

  • select specific model - select only "A" model to optimize.
  • select specific blocks - select only "OUT00, OUT01, OUT03,..."

default setting will try to vary all possible blocks and models -> it will consume to much time/GPU power without much visible improvement.

thank you for your reporting!

@wkpark wkpark reopened this Mar 8, 2024
@wkpark
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wkpark commented Mar 8, 2024

and 2-days ago, the following fix apply, d0710bd

before this fix. merge process totally not work at all. please check your version before try to use auto merger

@Enferlain
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mbw mode with 7 hours? wow. I didn't do that much.

all possible optimizers are not tested yet. some optimizer won't work at all. other optimizer will work as expected. and image scoring method also important factor.

anyway, I guess, there are some bug exist to prevent it from working correctly.

I recommend you partial optimizing, for example:

  • select specific model - select only "A" model to optimize.
  • select specific blocks - select only "OUT00, OUT01, OUT03,..."

default setting will try to vary all possible blocks and models -> it will consume to much time/GPU power without much visible improvement.

thank you for your reporting!

Yeah I only tried bayesian and simulated annealing and pattern search so far. I also did a run with not specifying alpha values for any of the weights, in case it was locking them in somehow.

Another thing to note is that I usually get a result that says "best iteration: 0"

This was the 7 hour run: I set search time (min) to 200, and I also set search iteration to 200. I did it when I went to sleep

Results: 'hyper_score'
   Best score: 0.5472393854351669
   Best parameter set:
      'model_b.BASE'  : 0.58
      'model_b.IN00'  : 0.41
      'model_b.IN01'  : 0.42
      'model_b.IN02'  : 0.18
      'model_b.IN03'  : 0.54
      'model_b.IN04'  : 0.44
      'model_b.IN05'  : 0.1
      'model_b.IN06'  : 0.31
      'model_b.IN07'  : 0.23
      'model_b.IN08'  : 0.4
      'model_b.M00'   : 0.54
      'model_b.OUT00' : 0.28
      'model_b.OUT01' : 0.14
      'model_b.OUT02' : 0.21
      'model_b.OUT03' : 0.13
      'model_b.OUT04' : 0.61
      'model_b.OUT05' : 0.38
      'model_b.OUT06' : 0.55
      'model_b.OUT07' : 0.49
      'model_b.OUT08' : 0.57
      'model_c.BASE'  : 0.53
      'model_c.IN00'  : 0.53
      'model_c.IN01'  : 0.23
      'model_c.IN02'  : 0.24
      'model_c.IN03'  : 0.21
      'model_c.IN04'  : 0.55
      'model_c.IN05'  : 0.58
      'model_c.IN06'  : 0.17
      'model_c.IN07'  : 0.3
      'model_c.IN08'  : 0.46
      'model_c.M00'   : 0.41
      'model_c.OUT00' : 0.59
      'model_c.OUT01' : 0.55
      'model_c.OUT02' : 0.37
      'model_c.OUT03' : 0.59
      'model_c.OUT04' : 0.19
      'model_c.OUT05' : 0.34
      'model_c.OUT06' : 0.16
      'model_c.OUT07' : 0.14
      'model_c.OUT08' : 0.39
   Best iteration: 0

   Random seed: 876348280

   Evaluation time   : 26219.17984700203 sec    [100.0 %]
   Optimization time : 0.14667487144470215 sec    [0.0 %]
   Iteration time    : 26219.326521873474 sec    [120.27 sec/iter]

I'll try the last update, I forgot to pull it. Was on bb3808b

Anyways, it's a great extension and I really like the auto merger implementation. It's still the least explored part of merging even though it has so much potential.

@wkpark
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wkpark commented Mar 9, 2024

commit bb3808b was the regression bug. it prevents the merge from working properly.
(I guess, that's why it fails to auto merge)

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