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Add scheduled eta and clamp_max #131

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Add scheduled eta and clamp_max #131

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4197dd6
Added eta evaluation
robobeebop Jul 18, 2022
2ff63dd
Add clamp_max evaluation and fix eta evaluation
robobeebop Jul 18, 2022
ed746e7
Fix type check: list to ndarray
robobeebop Jul 18, 2022
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15 changes: 8 additions & 7 deletions disco.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1331,8 +1331,9 @@ def do_run():
del init2

cur_t = None

t_int = 0
def cond_fn(x, t, y=None):
global t_int
with torch.enable_grad():
x_is_NaN = False
x = x.detach().requires_grad_()
Expand Down Expand Up @@ -1392,7 +1393,7 @@ def cond_fn(x, t, y=None):
grad = torch.zeros_like(x)
if args.clamp_grad and x_is_NaN == False:
magnitude = grad.square().mean().sqrt()
return grad * magnitude.clamp(max=args.clamp_max) / magnitude #min=-0.02, min=-clamp_max,
return grad * magnitude.clamp(max=args.clamp_max[1000-t_int] if type(args.clamp_max) is np.ndarray else args.clamp_max ) / magnitude #min=-0.02, min=-clamp_max,
return grad

if args.diffusion_sampling_mode == 'ddim':
Expand Down Expand Up @@ -1429,7 +1430,7 @@ def cond_fn(x, t, y=None):
skip_timesteps=skip_steps,
init_image=init,
randomize_class=randomize_class,
eta=eta,
eta=args.eta[1000-t_int] if type(args.eta) is np.ndarray else args.eta,
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really like this feature, can you provide a screenshot how it looks when this is intergrated?

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Here's the results: https://imgur.com/a/bVGj5Lc

And here's the link to the custom notebook with this feature implemented:
https://colab.research.google.com/drive/173sJy8VmXM8d9mUhjQcnEFr8WckpXIsc?usp=sharing

transformation_fn=symmetry_transformation_fn,
transformation_percent=args.transformation_percent
)
Expand Down Expand Up @@ -2772,9 +2773,9 @@ def warp(frame1, frame2, flo_path, blend=0.5, weights_path=None):
perlin_init = False #@param{type: 'boolean'}
perlin_mode = 'mixed' #@param ['mixed', 'color', 'gray']
set_seed = 'random_seed' #@param{type: 'string'}
eta = 0.8 #@param{type: 'number'}
eta = [0.9, 0.1] #@param
clamp_grad = True #@param{type: 'boolean'}
clamp_max = 0.05 #@param{type: 'number'}
clamp_max = [0.1, 0.04] #@param


### EXTRA ADVANCED SETTINGS:
Expand Down Expand Up @@ -3017,9 +3018,9 @@ def move_files(start_num, end_num, old_folder, new_folder):
'perlin_init': perlin_init,
'perlin_mode': perlin_mode,
'set_seed': set_seed,
'eta': eta,
'eta': np.linspace(eta[0], eta[1], cutn_batches) if type(eta) is list else eta,
'clamp_grad': clamp_grad,
'clamp_max': clamp_max,
'clamp_max': np.linspace(clamp_max[0], clamp_max[1], 1000) if type(clamp_max) is list else clamp_max,
'skip_augs': skip_augs,
'randomize_class': randomize_class,
'clip_denoised': clip_denoised,
Expand Down