Add a way to set which range of timesteps the cond gets applied to.
This commit is contained in:
parent
30de083dd0
commit
0240946ecf
|
@ -17,6 +17,14 @@ def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, con
|
|||
def get_area_and_mult(cond, x_in, cond_concat_in, timestep_in):
|
||||
area = (x_in.shape[2], x_in.shape[3], 0, 0)
|
||||
strength = 1.0
|
||||
if 'timestep_start' in cond[1]:
|
||||
timestep_start = cond[1]['timestep_start']
|
||||
if timestep_in > timestep_start:
|
||||
return None
|
||||
if 'timestep_end' in cond[1]:
|
||||
timestep_end = cond[1]['timestep_end']
|
||||
if timestep_in < timestep_end:
|
||||
return None
|
||||
if 'area' in cond[1]:
|
||||
area = cond[1]['area']
|
||||
if 'strength' in cond[1]:
|
||||
|
@ -428,6 +436,25 @@ def create_cond_with_same_area_if_none(conds, c):
|
|||
n = c[1].copy()
|
||||
conds += [[smallest[0], n]]
|
||||
|
||||
def calculate_start_end_timesteps(model, conds):
|
||||
for t in range(len(conds)):
|
||||
x = conds[t]
|
||||
|
||||
timestep_start = None
|
||||
timestep_end = None
|
||||
if 'start_percent' in x[1]:
|
||||
timestep_start = model.sigma_to_t(model.t_to_sigma(torch.tensor(x[1]['start_percent'] * 999.0)))
|
||||
if 'end_percent' in x[1]:
|
||||
timestep_end = model.sigma_to_t(model.t_to_sigma(torch.tensor(x[1]['end_percent'] * 999.0)))
|
||||
|
||||
if (timestep_start is not None) or (timestep_end is not None):
|
||||
n = x[1].copy()
|
||||
if (timestep_start is not None):
|
||||
n['timestep_start'] = timestep_start
|
||||
if (timestep_end is not None):
|
||||
n['timestep_end'] = timestep_end
|
||||
conds[t] = [x[0], n]
|
||||
|
||||
def apply_empty_x_to_equal_area(conds, uncond, name, uncond_fill_func):
|
||||
cond_cnets = []
|
||||
cond_other = []
|
||||
|
@ -571,6 +598,9 @@ class KSampler:
|
|||
resolve_cond_masks(positive, noise.shape[2], noise.shape[3], self.device)
|
||||
resolve_cond_masks(negative, noise.shape[2], noise.shape[3], self.device)
|
||||
|
||||
calculate_start_end_timesteps(self.model_wrap, negative)
|
||||
calculate_start_end_timesteps(self.model_wrap, positive)
|
||||
|
||||
#make sure each cond area has an opposite one with the same area
|
||||
for c in positive:
|
||||
create_cond_with_same_area_if_none(negative, c)
|
||||
|
|
23
nodes.py
23
nodes.py
|
@ -204,6 +204,28 @@ class ConditioningZeroOut:
|
|||
c.append(n)
|
||||
return (c, )
|
||||
|
||||
class ConditioningSetTimestepRange:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {"conditioning": ("CONDITIONING", ),
|
||||
"start": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
|
||||
"end": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001})
|
||||
}}
|
||||
RETURN_TYPES = ("CONDITIONING",)
|
||||
FUNCTION = "set_range"
|
||||
|
||||
CATEGORY = "advanced/conditioning"
|
||||
|
||||
def set_range(self, conditioning, start, end):
|
||||
c = []
|
||||
for t in conditioning:
|
||||
d = t[1].copy()
|
||||
d['start_percent'] = start
|
||||
d['end_percent'] = end
|
||||
n = [t[0], d]
|
||||
c.append(n)
|
||||
return (c, )
|
||||
|
||||
class VAEDecode:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
|
@ -1444,6 +1466,7 @@ NODE_CLASS_MAPPINGS = {
|
|||
"SaveLatent": SaveLatent,
|
||||
|
||||
"ConditioningZeroOut": ConditioningZeroOut,
|
||||
"ConditioningSetTimestepRange": ConditioningSetTimestepRange,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
|
|
Loading…
Reference in New Issue