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Added lcm avg(sqrt_linear,linear) beta_schedule for testing

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Jedrzej Kosinski
2024-02-05 10:22:31 -06:00
parent 1b12d3b09d
commit 3167dd882d
1 changed files with 11 additions and 4 deletions
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animatediff/utils_model.py
+11 -4
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@@ -75,6 +75,7 @@ class BetaSchedules:
LINEAR_ADXL = "linear (AnimateDiff-SDXL)"
LINEAR = "linear (HotshotXL/default)"
AVG_LINEAR_SQRT_LINEAR = "avg(sqrt_linear,linear)"
LCM_AVG_LINEAR_SQRT_LINEAR = "lcm avg(sqrt_linear,linear)"
LCM = "lcm"
LCM_100 = "lcm[100_ots]"
LCM_25 = "lcm[25_ots]"
@@ -86,7 +87,7 @@ class BetaSchedules:
LCM_LIST = [LCM, LCM_100, LCM_25, LCM_SQRT_LINEAR]
ALIAS_LIST = [AUTOSELECT, USE_EXISTING, SQRT_LINEAR, LINEAR_ADXL, LINEAR, AVG_LINEAR_SQRT_LINEAR, LCM, LCM_100, LCM_SQRT_LINEAR, # LCM_25 is purposely omitted
ALIAS_LIST = [AUTOSELECT, USE_EXISTING, SQRT_LINEAR, LINEAR_ADXL, LINEAR, AVG_LINEAR_SQRT_LINEAR, LCM_AVG_LINEAR_SQRT_LINEAR, LCM, LCM_100, LCM_SQRT_LINEAR, # LCM_25 is purposely omitted
SQRT, COSINE, SQUAREDCOS_CAP_V2]
ALIAS_MAP = {
@@ -123,9 +124,15 @@ class BetaSchedules:
def to_model_sampling(cls, alias: str, model: ModelPatcher):
if alias == cls.USE_EXISTING:
return None
if alias == cls.AVG_LINEAR_SQRT_LINEAR:
ms_linear = evolved_model_sampling(cls.to_config(cls.LINEAR), model_type=model.model.model_type, alias=alias)
ms_sqrt_linear = evolved_model_sampling(cls.to_config(cls.SQRT_LINEAR), model_type=model.model.model_type, alias=alias)
elif alias == cls.AVG_LINEAR_SQRT_LINEAR:
ms_linear = evolved_model_sampling(cls.to_config(cls.LINEAR), model_type=model.model.model_type, alias=cls.LINEAR)
ms_sqrt_linear = evolved_model_sampling(cls.to_config(cls.SQRT_LINEAR), model_type=model.model.model_type, alias=cls.SQRT_LINEAR)
avg_sigmas = (ms_linear.sigmas + ms_sqrt_linear.sigmas) / 2
ms_linear.set_sigmas(avg_sigmas)
return ms_linear
elif alias == cls.LCM_AVG_LINEAR_SQRT_LINEAR:
ms_linear = evolved_model_sampling(cls.to_config(cls.LCM), model_type=model.model.model_type, alias=cls.LCM)
ms_sqrt_linear = evolved_model_sampling(cls.to_config(cls.LCM_SQRT_LINEAR), model_type=model.model.model_type, alias=cls.LCM_SQRT_LINEAR)
avg_sigmas = (ms_linear.sigmas + ms_sqrt_linear.sigmas) / 2
ms_linear.set_sigmas(avg_sigmas)
return ms_linear