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update presets #39

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update presets #39

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10 changes: 5 additions & 5 deletions lib_free_u/global_state.py
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Original file line number Diff line number Diff line change
Expand Up @@ -143,22 +143,22 @@ def apply_xyz():
default_presets = {
"SD1.4 Recommendations": State(
stage_infos=[
StageInfo(1.2, 0.9),
StageInfo(1.3, 0.9),
StageInfo(1.4, 0.2),
StageInfo(1, 1),
],
),
"SD2.1 Recommendations": State(
stage_infos=[
StageInfo(1.1, 0.9),
StageInfo(1.2, 0.2),
StageInfo(1.4, 0.9),
StageInfo(1.6, 0.2),
StageInfo(1, 1),
],
),
"SDXL Recommendations": State(
stage_infos=[
StageInfo(1.1, 0.6),
StageInfo(1.2, 0.4),
StageInfo(1.3, 0.9),
StageInfo(1.4, 0.2),
StageInfo(1, 1),
],
),
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8 changes: 4 additions & 4 deletions lib_free_u/unet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ def free_u_cat_hijack(hs, *args, original_function, **kwargs):

h[:, mask] *= get_backbone_scale(
h,
backbone_factor=lerp(1, stage_info.backbone_factor, schedule_ratio),
base_scale=lerp(1, stage_info.backbone_factor, schedule_ratio),
)
h_skip = filter_skip(
h_skip,
Expand All @@ -74,17 +74,17 @@ def free_u_cat_hijack(hs, *args, original_function, **kwargs):
return original_function([h, h_skip], *args, **kwargs)


def get_backbone_scale(h, backbone_factor):
def get_backbone_scale(h, base_scale):
if global_state.instance.version == "1":
return backbone_factor
return base_scale

#if global_state.instance.version == "2":
features_mean = h.mean(1, keepdim=True)
batch_dims = h.shape[0]
features_max, _ = torch.max(features_mean.view(batch_dims, -1), dim=-1, keepdim=True)
features_min, _ = torch.min(features_mean.view(batch_dims, -1), dim=-1, keepdim=True)
hidden_mean = (features_mean - features_min.unsqueeze(2).unsqueeze(3)) / (features_max - features_min).unsqueeze(2).unsqueeze(3)
return 1 + (backbone_factor - 1) * hidden_mean
return 1 + (base_scale - 1) * hidden_mean


def filter_skip(x, threshold, scale, scale_high):
Expand Down