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Add support for locon mid weights.

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comfyanonymous 2023-03-21 14:51:51 -04:00
parent 451447bd9f
commit cc309568e1
1 changed files with 10 additions and 1 deletions
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11
comfy/sd.py
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@ -129,12 +129,17 @@ def load_lora(path, to_load):
A_name = "{}.lora_up.weight".format(x)
B_name = "{}.lora_down.weight".format(x)
alpha_name = "{}.alpha".format(x)
mid_name = "{}.lora_mid.weight".format(x)
if A_name in lora.keys():
alpha = None
if alpha_name in lora.keys():
alpha = lora[alpha_name].item()
loaded_keys.add(alpha_name)
patch_dict[to_load[x]] = (lora[A_name], lora[B_name], alpha)
mid = None
if mid_name in lora.keys():
mid = lora[mid_name]
loaded_keys.add(mid_name)
patch_dict[to_load[x]] = (lora[A_name], lora[B_name], alpha, mid)
loaded_keys.add(A_name)
loaded_keys.add(B_name)
for x in lora.keys():
@ -279,6 +284,10 @@ class ModelPatcher:
mat2 = v[1]
if v[2] is not None:
alpha *= v[2] / mat2.shape[0]
if v[3] is not None:
#locon mid weights, hopefully the math is fine because I didn't properly test it
final_shape = [mat2.shape[1], mat2.shape[0], v[3].shape[2], v[3].shape[3]]
mat2 = torch.mm(mat2.transpose(0, 1).flatten(start_dim=1).float(), v[3].transpose(0, 1).flatten(start_dim=1).float()).reshape(final_shape).transpose(0, 1)
weight += (alpha * torch.mm(mat1.flatten(start_dim=1).float(), mat2.flatten(start_dim=1).float())).reshape(weight.shape).type(weight.dtype).to(weight.device)
return self.model
def unpatch_model(self):