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Fix dora.

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comfyanonymous 2024-08-23 04:58:59 -04:00
parent 5d8bbb7281
commit 7df42b9a23
2 changed files with 20 additions and 21 deletions
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20
comfy/lora.py
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@ -327,6 +327,26 @@ def model_lora_keys_unet(model, key_map={}):
return key_map return key_map
def weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype):
dora_scale = comfy.model_management.cast_to_device(dora_scale, weight.device, intermediate_dtype)
lora_diff *= alpha
weight_calc = weight + lora_diff.type(weight.dtype)
weight_norm = (
weight_calc.transpose(0, 1)
.reshape(weight_calc.shape[1], -1)
.norm(dim=1, keepdim=True)
.reshape(weight_calc.shape[1], *[1] * (weight_calc.dim() - 1))
.transpose(0, 1)
)
weight_calc *= (dora_scale / weight_norm).type(weight.dtype)
if strength != 1.0:
weight_calc -= weight
weight += strength * (weight_calc)
else:
weight[:] = weight_calc
return weight
def calculate_weight(patches, weight, key, intermediate_dtype=torch.float32): def calculate_weight(patches, weight, key, intermediate_dtype=torch.float32):
for p in patches: for p in patches:
strength = p[0] strength = p[0]

21
comfy/model_patcher.py
View File

@ -31,27 +31,6 @@ import comfy.lora
from comfy.types import UnetWrapperFunction from comfy.types import UnetWrapperFunction
def weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype):
dora_scale = comfy.model_management.cast_to_device(dora_scale, weight.device, intermediate_dtype)
lora_diff *= alpha
weight_calc = weight + lora_diff.type(weight.dtype)
weight_norm = (
weight_calc.transpose(0, 1)
.reshape(weight_calc.shape[1], -1)
.norm(dim=1, keepdim=True)
.reshape(weight_calc.shape[1], *[1] * (weight_calc.dim() - 1))
.transpose(0, 1)
)
weight_calc *= (dora_scale / weight_norm).type(weight.dtype)
if strength != 1.0:
weight_calc -= weight
weight += strength * (weight_calc)
else:
weight[:] = weight_calc
return weight
def set_model_options_patch_replace(model_options, patch, name, block_name, number, transformer_index=None): def set_model_options_patch_replace(model_options, patch, name, block_name, number, transformer_index=None):
to = model_options["transformer_options"].copy() to = model_options["transformer_options"].copy()