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[DoRA] Fix TypeError for LoRA config when use_dora is False in DreamBooth SDXL #9842

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[DoRA] Fix TypeError for LoRA config when use_dora is False in DreamBooth SDXL #9842

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31 changes: 21 additions & 10 deletions examples/dreambooth/train_dreambooth_lora_sdxl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1183,25 +1183,36 @@ def main(args):
text_encoder_one.gradient_checkpointing_enable()
text_encoder_two.gradient_checkpointing_enable()

def get_lora_config(rank, use_dora, target_modules):
base_config = {
"r": rank,
"lora_alpha": rank,
"init_lora_weights": "gaussian",
"target_modules": target_modules,
}

if use_dora:
base_config["use_dora"] = True
Comment on lines +1194 to +1195
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@sayakpaul sayakpaul Nov 2, 2024

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This would fail for lower version of peft where use_dora isn't present in the call args.

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@adhiiisetiawan adhiiisetiawan Nov 2, 2024

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Thanks for pointing that out! Could you clarify which version of peft lacks use_dora in the call args?

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@sayakpaul sayakpaul Nov 3, 2024

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diffusers/src/diffusers/loaders/peft.py

Line 220 in 13e8fde

if lora_config_kwargs["use_dora"] and is_peft_version("<", "0.9.0"):


return LoraConfig(**base_config)

# now we will add new LoRA weights to the attention layers
unet_lora_config = LoraConfig(
r=args.rank,
unet_target_modules = ["to_k", "to_q", "to_v", "to_out.0"]
unet_lora_config = get_lora_config(
rank=args.rank,
use_dora=args.use_dora,
lora_alpha=args.rank,
init_lora_weights="gaussian",
target_modules=["to_k", "to_q", "to_v", "to_out.0"],
target_modules=unet_target_modules
)
unet.add_adapter(unet_lora_config)

# The text encoder comes from 🤗 transformers, so we cannot directly modify it.
# So, instead, we monkey-patch the forward calls of its attention-blocks.
if args.train_text_encoder:
text_lora_config = LoraConfig(
r=args.rank,
text_target_modules = ["q_proj", "k_proj", "v_proj", "out_proj"]
text_lora_config = get_lora_config(
rank=args.rank,
use_dora=args.use_dora,
lora_alpha=args.rank,
init_lora_weights="gaussian",
target_modules=["q_proj", "k_proj", "v_proj", "out_proj"],
target_modules=text_target_modules
)
text_encoder_one.add_adapter(text_lora_config)
text_encoder_two.add_adapter(text_lora_config)
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