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Fix LCM LoRA SDXL distillation state dict loading and saving #14562

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Fix LCM LoRA SDXL distillation state dict loading and saving #14562

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9 changes: 3 additions & 6 deletions examples/consistency_distillation/train_lcm_distill_lora_sdxl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,6 @@
from diffusers.training_utils import cast_training_params, resolve_interpolation_mode
from diffusers.utils import (
check_min_version,
convert_state_dict_to_diffusers,
convert_unet_state_dict_to_peft,
is_wandb_available,
)
Expand Down Expand Up @@ -121,7 +120,7 @@ def log_validation(vae, args, accelerator, weight_dtype, step, unet=None, is_fin
if unet is None:
raise ValueError("Must provide a `unet` when doing intermediate validation.")
unet = accelerator.unwrap_model(unet)
state_dict = convert_state_dict_to_diffusers(get_peft_model_state_dict(unet))
state_dict = get_peft_model_state_dict(unet)
to_load = state_dict
else:
to_load = args.output_dir
Expand Down Expand Up @@ -888,9 +887,7 @@ def main(args):
def save_model_hook(models, weights, output_dir):
if accelerator.is_main_process:
unet_ = accelerator.unwrap_model(unet)
# also save the checkpoints in native `diffusers` format so that it can be easily
# be independently loaded via `load_lora_weights()`.
state_dict = convert_state_dict_to_diffusers(get_peft_model_state_dict(unet_))
state_dict = get_peft_model_state_dict(unet_)
StableDiffusionXLPipeline.save_lora_weights(output_dir, unet_lora_layers=state_dict)

for _, model in enumerate(models):
Expand Down Expand Up @@ -1442,7 +1439,7 @@ def compute_time_ids(original_size, crops_coords_top_left):
accelerator.wait_for_everyone()
if accelerator.is_main_process:
unet = accelerator.unwrap_model(unet)
unet_lora_state_dict = convert_state_dict_to_diffusers(get_peft_model_state_dict(unet))
unet_lora_state_dict = get_peft_model_state_dict(unet)
StableDiffusionXLPipeline.save_lora_weights(args.output_dir, unet_lora_layers=unet_lora_state_dict)

if args.push_to_hub:
Expand Down
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