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Feature/ Better LoRA : Dropout, Conv2d #133

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Merged
Parent: v0.1.8
merged 8 commits into from
Jan 15, 2023
Merged

Feature/ Better LoRA : Dropout, Conv2d #133

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e19f6ae
Merge pull request #130 from cloneofsimo/develop
cloneofsimo Jan 9, 2023
7bb97a3
feat : adds conv2d support
cloneofsimo Jan 13, 2023
5062fd4
conv2d as extended target replace on PTI
cloneofsimo Jan 13, 2023
7dca434
git update
cloneofsimo Jan 13, 2023
204d6ed
scale conv2d as well
cloneofsimo Jan 14, 2023
583b1e7
adds dropout
cloneofsimo Jan 14, 2023
4e2612b
minor bug fix
cloneofsimo Jan 15, 2023
770b97a
version up
cloneofsimo Jan 15, 2023
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2 changes: 1 addition & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -5,5 +5,5 @@ __pycache__
__test*
merged_lora*
wandb
exps
exps*
.vscode
32 changes: 27 additions & 5 deletions lora_diffusion/cli_lora_pti.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,11 +36,13 @@
PivotalTuningDatasetCapation,
extract_lora_ups_down,
inject_trainable_lora,
inject_trainable_lora_extended,
inspect_lora,
save_lora_weight,
save_all,
prepare_clip_model_sets,
evaluate_pipe,
UNET_EXTENDED_TARGET_REPLACE,
)


Expand Down Expand Up @@ -418,6 +420,8 @@ def perform_tuning(
placeholder_tokens,
save_path,
lr_scheduler_lora,
lora_unet_target_modules,
lora_clip_target_modules,
):

progress_bar = tqdm(range(num_steps))
Expand Down Expand Up @@ -467,6 +471,8 @@ def perform_tuning(
save_path=os.path.join(
save_path, f"step_{global_step}.safetensors"
),
target_replace_module_text=lora_clip_target_modules,
target_replace_module_unet=lora_unet_target_modules,
)
moved = (
torch.tensor(list(itertools.chain(*inspect_lora(unet).values())))
Expand Down Expand Up @@ -521,11 +527,12 @@ def train(
lora_rank: int = 4,
lora_unet_target_modules={"CrossAttention", "Attention", "GEGLU"},
lora_clip_target_modules={"CLIPAttention"},
use_extended_lora: bool = False,
clip_ti_decay: bool = True,
learning_rate_unet: float = 1e-4,
learning_rate_text: float = 1e-5,
learning_rate_ti: float = 5e-4,
continue_inversion: bool = True,
continue_inversion: bool = False,
continue_inversion_lr: Optional[float] = None,
use_face_segmentation_condition: bool = False,
scale_lr: bool = False,
Expand Down Expand Up @@ -690,9 +697,21 @@ def train(
del ti_optimizer

# Next perform Tuning with LoRA:
unet_lora_params, _ = inject_trainable_lora(
unet, r=lora_rank, target_replace_module=lora_unet_target_modules
)
if not use_extended_lora:
unet_lora_params, _ = inject_trainable_lora(
unet, r=lora_rank, target_replace_module=lora_unet_target_modules
)
else:
print("USING EXTENDED UNET!!!")
lora_unet_target_modules = (
lora_unet_target_modules | UNET_EXTENDED_TARGET_REPLACE
)
print("Will replace modules: ", lora_unet_target_modules)

unet_lora_params, _ = inject_trainable_lora_extended(
unet, r=lora_rank, target_replace_module=lora_unet_target_modules
)
print(f"PTI : has {len(unet_lora_params)} lora")

print("Before training:")
inspect_lora(unet)
Expand Down Expand Up @@ -720,7 +739,8 @@ def train(
)
for param in params_to_freeze:
param.requires_grad = False

else:
text_encoder.requires_grad_(False)
if train_text_encoder:
text_encoder_lora_params, _ = inject_trainable_lora(
text_encoder,
Expand Down Expand Up @@ -763,6 +783,8 @@ def train(
placeholder_token_ids=placeholder_token_ids,
save_path=output_dir,
lr_scheduler_lora=lr_scheduler_lora,
lora_unet_target_modules=lora_unet_target_modules,
lora_clip_target_modules=lora_clip_target_modules,
)


Expand Down
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