ENH: Improve speed of function expanding LoRA scales (huggingface#11834)

* ENH Improve speed of expanding LoRA scales

Resolves huggingface#11816

The following call proved to be a bottleneck when setting a lot of LoRA
adapters in diffusers:

https://github.com/huggingface/diffusers/blob/cdaf84a708eadf17d731657f4be3fa39d09a12c0/src/diffusers/loaders/peft.py#L482

This is because we would repeatedly call unet.state_dict(), even though
in the standard case, it is not necessary:

https://github.com/huggingface/diffusers/blob/cdaf84a708eadf17d731657f4be3fa39d09a12c0/src/diffusers/loaders/unet_loader_utils.py#L55

This PR fixes this by deferring this call, so that it is only run when
it's necessary, not earlier.

* Small fix

---------

Co-authored-by: Sayak Paul <[email protected]>

Author: BenjaminBossan

src/diffusers/loaders/unet_loader_utils.py

@@ -14,6 +14,8 @@
 import copy
 from typing import TYPE_CHECKING, Dict, List, Union
 
+from torch import nn
+
 from ..utils import logging
 
 
@@ -52,7 +54,7 @@ def _maybe_expand_lora_scales(
             weight_for_adapter,
             blocks_with_transformer,
             transformer_per_block,
-            unet.state_dict(),
+            model=unet,
             default_scale=default_scale,
         )
         for weight_for_adapter in weight_scales
@@ -65,7 +67,7 @@ def _maybe_expand_lora_scales_for_one_adapter(
     scales: Union[float, Dict],
     blocks_with_transformer: Dict[str, int],
     transformer_per_block: Dict[str, int],
-    state_dict: None,
+    model: nn.Module,
     default_scale: float = 1.0,
 ):
     """
@@ -154,6 +156,7 @@ def _maybe_expand_lora_scales_for_one_adapter(
 
         del scales[updown]
 
+    state_dict = model.state_dict()
     for layer in scales.keys():
         if not any(_translate_into_actual_layer_name(layer) in module for module in state_dict.keys()):
             raise ValueError(