simplify ti loading

modules/processing_diffusers.py

@@ -3,6 +3,7 @@ import inspect
 import typing
 import torch
 import torchvision.transforms.functional as TF
+import diffusers
 import modules.devices as devices
 import modules.shared as shared
 import modules.sd_samplers as sd_samplers
@@ -15,12 +16,6 @@ from modules.processing import StableDiffusionProcessing
 import modules.prompt_parser_diffusers as prompt_parser_diffusers
 
 
-try:
-    import diffusers
-except Exception as ex:
-    shared.log.error(f'Failed to import diffusers: {ex}')
-
-
 def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_prompts):
     results = []
     if p.enable_hr and p.hr_upscaler != 'None' and p.denoising_strength > 0 and len(getattr(p, 'init_images', [])) == 0:
@@ -171,6 +166,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         return prompts, negative_prompts, prompts_2, negative_prompts_2
 
     def set_pipeline_args(model, prompts: list, negative_prompts: list, prompts_2: typing.Optional[list]=None, negative_prompts_2: typing.Optional[list]=None, desc:str='', **kwargs):
+        if hasattr(model, 'embedding_db'):
+            del model.embedding_db
         try:
             is_refiner = model.text_encoder.__class__.__name__ != 'CLIPTextModel'
         except Exception: