fix zero

model_lib/moMA_generator.py

@@ -1,8 +1,7 @@
 import torch
 from model_lib.attention_processor import IPAttnProcessor, IPAttnProcessor_Self, get_mask_from_cross
-from diffusers import StableDiffusionPipeline, DDIMScheduler, AutoencoderKL
 import tqdm
-
+import diffusers
 
 def get_subject_idx(model,prompt,src_subject,device):
     tokenized_prompt = model.tokenizer(prompt,padding="max_length",max_length=model.tokenizer.model_max_length,truncation=True,return_tensors="pt",).to(device)
@@ -82,13 +81,13 @@ class MoMA_generator:
         self.args = args
         self.device = device
         
-        noise_scheduler = DDIMScheduler(num_train_timesteps=1000,beta_start=0.00085,beta_end=0.012,beta_schedule="scaled_linear",clip_sample=False,set_alpha_to_one=False,steps_offset=1,)
+        noise_scheduler = diffusers.DDIMScheduler(num_train_timesteps=1000,beta_start=0.00085,beta_end=0.012,beta_schedule="scaled_linear",clip_sample=False,set_alpha_to_one=False,steps_offset=1,)
         
         print('Loading VAE: stabilityai--sd-vae-ft-mse...')
-        vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse")
+        vae = diffusers.AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse")
         
         print('Loading StableDiffusion: Realistic_Vision...')
-        self.pipe = StableDiffusionPipeline.from_pretrained(
+        self.pipe = diffusers.StableDiffusionPipeline.from_pretrained(
             "SG161222/Realistic_Vision_V4.0_noVAE",
             torch_dtype=torch.float16,
             scheduler=noise_scheduler,