Update app.py

app.py

@@ -106,7 +106,7 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
         negative = ""
     return p.replace("{prompt}", positive), n + negative
     
-unetX = UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='unet', low_cpu_mem_usage=False, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
+#unetX = UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='unet', low_cpu_mem_usage=False, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
 
 def load_and_prepare_model():
     vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False, low_cpu_mem_usage=False, torch_dtype=torch.float32, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
@@ -177,7 +177,7 @@ txt_tokenizer.tokenizer_legacy=False
 model = Phi3ForCausalLM.from_pretrained(checkpoint).to('cuda:0')
 #model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map='cuda') #.to('cuda')
 
-#ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
+ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
 text_encoder_1=CLIPTextModel.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='text_encoder',token=True) #.to(device=device, dtype=torch.bfloat16)
 text_encoder_2=CLIPTextModelWithProjection.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='text_encoder_2',token=True) #.to(device=device, dtype=torch.bfloat16)
    
@@ -449,11 +449,11 @@ def generate_30(
         torch.cuda.empty_cache()
         global text_encoder_1
         global text_encoder_2
-        global unetX
+        #global unetX
         pipe.text_encoder=text_encoder_1.to(device=device, dtype=torch.bfloat16)
         pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
-        pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
-        ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
+        #pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
+        #ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
         print('-- generating image --')
         sd_image = ip_model.generate(
                 pil_image_1=sd_image_a,
@@ -599,11 +599,11 @@ def generate_60(
         torch.cuda.empty_cache()
         global text_encoder_1
         global text_encoder_2
-        global unetX
+        #global unetX
         pipe.text_encoder=text_encoder_1.to(device=device, dtype=torch.bfloat16)
         pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
-        pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
-        ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
+        #pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
+        #ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
         print('-- generating image --')
         sd_image = ip_model.generate(
                 pil_image_1=sd_image_a,
@@ -750,11 +750,11 @@ def generate_90(
         torch.cuda.empty_cache()
         global text_encoder_1
         global text_encoder_2
-        global unetX
+        #global unetX
         pipe.text_encoder=text_encoder_1.to(device=device, dtype=torch.bfloat16)
         pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
-        pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
-        ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
+        #pipe.unet=unetX.to(device=device, dtype=torch.bfloat16)
+        #ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
         print('-- generating image --')
         sd_image = ip_model.generate(
                 pil_image_1=sd_image_a,