Update app.py

app.py

@@ -116,7 +116,7 @@ def load_and_prepare_model(model_id):
     #sched = EulerAncestralDiscreteScheduler()
     #sched = EulerAncestralDiscreteScheduler.from_config('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)
       #  sched = EulerAncestralDiscreteScheduler.from_config('ford442/RealVisXL_V5.0_BF16', beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
-    pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",use_safetensors=True).to(torch.bfloat16)
+    pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",use_safetensors=True)
     
     #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
     pipe = StableDiffusionXLPipeline.from_pretrained(
@@ -131,19 +131,18 @@ def load_and_prepare_model(model_id):
      #  vae=AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",repo_type='model',safety_checker=None),
      #   vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None, torch_dtype=torch.float32),
        # vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None),
-        #vae=vae,
-       # unet=pipeX.unet,
-        scheduler = sched
+        vae=vae,
+        unet=pipeX.unet,
+        scheduler = sched,
       #  scheduler = EulerAncestralDiscreteScheduler.from_config(pipeX.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
         #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
     )
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
     #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.to('cuda')
-    pipe.watermark=None
-    pipe.safety_checker=None
+
     #pipe.scheduler = sched
-    pipe.unet=pipeX.unet
+    #pipe.unet=pipeX.unet
    # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
     #pipe.to(dtype=torch.bfloat16)
     #pipe.unet = pipeX.unet
@@ -154,7 +153,14 @@ def load_and_prepare_model(model_id):
     pipe.to(torch.bfloat16)
 
     #pipe.to(torch.bfloat16)
-
+    print(f'Pipeline: ')
+    print(f'_optional_components: {pipe._optional_components} ')
+    print(f'watermark: {pipe.watermark} ')
+    print(f'safety_checker: {pipe.safety_checker)
+    print(f'final_image_processor: {pipe.final_image_processor}')
+    print(f'feature_extractor: {pipe.feature_extractor}')
+    pipe.watermark=None
+    pipe.safety_checker=None  
     #pipe.to(torch.device("cuda:0"))
     #pipe.vae.to(torch.bfloat16)
     #pipe.to(device, torch.bfloat16)