Update app.py

app.py

@@ -108,7 +108,7 @@ def load_and_prepare_model(model_id):
     model_dtypes = {"ford442/RealVisXL_V5.0_BF16": torch.bfloat16,}
     dtype = model_dtypes.get(model_id, torch.bfloat16)  # Default to float32 if not found
     #vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", torch_dtype=torch.bfloat16,safety_checker=None)
-    vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",safety_checker=None)
+    vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",safety_checker=None).to(torch.bfloat16)
   #  vae = AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",safety_checker=None).to(torch.bfloat16)
     #  vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None).to('cuda')
     #sched = EulerAncestralDiscreteScheduler.from_config('ford442/Juggernaut-XI-v11-fp32', subfolder='scheduler',beta_schedule="scaled_linear",use_karras_sigmas=True)
@@ -145,7 +145,7 @@ def load_and_prepare_model(model_id):
     #pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.unet.to(torch.bfloat16)
     pipe.to(device)
-    pipe.to(torch.bfloat16)
+    #pipe.to(torch.bfloat16)
 
     #pipe.to(torch.device("cuda:0"))
     #pipe.vae.to(torch.bfloat16)
@@ -235,7 +235,7 @@ def generate_30(
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a custom before cuda \n")
-        f.write(f"Model VAE: default \n")
+        f.write(f"Model VAE: sdxl_vae to bfloat before cuda \n")
         f.write(f"Model UNET: default \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
@@ -301,7 +301,7 @@ def generate_60(
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a custom before cuda \n")
-        f.write(f"Model VAE: default \n")
+        f.write(f"Model VAE: sdxl_vae to bfloat before cuda \n")
         f.write(f"Model UNET: default \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
@@ -367,7 +367,7 @@ def generate_90(
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a custom before cuda \n")
-        f.write(f"Model VAE: default \n")
+        f.write(f"Model VAE: sdxl_vae to bfloat before cuda \n")
         f.write(f"Model UNET: default \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):