Update app.py

app.py

@@ -86,11 +86,7 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 text_encoder = CLIPTextModel.from_pretrained('ford442/RealVisXL_V5.0_BF16', low_cpu_mem_usage=False, subfolder='text_encoder', token=True)#.to(device=device, dtype=torch.bfloat16)
 text_encoder_2 = CLIPTextModelWithProjection.from_pretrained('ford442/RealVisXL_V5.0_BF16', low_cpu_mem_usage=False, subfolder='text_encoder_2',token=True)#.to(device=device, dtype=torch.bfloat16)
 def load_and_prepare_model():
-    proc=Attention(
-        upcast_attention=True,
-      #  upcast_softmax = True,
-        processor = AttnProcessor2_0
-    )
+    proc=Attention(query_dim=4, upcast_attention=True, upcast_softmax = True, processor = AttnProcessor2_0)
     tokenizer_1 = CLIPTokenizer.from_pretrained('ford442/RealVisXL_V5.0_BF16', low_cpu_mem_usage=False, subfolder='tokenizer', token=True)
     tokenizer_2 = CLIPTokenizer.from_pretrained('ford442/RealVisXL_V5.0_BF16', low_cpu_mem_usage=False, subfolder='tokenizer_2', token=True)
     scheduler = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', low_cpu_mem_usage=False, subfolder='scheduler', token=True)
@@ -123,7 +119,6 @@ def load_and_prepare_model():
     #pipe.unet.to(memory_format=torch.channels_last)
     pipe.to(device=device, dtype=torch.bfloat16)
     pipe.vae = vaeXL.to(device) #.to('cpu') #.to(torch.bfloat16)
-    pipe.unet.set_attn_processor(proc)
     pipe.vae.set_default_attn_processor()
     return pipe