Update app.py

app.py

@@ -90,7 +90,7 @@ def load_and_prepare_model():
     vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
     #sched = EulerAncestralDiscreteScheduler.from_pretrained('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 = DPMSolverSDEScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler')
-    sched = EulerAncestralDiscreteScheduler.from_pretrained('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_pretrained('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_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
     pipe = StableDiffusionXLPipeline.from_pretrained(
         'ford442/RealVisXL_V5.0_BF16',
@@ -117,11 +117,11 @@ def load_and_prepare_model():
     
           # for compile
 hidet.option.parallel_build(True)
-hidet.option.parallel_tune(-1,2.0)
+hidet.option.parallel_tune(-1,4.0)
 torch._dynamo.config.suppress_errors = True
 torch._dynamo.disallow_in_graph(diffusers.models.attention.BasicTransformerBlock)
 # more search
-hidet.torch.dynamo_config.search_space(2)
+hidet.torch.dynamo_config.search_space(1)
 #hidet.torch.dynamo_config.dump_graph_ir("./local_graph")
 hidet.option.cache_dir("local_cache")
 # automatically transform the model to use float16 data type
@@ -131,6 +131,7 @@ hidet.torch.dynamo_config.use_fp16_reduction(True)
 # use tensorcore
 hidet.torch.dynamo_config.use_tensor_core()
 # Preload and compile both models
+hidet.torch.dynamo_config.steal_weights(False)
 
 pipe = load_and_prepare_model()