Update src/pipeline.py

src/pipeline.py

@@ -33,9 +33,12 @@ def load_pipeline(pipeline=None) -> StableDiffusionXLPipeline:
     load_pipe(pipeline, dir="/home/sandbox/.cache/huggingface/hub/models--RobertML--cached-pipe-02/snapshots/58d70deae87034cce351b780b48841f9746d4ad7")
 
     instance = get_instance(device)
-    mul = torch.nn.Parameter(torch.tensor(0.3038, requires_grad=False, device=device))
-    sub = torch.nn.Parameter(torch.tensor(-0.3141, requires_grad=False, device=device))
-    scaling_factor = torch.nn.Parameter(torch.tensor(0.5439, requires_grad=False, device=device))
+    # mul = torch.nn.Parameter(torch.tensor(0.3038, requires_grad=False, device=device))
+    # sub = torch.nn.Parameter(torch.tensor(-0.3141, requires_grad=False, device=device))
+    # scaling_factor = torch.nn.Parameter(torch.tensor(0.5439, requires_grad=False, device=device))
+    mul = torch.nn.Parameter(torch.tensor(0.2940097749233246, requires_grad=False, device=device))
+    sub = torch.nn.Parameter(torch.tensor(-0.31909096240997314, requires_grad=False, device=device))
+    scaling_factor = torch.nn.Parameter(torch.tensor(0.554410457611084, requires_grad=False, device=device))
     hook_pipe(pipeline, instance, mul, sub, scaling_factor)
 
     for _ in range(1):
@@ -66,55 +69,4 @@ def infer(request: TextToImageRequest, pipeline: StableDiffusionXLPipeline) -> I
         guidance_rescale = 0.0,
         callback_on_step_end=callback_dynamic_cfg,
         callback_on_step_end_tensor_inputs=['prompt_embeds', 'add_text_embeds', 'add_time_ids'],
-    ).images[0]
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+    ).images[0]