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src/pipeline.py

@@ -51,7 +51,7 @@ def load_pipeline() -> Pipeline:
     pipeline.transformer = torch.compile(pipeline.transformer, mode="max-autotune", fullgraph=True)
     pipeline.vae.to(memory_format=torch.channels_last)
     quantize_(pipeline.vae, int8_weight_only())
-    pipeline.vae = torch.compile(pipeline.vae, fullgraph=True, mode="max-autotune")
+    # pipeline.vae = torch.compile(pipeline.vae, fullgraph=True, mode="max-autotune")
     
     PROMPT = 'semiconformity, peregrination, quip, twineless, emotionless, tawa, depickle'
     with torch.inference_mode():