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src/pipeline.py

@@ -11,7 +11,8 @@ from torch import Generator
 from torchao.quantization import quantize_, int8_weight_only
 from transformers import T5EncoderModel, CLIPTextModel, logging 
 import torch._dynamo
-torch._dynamo.config.suppress_errors = True
+import torch_tensorrt
+# torch._dynamo.config.suppress_errors = True
 
 Pipeline: TypeAlias = FluxPipeline
 
@@ -50,7 +51,7 @@ def load_pipeline() -> Pipeline:
     pipeline.transformer.to(memory_format=torch.channels_last)
     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, backend="tensorrt")
     
     PROMPT = 'semiconformity, peregrination, quip, twineless, emotionless, tawa, depickle'
     with torch.inference_mode():