torch.compile with dynamic=False (#185)

* torch.compile with dynamic=False

* fix compile repeated blocks

---------

Co-authored-by: Glaceon-Hyy <[email protected]>

Author: akaitsuki-ii

diffsynth_engine/pipelines/flux_image.py

@@ -573,7 +573,7 @@ def update_weights(self, state_dicts: FluxStateDicts) -> None:
         self.update_component(self.vae_encoder, state_dicts.vae, self.config.device, self.config.vae_dtype)
 
     def compile(self):
-        self.dit.compile_repeated_blocks(dynamic=True)
+        self.dit.compile_repeated_blocks()
 
     def load_loras(self, lora_list: List[Tuple[str, float]], fused: bool = True, save_original_weight: bool = False):
         assert self.config.tp_degree is None or self.config.tp_degree == 1, (

diffsynth_engine/pipelines/qwen_image.py

@@ -307,7 +307,7 @@ def update_weights(self, state_dicts: QwenImageStateDicts) -> None:
         self.update_component(self.vae, state_dicts.vae, self.config.device, self.config.vae_dtype)
 
     def compile(self):
-        self.dit.compile_repeated_blocks(dynamic=True)
+        self.dit.compile_repeated_blocks()
 
     def load_loras(self, lora_list: List[Tuple[str, float]], fused: bool = True, save_original_weight: bool = False):
         assert self.config.tp_degree is None or self.config.tp_degree == 1, (

diffsynth_engine/pipelines/wan_video.py

@@ -645,6 +645,6 @@ def _get_vae_type(vae_state_dict: Dict[str, torch.Tensor]) -> str:
         return vae_type
 
     def compile(self):
-        self.dit.compile_repeated_blocks(dynamic=True)
+        self.dit.compile_repeated_blocks()
         if self.dit2 is not None:
-            self.dit2.compile_repeated_blocks(dynamic=True)
+            self.dit2.compile_repeated_blocks()