up

optimization.py

@@ -23,6 +23,7 @@ P = ParamSpec("P")
 # See: https://github.com/huggingface/diffusers/blob/c052791b5fe29ce8a308bf63dda97aa205b729be/src/diffusers/pipelines/ltx/pipeline_ltx.py#L420
 TRANSFORMER_NUM_FRAMES_DIM = torch.export.Dim("seq_len", min=4680, max=4680)
 
+# Unused currently as I don't know how to make the best use of it for LTX.
 TRANSFORMER_DYNAMIC_SHAPES = {
     "hidden_states": {1: TRANSFORMER_NUM_FRAMES_DIM},
 }
@@ -55,7 +56,7 @@ def optimize_pipeline_(pipeline: Callable[P, Any], *args: P.args, **kwargs: P.kw
             pipeline(*args, **kwargs)
 
         dynamic_shapes = tree_map_only((torch.Tensor, bool), lambda t: None, call.kwargs)
-        dynamic_shapes |= TRANSFORMER_DYNAMIC_SHAPES
+        # dynamic_shapes |= TRANSFORMER_DYNAMIC_SHAPES
 
         quantize_(pipeline.transformer, Float8DynamicActivationFloat8WeightConfig())
 
@@ -94,7 +95,7 @@ def optimize_pipeline_(pipeline: Callable[P, Any], *args: P.args, **kwargs: P.kw
             mod=pipeline.transformer,
             args=call.args,
             kwargs=call.kwargs | {"hidden_states": hidden_states_portrait},
-            dynamic_shapes=dynamic_shapes,
+            ddynamic_shapes=dynamic_shapes,
         )
 
         compiled_landscape = aoti_compile(exported_landscape, INDUCTOR_CONFIGS)