Add SVD compile node

onediff_comfy_nodes/README.md

@@ -129,6 +129,18 @@ Omitting specific details here, the following workflow can be loaded and tested.
 
 ![](workflows/vae-graph-loader.png)
 
+
+### SVD Acceleration
+
+Similar to the usage of "Model Speedup" nodes, it's used to accelerate the Stable Video Diffusion (SVD) model, completing the acceleration of the text-to-video pipeline.
+
+Compatible with "Model Graph Loader" node and "Model Graph Saver" node.
+
+Omitting specific details here, the following workflow can be loaded and tested.
+
+![](workflows/text-to-video-speedup.png)
+
+
 ### Image Distinction Scanner
 
 The "Image Distinction Scanner" node is used to compare the differences between two images and visualize the resulting variances.

onediff_comfy_nodes/__init__.py

@@ -7,6 +7,7 @@
     VaeSpeedup,
     VaeGraphLoader,
     VaeGraphSaver,
+    SVDSpeedup,
 )
 from ._compare_node import CompareModel, ShowImageDiff
 
@@ -20,6 +21,7 @@
     "VaeSpeedup": VaeSpeedup,
     "VaeGraphSaver": VaeGraphSaver,
     "VaeGraphLoader": VaeGraphLoader,
+    "SVDSpeedup": SVDSpeedup,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -31,6 +33,7 @@
     "VaeSpeedup": "VAE Speedup",
     "VaeGraphLoader": "VAE Graph Loader",
     "VaeGraphSaver": "VAE Graph Saver",
+    "SVDSpeedup": "SVD Speedup",
 }
 
 if _USE_UNET_INT8:

onediff_comfy_nodes/_nodes.py

@@ -23,6 +23,7 @@
     "VaeSpeedup",
     "VaeGraphLoader",
     "VaeGraphSaver",
+    "SVDSpeedup",
 ]
 
 if not args.dont_upcast_attention:
@@ -151,6 +152,33 @@ def save_graph(self, samples, model, filename_prefix):
         return {}
 
 
+class SVDSpeedup:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "static_mode": (["enable", "disable"],),
+            },
+        }
+
+    RETURN_TYPES = ("MODEL",)
+    FUNCTION = "speedup"
+    CATEGORY = "OneDiff"
+
+    def speedup(self, model, static_mode):
+        from onediff.infer_compiler import oneflow_compile
+
+        use_graph = static_mode == "enable"
+
+        new_model = copy.deepcopy(model) 
+        new_model.model.diffusion_model = oneflow_compile(
+            new_model.model.diffusion_model, use_graph=use_graph
+        )
+
+        return (new_model,)
+
+
 class VaeSpeedup:
     @classmethod
     def INPUT_TYPES(s):