Fixed same Load AnimateDiff Model output linked to two connected Apply AD Model nodes not working as intended

animatediff/model_injection.py

@@ -396,6 +396,15 @@ def load_motion_module_gen2(model_name: str, motion_model_settings: 'MotionModel
     return motion_model
 
 
+def create_fresh_motion_module(motion_model: MotionModelPatcher) -> MotionModelPatcher:
+    ad_wrapper = AnimateDiffModel(mm_state_dict=motion_model.model.state_dict(), mm_info=motion_model.model.mm_info)
+    ad_wrapper.to(comfy.model_management.unet_dtype())
+    ad_wrapper.to(comfy.model_management.unet_offload_device())
+    ad_wrapper.load_state_dict(motion_model.model.state_dict())
+    return MotionModelPatcher(model=ad_wrapper, load_device=comfy.model_management.get_torch_device(),
+                                      offload_device=comfy.model_management.unet_offload_device())
+
+
 def validate_model_compatibility_gen2(model: ModelPatcher, motion_model: MotionModelPatcher):
     # check that motion model is compatible with sd model
     model_sd_type = get_sd_model_type(model)

animatediff/nodes_gen2.py

@@ -9,7 +9,7 @@ from .logger import logger
 from .utils_model import BIGMAX, BetaSchedules, get_available_motion_loras, get_available_motion_models, get_motion_lora_path
 from .utils_motion import ADKeyframeGroup, ADKeyframe
 from .motion_lora import MotionLoraInfo, MotionLoraList
-from .model_injection import (InjectionParams, ModelPatcherAndInjector, MotionModelGroup, MotionModelPatcher, MotionModelSettings,
+from .model_injection import (InjectionParams, ModelPatcherAndInjector, MotionModelGroup, MotionModelPatcher, MotionModelSettings, create_fresh_motion_module,
                               load_motion_module, load_motion_module_gen2, load_motion_lora_as_patches, validate_model_compatibility_gen2)
 from .sample_settings import SampleSettings, SeedNoiseGeneration
 from .sampling import motion_sample_factory
@@ -103,6 +103,11 @@ class ApplyAnimateDiffModelNode:
             prev_m_models = MotionModelGroup()
         prev_m_models = prev_m_models.clone()
         motion_model = motion_model.clone()
+        # check if internal motion model already present in previous model - create new if so
+        for prev_model in prev_m_models.models:
+            if motion_model.model is prev_model.model:
+                # need to create new internal model based on same state_dict
+                motion_model = create_fresh_motion_module(motion_model)
         # apply motion model to loaded_mm
         if motion_lora is not None:
             for lora in motion_lora.loras: