Replace util.get_attr with ModelPatcher.get_model_object (#120)

lib_layerdiffusion/attention_sharing.py

@@ -4,8 +4,9 @@ import functools
 import torch
 import einops
 
-from comfy import model_management, utils
+from comfy import model_management
 from comfy.ldm.modules.attention import optimized_attention
+from comfy.model_patcher import ModelPatcher
 
 
 module_mapping_sd15 = {
@@ -324,53 +325,19 @@ class HookerLayers(torch.nn.Module):
         self.layers = torch.nn.ModuleList(layer_list)
 
 
-def unload_model_clones(model, unload_weights_only=True, force_unload=True):
-    current_loaded_models = model_management.current_loaded_models
-
-    to_unload = []
-    for i, m in enumerate(current_loaded_models):
-        if model.is_clone(m.model):
-            to_unload = [i] + to_unload
-
-    if len(to_unload) == 0:
-        return True
-
-    same_weights = 0
-    for i in to_unload:
-        if model.clone_has_same_weights(current_loaded_models[i].model):
-            same_weights += 1
-
-    if same_weights == len(to_unload):
-        unload_weight = False
-    else:
-        unload_weight = True
-
-    if not force_unload:
-        if unload_weights_only and unload_weight is False:
-            return None
-    else:
-        unload_weight = True
-
-    for i in to_unload:
-        current_loaded_models.pop(i).model_unload(unpatch_weights=unload_weight)
-
-    return unload_weight
-
-
 class AttentionSharingPatcher(torch.nn.Module):
-    def __init__(self, unet, frames=2, use_control=True, rank=256):
+    def __init__(self, unet: ModelPatcher, frames=2, use_control=True, rank=256):
         super().__init__()
-        unload_model_clones(unet)
 
         units = []
         for i in range(32):
-            real_key = module_mapping_sd15[i]
-            attn_module = utils.get_attr(unet.model.diffusion_model, real_key)
+            key = "diffusion_model." + module_mapping_sd15[i]
+            attn_module = unet.get_model_object(key)
             u = AttentionSharingUnit(
                 attn_module, frames=frames, use_control=use_control, rank=rank
             )
             units.append(u)
-            unet.add_object_patch("diffusion_model." + real_key, u)
+            unet.add_object_patch(key, u)
 
         self.hookers = HookerLayers(units)