diff options
| -rw-r--r-- | extensions-builtin/Lora/lora.py | 41 | ||||
| -rw-r--r-- | modules/sd_models.py | 3 | ||||
| -rw-r--r-- | modules/sd_models_xl.py | 1 |
3 files changed, 33 insertions, 12 deletions
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 03f1ef85..4b5da7b5 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -68,6 +68,14 @@ def convert_diffusers_name_to_compvis(key, is_sd2): return f"transformer_text_model_encoder_layers_{m[0]}_{m[1]}"
+ if match(m, r"lora_te2_text_model_encoder_layers_(\d+)_(.+)"):
+ if 'mlp_fc1' in m[1]:
+ return f"1_model_transformer_resblocks_{m[0]}_{m[1].replace('mlp_fc1', 'mlp_c_fc')}"
+ elif 'mlp_fc2' in m[1]:
+ return f"1_model_transformer_resblocks_{m[0]}_{m[1].replace('mlp_fc2', 'mlp_c_proj')}"
+ else:
+ return f"1_model_transformer_resblocks_{m[0]}_{m[1].replace('self_attn', 'attn')}"
+
return key
@@ -142,10 +150,20 @@ class LoraUpDownModule: def assign_lora_names_to_compvis_modules(sd_model):
lora_layer_mapping = {}
- for name, module in shared.sd_model.cond_stage_model.wrapped.named_modules():
- lora_name = name.replace(".", "_")
- lora_layer_mapping[lora_name] = module
- module.lora_layer_name = lora_name
+ if shared.sd_model.is_sdxl:
+ for i, embedder in enumerate(shared.sd_model.conditioner.embedders):
+ if not hasattr(embedder, 'wrapped'):
+ continue
+
+ for name, module in embedder.wrapped.named_modules():
+ lora_name = f'{i}_{name.replace(".", "_")}'
+ lora_layer_mapping[lora_name] = module
+ module.lora_layer_name = lora_name
+ else:
+ for name, module in shared.sd_model.cond_stage_model.wrapped.named_modules():
+ lora_name = name.replace(".", "_")
+ lora_layer_mapping[lora_name] = module
+ module.lora_layer_name = lora_name
for name, module in shared.sd_model.model.named_modules():
lora_name = name.replace(".", "_")
@@ -168,10 +186,10 @@ def load_lora(name, lora_on_disk): keys_failed_to_match = {}
is_sd2 = 'model_transformer_resblocks' in shared.sd_model.lora_layer_mapping
- for key_diffusers, weight in sd.items():
- key_diffusers_without_lora_parts, lora_key = key_diffusers.split(".", 1)
- key = convert_diffusers_name_to_compvis(key_diffusers_without_lora_parts, is_sd2)
+ for key_lora, weight in sd.items():
+ key_lora_without_lora_parts, lora_key = key_lora.split(".", 1)
+ key = convert_diffusers_name_to_compvis(key_lora_without_lora_parts, is_sd2)
sd_module = shared.sd_model.lora_layer_mapping.get(key, None)
if sd_module is None:
@@ -180,12 +198,15 @@ def load_lora(name, lora_on_disk): sd_module = shared.sd_model.lora_layer_mapping.get(m.group(1), None)
# SDXL loras seem to already have correct compvis keys, so only need to replace "lora_unet" with "diffusion_model"
- if sd_module is None and "lora_unet" in key_diffusers_without_lora_parts:
- key = key_diffusers_without_lora_parts.replace("lora_unet", "diffusion_model")
+ if sd_module is None and "lora_unet" in key_lora_without_lora_parts:
+ key = key_lora_without_lora_parts.replace("lora_unet", "diffusion_model")
+ sd_module = shared.sd_model.lora_layer_mapping.get(key, None)
+ elif sd_module is None and "lora_te1_text_model" in key_lora_without_lora_parts:
+ key = key_lora_without_lora_parts.replace("lora_te1_text_model", "0_transformer_text_model")
sd_module = shared.sd_model.lora_layer_mapping.get(key, None)
if sd_module is None:
- keys_failed_to_match[key_diffusers] = key
+ keys_failed_to_match[key_lora] = key
continue
lora_module = lora.modules.get(key, None)
diff --git a/modules/sd_models.py b/modules/sd_models.py index 9e8cb3cf..07702175 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -289,7 +289,8 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer if state_dict is None:
state_dict = get_checkpoint_state_dict(checkpoint_info, timer)
- if hasattr(model, 'conditioner'):
+ model.is_sdxl = hasattr(model, 'conditioner')
+ if model.is_sdxl:
sd_models_xl.extend_sdxl(model)
model.load_state_dict(state_dict, strict=False)
diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index af445a61..a7240dc0 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -48,7 +48,6 @@ def extend_sdxl(model): discretization = sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization()
model.alphas_cumprod = torch.asarray(discretization.alphas_cumprod, device=devices.device, dtype=dtype)
- model.is_sdxl = True
sgm.models.diffusion.DiffusionEngine.get_learned_conditioning = get_learned_conditioning
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