Rename peft/ -> lora/

invokeai/app/invocations/compel.py

@@ -19,8 +19,8 @@ from invokeai.app.invocations.model import CLIPField
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import generate_ti_list
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.peft.lora import LoRAModelRaw
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ConditioningFieldData,

invokeai/app/invocations/denoise_latents.py

@@ -36,9 +36,9 @@ from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_manager import BaseModelType, ModelVariantType
 from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.peft.lora import LoRAModelRaw
 from invokeai.backend.stable_diffusion import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext, DenoiseInputs
 from invokeai.backend.stable_diffusion.diffusers_pipeline import (

invokeai/app/invocations/flux_denoise.py

@@ -29,8 +29,8 @@ from invokeai.backend.flux.sampling_utils import (
     pack,
     unpack,
 )
-from invokeai.backend.peft.lora import LoRAModelRaw
-from invokeai.backend.peft.peft_patcher import PeftPatcher
+from invokeai.backend.lora.lora import LoRAModelRaw
+from invokeai.backend.lora.peft_patcher import PeftPatcher
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import FLUXConditioningInfo
 from invokeai.backend.util.devices import TorchDevice

invokeai/app/invocations/tiled_multi_diffusion_denoise_latents.py

@@ -22,8 +22,8 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.model import UNetField
 from invokeai.app.invocations.primitives import LatentsOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.peft.lora import LoRAModelRaw
 from invokeai.backend.stable_diffusion.diffusers_pipeline import ControlNetData, PipelineIntermediateState
 from invokeai.backend.stable_diffusion.multi_diffusion_pipeline import (
     MultiDiffusionPipeline,

invokeai/backend/lora/conversions/flux_diffusers_lora_conversion_utils.py

@@ -2,11 +2,11 @@ from typing import Dict
 
 import torch
 
-from invokeai.backend.peft.layers.any_lora_layer import AnyLoRALayer
-from invokeai.backend.peft.layers.concatenated_lora_layer import ConcatenatedLoRALayer
-from invokeai.backend.peft.layers.lora_layer import LoRALayer
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
-from invokeai.backend.peft.lora import LoRAModelRaw
+from invokeai.backend.lora.layers.any_lora_layer import AnyLoRALayer
+from invokeai.backend.lora.layers.concatenated_lora_layer import ConcatenatedLoRALayer
+from invokeai.backend.lora.layers.lora_layer import LoRALayer
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.lora import LoRAModelRaw
 
 
 def is_state_dict_likely_in_flux_diffusers_format(state_dict: Dict[str, torch.Tensor]) -> bool:

invokeai/backend/lora/conversions/flux_kohya_lora_conversion_utils.py

@@ -3,9 +3,9 @@ from typing import Any, Dict, TypeVar
 
 import torch
 
-from invokeai.backend.peft.layers.any_lora_layer import AnyLoRALayer
-from invokeai.backend.peft.layers.utils import peft_layer_from_state_dict
-from invokeai.backend.peft.lora import LoRAModelRaw
+from invokeai.backend.lora.layers.any_lora_layer import AnyLoRALayer
+from invokeai.backend.lora.layers.utils import peft_layer_from_state_dict
+from invokeai.backend.lora.lora import LoRAModelRaw
 
 # A regex pattern that matches all of the keys in the Kohya FLUX LoRA format.
 # Example keys:

invokeai/backend/lora/conversions/sd_lora_conversion_utils.py

@@ -2,9 +2,9 @@ from typing import Dict
 
 import torch
 
-from invokeai.backend.peft.layers.any_lora_layer import AnyLoRALayer
-from invokeai.backend.peft.layers.utils import peft_layer_from_state_dict
-from invokeai.backend.peft.lora import LoRAModelRaw
+from invokeai.backend.lora.layers.any_lora_layer import AnyLoRALayer
+from invokeai.backend.lora.layers.utils import peft_layer_from_state_dict
+from invokeai.backend.lora.lora import LoRAModelRaw
 
 
 def lora_model_from_sd_state_dict(state_dict: Dict[str, torch.Tensor]) -> LoRAModelRaw:

invokeai/backend/lora/layers/any_lora_layer.py

@@ -0,0 +1,11 @@
+from typing import Union
+
+from invokeai.backend.lora.layers.concatenated_lora_layer import ConcatenatedLoRALayer
+from invokeai.backend.lora.layers.full_layer import FullLayer
+from invokeai.backend.lora.layers.ia3_layer import IA3Layer
+from invokeai.backend.lora.layers.loha_layer import LoHALayer
+from invokeai.backend.lora.layers.lokr_layer import LoKRLayer
+from invokeai.backend.lora.layers.lora_layer import LoRALayer
+from invokeai.backend.lora.layers.norm_layer import NormLayer
+
+AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer, NormLayer, ConcatenatedLoRALayer]

invokeai/backend/lora/layers/concatenated_lora_layer.py

@@ -2,7 +2,7 @@ from typing import List, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class ConcatenatedLoRALayer(LoRALayerBase):

invokeai/backend/lora/layers/full_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class FullLayer(LoRALayerBase):

invokeai/backend/lora/layers/ia3_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class IA3Layer(LoRALayerBase):

invokeai/backend/lora/layers/loha_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class LoHALayer(LoRALayerBase):

invokeai/backend/lora/layers/lokr_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class LoKRLayer(LoRALayerBase):

invokeai/backend/lora/layers/lora_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 # TODO: find and debug lora/locon with bias

invokeai/backend/lora/layers/norm_layer.py

@@ -2,7 +2,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.lora_layer_base import LoRALayerBase
+from invokeai.backend.lora.layers.lora_layer_base import LoRALayerBase
 
 
 class NormLayer(LoRALayerBase):

invokeai/backend/lora/layers/utils.py

@@ -2,13 +2,13 @@ from typing import Dict
 
 import torch
 
-from invokeai.backend.peft.layers.any_lora_layer import AnyLoRALayer
-from invokeai.backend.peft.layers.full_layer import FullLayer
-from invokeai.backend.peft.layers.ia3_layer import IA3Layer
-from invokeai.backend.peft.layers.loha_layer import LoHALayer
-from invokeai.backend.peft.layers.lokr_layer import LoKRLayer
-from invokeai.backend.peft.layers.lora_layer import LoRALayer
-from invokeai.backend.peft.layers.norm_layer import NormLayer
+from invokeai.backend.lora.layers.any_lora_layer import AnyLoRALayer
+from invokeai.backend.lora.layers.full_layer import FullLayer
+from invokeai.backend.lora.layers.ia3_layer import IA3Layer
+from invokeai.backend.lora.layers.loha_layer import LoHALayer
+from invokeai.backend.lora.layers.lokr_layer import LoKRLayer
+from invokeai.backend.lora.layers.lora_layer import LoRALayer
+from invokeai.backend.lora.layers.norm_layer import NormLayer
 
 
 def peft_layer_from_state_dict(layer_key: str, state_dict: Dict[str, torch.Tensor]) -> AnyLoRALayer:

invokeai/backend/lora/lora.py

@@ -3,7 +3,7 @@ from typing import Dict, Optional
 
 import torch
 
-from invokeai.backend.peft.layers.any_lora_layer import AnyLoRALayer
+from invokeai.backend.lora.layers.any_lora_layer import AnyLoRALayer
 from invokeai.backend.raw_model import RawModel
 
 

invokeai/backend/lora/peft_patcher.py

@@ -3,7 +3,7 @@ from typing import Dict, Iterator, Optional, Tuple
 
 import torch
 
-from invokeai.backend.peft.lora import LoRAModelRaw
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.original_weights_storage import OriginalWeightsStorage
 

invokeai/backend/model_manager/load/model_loaders/lora.py

@@ -9,6 +9,14 @@ import torch
 from safetensors.torch import load_file
 
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.lora.conversions.flux_diffusers_lora_conversion_utils import (
+    lora_model_from_flux_diffusers_state_dict,
+)
+from invokeai.backend.lora.conversions.flux_kohya_lora_conversion_utils import (
+    lora_model_from_flux_kohya_state_dict,
+)
+from invokeai.backend.lora.conversions.sd_lora_conversion_utils import lora_model_from_sd_state_dict
+from invokeai.backend.lora.conversions.sdxl_lora_conversion_utils import convert_sdxl_keys_to_diffusers_format
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
@@ -20,14 +28,6 @@ from invokeai.backend.model_manager import (
 from invokeai.backend.model_manager.load.load_default import ModelLoader
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
-from invokeai.backend.peft.conversions.flux_diffusers_lora_conversion_utils import (
-    lora_model_from_flux_diffusers_state_dict,
-)
-from invokeai.backend.peft.conversions.flux_kohya_lora_conversion_utils import (
-    lora_model_from_flux_kohya_state_dict,
-)
-from invokeai.backend.peft.conversions.sd_lora_conversion_utils import lora_model_from_sd_state_dict
-from invokeai.backend.peft.conversions.sdxl_lora_conversion_utils import convert_sdxl_keys_to_diffusers_format
 
 
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.LoRA, format=ModelFormat.Diffusers)

invokeai/backend/model_manager/load/model_util.py

@@ -15,9 +15,9 @@ from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import D
 from invokeai.backend.image_util.grounding_dino.grounding_dino_pipeline import GroundingDinoPipeline
 from invokeai.backend.image_util.segment_anything.segment_anything_pipeline import SegmentAnythingPipeline
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_manager.config import AnyModel
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
-from invokeai.backend.peft.lora import LoRAModelRaw
 from invokeai.backend.spandrel_image_to_image_model import SpandrelImageToImageModel
 from invokeai.backend.textual_inversion import TextualInversionModelRaw
 

invokeai/backend/model_manager/probe.py

@@ -10,6 +10,10 @@ from picklescan.scanner import scan_file_path
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.util.misc import uuid_string
+from invokeai.backend.lora.conversions.flux_diffusers_lora_conversion_utils import (
+    is_state_dict_likely_in_flux_diffusers_format,
+)
+from invokeai.backend.lora.conversions.flux_kohya_lora_conversion_utils import is_state_dict_likely_in_flux_kohya_format
 from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS, ModelHash
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
@@ -26,10 +30,6 @@ from invokeai.backend.model_manager.config import (
     SchedulerPredictionType,
 )
 from invokeai.backend.model_manager.util.model_util import lora_token_vector_length, read_checkpoint_meta
-from invokeai.backend.peft.conversions.flux_diffusers_lora_conversion_utils import (
-    is_state_dict_likely_in_flux_diffusers_format,
-)
-from invokeai.backend.peft.conversions.flux_kohya_lora_conversion_utils import is_state_dict_likely_in_flux_kohya_format
 from invokeai.backend.spandrel_image_to_image_model import SpandrelImageToImageModel
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 

invokeai/backend/model_patcher.py

@@ -13,10 +13,10 @@ from diffusers import OnnxRuntimeModel, UNet2DConditionModel
 from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
 
 from invokeai.app.shared.models import FreeUConfig
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_manager import AnyModel
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
-from invokeai.backend.peft.lora import LoRAModelRaw
 from invokeai.backend.stable_diffusion.extensions.lora import LoRAExt
 from invokeai.backend.textual_inversion import TextualInversionManager, TextualInversionModelRaw
 from invokeai.backend.util.original_weights_storage import OriginalWeightsStorage

invokeai/backend/peft/layers/any_lora_layer.py

@@ -1,11 +0,0 @@
-from typing import Union
-
-from invokeai.backend.peft.layers.concatenated_lora_layer import ConcatenatedLoRALayer
-from invokeai.backend.peft.layers.full_layer import FullLayer
-from invokeai.backend.peft.layers.ia3_layer import IA3Layer
-from invokeai.backend.peft.layers.loha_layer import LoHALayer
-from invokeai.backend.peft.layers.lokr_layer import LoKRLayer
-from invokeai.backend.peft.layers.lora_layer import LoRALayer
-from invokeai.backend.peft.layers.norm_layer import NormLayer
-
-AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer, NormLayer, ConcatenatedLoRALayer]

invokeai/backend/stable_diffusion/extensions/lora.py

@@ -12,7 +12,7 @@ from invokeai.backend.util.devices import TorchDevice
 if TYPE_CHECKING:
     from invokeai.app.invocations.model import ModelIdentifierField
     from invokeai.app.services.shared.invocation_context import InvocationContext
-    from invokeai.backend.peft.lora import LoRAModelRaw
+    from invokeai.backend.lora.lora import LoRAModelRaw
     from invokeai.backend.util.original_weights_storage import OriginalWeightsStorage
 
 

tests/backend/lora/conversions/test_flux_diffusers_lora_conversion_utils.py

@@ -1,7 +1,7 @@
 import pytest
 import torch
 
-from invokeai.backend.peft.conversions.flux_diffusers_lora_conversion_utils import (
+from invokeai.backend.lora.conversions.flux_diffusers_lora_conversion_utils import (
     is_state_dict_likely_in_flux_diffusers_format,
     lora_model_from_flux_diffusers_state_dict,
 )

tests/backend/lora/conversions/test_flux_kohya_lora_conversion_utils.py

@@ -3,7 +3,7 @@ import torch
 
 from invokeai.backend.flux.model import Flux
 from invokeai.backend.flux.util import params
-from invokeai.backend.peft.conversions.flux_kohya_lora_conversion_utils import (
+from invokeai.backend.lora.conversions.flux_kohya_lora_conversion_utils import (
     convert_flux_kohya_state_dict_to_invoke_format,
     is_state_dict_likely_in_flux_kohya_format,
     lora_model_from_flux_kohya_state_dict,

tests/backend/model_manager/test_lora.py

@@ -1,9 +1,9 @@
 import pytest
 import torch
 
+from invokeai.backend.lora.layers.lora_layer import LoRALayer
+from invokeai.backend.lora.lora import LoRAModelRaw
 from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.peft.layers.lora_layer import LoRALayer
-from invokeai.backend.peft.lora import LoRAModelRaw
 
 
 @pytest.mark.parametrize(