Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

For loras/embeddings treat folders the same as single files

Browse Source
This commit is contained in:
Brandon Rising 2024-03-21 11:24:27 -04:00 committed by Brandon
parent bbecb99eb4
commit 18098cc4b9
1 changed files with 10 additions and 16 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
invokeai/backend/model_manager/probe.py
View File

@ -644,18 +644,15 @@ class VaeFolderProbe(FolderProbeBase):
return name
class TextualInversionFolderProbe(FolderProbeBase):
def get_format(self) -> ModelFormat:
return ModelFormat.EmbeddingFolder
def get_base_type(self) -> BaseModelType:
files = os.scandir(self.model_path)
class TextualInversionFolderProbe(TextualInversionCheckpointProbe):
def __init__(self, model_path: Path):
files = os.scandir(model_path)
files = [Path(f.path) for f in files if f.is_file() and f.name.endswith((".ckpt", ".pt", ".pth", ".bin", ".safetensors"))]
if len(files) != 1:
raise InvalidModelConfigException(
f"Unable to determine base type for {self.model_path}: expected exactly one valid model file, found {[f.name for f in files]}."
f"Unable to determine base type for {model_path}: expected exactly one valid model file, found {[f.name for f in files]}."
)
return TextualInversionCheckpointProbe(files.pop()).get_base_type()
super().__init__(model_path)
class ONNXFolderProbe(PipelineFolderProbe):
@ -701,19 +698,16 @@ class ControlNetFolderProbe(FolderProbeBase):
return base_model
class LoRAFolderProbe(FolderProbeBase):
def get_base_type(self) -> BaseModelType:
model_file = None
files = os.scandir(self.model_path)
class LoRAFolderProbe(LoRACheckpointProbe):
def __init__(self, model_path: Path):
files = os.scandir(model_path)
files = [Path(f.path) for f in files if f.is_file() and f.name.endswith((".bin", ".safetensors"))]
if len(files) != 1:
raise InvalidModelConfigException(
f"Unable to determine base type for {self.model_path}: expected exactly one valid model file, found {[f.name for f in files]}."
f"Unable to determine base type for lora {model_path}: expected exactly one valid model file, found {[f.name for f in files]}."
)
model_file = files.pop()
if not model_file:
raise InvalidModelConfigException("Unknown LoRA format encountered")
return LoRACheckpointProbe(model_file).get_base_type()
super().__init__(model_file)
class IPAdapterFolderProbe(FolderProbeBase):