mirror of
https://github.com/invoke-ai/InvokeAI
synced 2025-07-25 12:55:55 +00:00
Add T2I-Adapter model to model-management.
This commit is contained in:
@ -53,6 +53,7 @@ class ModelType(str, Enum):
|
||||
TextualInversion = "embedding"
|
||||
IPAdapter = "ip_adapter"
|
||||
CLIPVision = "clip_vision"
|
||||
T2IAdapter = "t2i_adapter"
|
||||
|
||||
|
||||
class SubModelType(str, Enum):
|
||||
|
88
invokeai/backend/model_management/models/t2i_adapter.py
Normal file
88
invokeai/backend/model_management/models/t2i_adapter.py
Normal file
@ -0,0 +1,88 @@
|
||||
import os
|
||||
from enum import Enum
|
||||
from typing import Literal, Optional
|
||||
|
||||
import torch
|
||||
from diffusers import T2IAdapter
|
||||
|
||||
from invokeai.backend.model_management.models.base import (
|
||||
BaseModelType,
|
||||
EmptyConfigLoader,
|
||||
InvalidModelException,
|
||||
ModelBase,
|
||||
ModelConfigBase,
|
||||
ModelNotFoundException,
|
||||
ModelType,
|
||||
SubModelType,
|
||||
calc_model_size_by_data,
|
||||
calc_model_size_by_fs,
|
||||
classproperty,
|
||||
)
|
||||
|
||||
|
||||
class T2IAdapterModelFormat(str, Enum):
|
||||
Diffusers = "diffusers"
|
||||
|
||||
|
||||
class T2IAdapterModel(ModelBase):
|
||||
class DiffusersConfig(ModelConfigBase):
|
||||
model_format: Literal[T2IAdapterModelFormat.Diffusers]
|
||||
|
||||
def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
|
||||
assert model_type == ModelType.T2IAdapter
|
||||
super().__init__(model_path, base_model, model_type)
|
||||
|
||||
config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
|
||||
|
||||
model_class_name = config.get("_class_name", None)
|
||||
if model_class_name not in {"T2IAdapter"}:
|
||||
raise InvalidModelException(f"Invalid T2I-Adapter model. Unknown _class_name: '{model_class_name}'.")
|
||||
|
||||
self.model_class = self._hf_definition_to_type(["diffusers", model_class_name])
|
||||
self.model_size = calc_model_size_by_fs(self.model_path)
|
||||
|
||||
def get_size(self, child_type: Optional[SubModelType] = None):
|
||||
if child_type is not None:
|
||||
raise ValueError(f"T2I-Adapters do not have child models. Invalid child type: '{child_type}'.")
|
||||
return self.model_size
|
||||
|
||||
def get_model(
|
||||
self,
|
||||
torch_dtype: Optional[torch.dtype],
|
||||
child_type: Optional[SubModelType] = None,
|
||||
) -> T2IAdapter:
|
||||
if child_type is not None:
|
||||
raise ValueError(f"T2I-Adapters do not have child models. Invalid child type: '{child_type}'.")
|
||||
|
||||
model = None
|
||||
for variant in ["fp16", None]:
|
||||
try:
|
||||
model = self.model_class.from_pretrained(
|
||||
self.model_path,
|
||||
torch_dtype=torch_dtype,
|
||||
variant=variant,
|
||||
)
|
||||
break
|
||||
except Exception:
|
||||
pass
|
||||
if not model:
|
||||
raise ModelNotFoundException()
|
||||
|
||||
# Calculate a more accurate size after loading the model into memory.
|
||||
self.model_size = calc_model_size_by_data(model)
|
||||
return model
|
||||
|
||||
@classproperty
|
||||
def save_to_config(cls) -> bool:
|
||||
return False
|
||||
|
||||
@classmethod
|
||||
def detect_format(cls, path: str):
|
||||
if not os.path.exists(path):
|
||||
raise ModelNotFoundException(f"Model not found at '{path}'.")
|
||||
|
||||
if os.path.isdir(path):
|
||||
if os.path.exists(os.path.join(path, "config.json")):
|
||||
return T2IAdapterModelFormat.Diffusers
|
||||
|
||||
raise InvalidModelException(f"Unsupported T2I-Adapter format: '{path}'.")
|
Reference in New Issue
Block a user