mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
import os
|
|
import torch
|
|
from enum import Enum
|
|
from pathlib import Path
|
|
from typing import Optional, Union, Literal
|
|
from .base import (
|
|
ModelBase,
|
|
ModelConfigBase,
|
|
BaseModelType,
|
|
ModelType,
|
|
SubModelType,
|
|
EmptyConfigLoader,
|
|
calc_model_size_by_fs,
|
|
calc_model_size_by_data,
|
|
classproperty,
|
|
)
|
|
|
|
class ControlNetModelFormat(str, Enum):
|
|
Checkpoint = "checkpoint"
|
|
Diffusers = "diffusers"
|
|
|
|
class ControlNetModel(ModelBase):
|
|
#model_class: Type
|
|
#model_size: int
|
|
|
|
class Config(ModelConfigBase):
|
|
model_format: ControlNetModelFormat
|
|
|
|
def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
|
|
assert model_type == ModelType.ControlNet
|
|
super().__init__(model_path, base_model, model_type)
|
|
|
|
try:
|
|
config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
|
|
#config = json.loads(os.path.join(self.model_path, "config.json"))
|
|
except:
|
|
raise Exception("Invalid controlnet model! (config.json not found or invalid)")
|
|
|
|
model_class_name = config.get("_class_name", None)
|
|
if model_class_name not in {"ControlNetModel"}:
|
|
raise Exception(f"Invalid ControlNet model! Unknown _class_name: {model_class_name}")
|
|
|
|
try:
|
|
self.model_class = self._hf_definition_to_type(["diffusers", model_class_name])
|
|
self.model_size = calc_model_size_by_fs(self.model_path)
|
|
except:
|
|
raise Exception("Invalid ControlNet model!")
|
|
|
|
def get_size(self, child_type: Optional[SubModelType] = None):
|
|
if child_type is not None:
|
|
raise Exception("There is no child models in controlnet model")
|
|
return self.model_size
|
|
|
|
def get_model(
|
|
self,
|
|
torch_dtype: Optional[torch.dtype],
|
|
child_type: Optional[SubModelType] = None,
|
|
):
|
|
if child_type is not None:
|
|
raise Exception("There is no child models in controlnet model")
|
|
|
|
model = self.model_class.from_pretrained(
|
|
self.model_path,
|
|
torch_dtype=torch_dtype,
|
|
)
|
|
# calc more accurate size
|
|
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 os.path.isdir(path):
|
|
return ControlNetModelFormat.Diffusers
|
|
else:
|
|
return ControlNetModelFormat.Checkpoint
|
|
|
|
@classmethod
|
|
def convert_if_required(
|
|
cls,
|
|
model_path: str,
|
|
output_path: str,
|
|
config: ModelConfigBase, # empty config or config of parent model
|
|
base_model: BaseModelType,
|
|
) -> str:
|
|
if cls.detect_format(model_path) != ControlNetModelFormat.Diffusers:
|
|
raise NotImplementedError("Checkpoint controlnet models currently unsupported")
|
|
else:
|
|
return model_path
|