InvokeAI/invokeai/backend/model_management/models/ip_adapter.py
2023-09-15 13:18:00 -04:00

93 lines
3.0 KiB
Python

import os
import typing
from enum import Enum
from typing import Literal, Optional
import torch
from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus, build_ip_adapter
from invokeai.backend.model_management.models.base import (
BaseModelType,
InvalidModelException,
ModelBase,
ModelConfigBase,
ModelType,
SubModelType,
classproperty,
)
class IPAdapterModelFormat(str, Enum):
# The custom IP-Adapter model format defined by InvokeAI.
InvokeAI = "invokeai"
class IPAdapterModel(ModelBase):
class InvokeAIConfig(ModelConfigBase):
model_format: Literal[IPAdapterModelFormat.InvokeAI]
def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
assert model_type == ModelType.IPAdapter
super().__init__(model_path, base_model, model_type)
self.model_size = os.path.getsize(self.model_path)
@classmethod
def detect_format(cls, path: str) -> str:
if not os.path.exists(path):
raise ModuleNotFoundError(f"No IP-Adapter model at path '{path}'.")
if os.path.isdir(path):
model_file = os.path.join(path, "ip_adapter.bin")
image_encoder_config_file = os.path.join(path, "image_encoder.txt")
if os.path.exists(model_file) and os.path.exists(image_encoder_config_file):
return IPAdapterModelFormat.InvokeAI
raise InvalidModelException(f"Unexpected IP-Adapter model format: {path}")
@classproperty
def save_to_config(cls) -> bool:
return True
def get_size(self, child_type: Optional[SubModelType] = None) -> int:
if child_type is not None:
raise ValueError("There are no child models in an IP-Adapter model.")
return self.model_size
def get_model(
self,
torch_dtype: Optional[torch.dtype],
child_type: Optional[SubModelType] = None,
) -> typing.Union[IPAdapter, IPAdapterPlus]:
if child_type is not None:
raise ValueError("There are no child models in an IP-Adapter model.")
return build_ip_adapter(
ip_adapter_ckpt_path=os.path.join(self.model_path, "ip_adapter.bin"), device="cpu", dtype=torch_dtype
)
@classmethod
def convert_if_required(
cls,
model_path: str,
output_path: str,
config: ModelConfigBase,
base_model: BaseModelType,
) -> str:
format = cls.detect_format(model_path)
if format == IPAdapterModelFormat.InvokeAI:
return model_path
else:
raise ValueError(f"Unsupported format: '{format}'.")
def get_ip_adapter_image_encoder_model_id(model_path: str):
"""Read the ID of the image encoder associated with the IP-Adapter at `model_path`."""
image_encoder_config_file = os.path.join(model_path, "image_encoder.txt")
with open(image_encoder_config_file, "r") as f:
image_encoder_model = f.readline().strip()
return image_encoder_model