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from constants import DEVICE, LCM_DEFAULT_MODEL_OPENVINO
from backend.tiny_decoder import get_tiny_decoder_vae_model
from typing import Any
from backend.device import is_openvino_device
from paths import get_base_folder_name
if is_openvino_device():
from huggingface_hub import snapshot_download
from optimum.intel.openvino.modeling_diffusion import OVBaseModel
from optimum.intel.openvino.modeling_diffusion import (
OVStableDiffusionPipeline,
OVStableDiffusionImg2ImgPipeline,
OVStableDiffusionXLPipeline,
OVStableDiffusionXLImg2ImgPipeline,
)
from backend.openvino.custom_ov_model_vae_decoder import CustomOVModelVaeDecoder
def ov_load_taesd(
pipeline: Any,
use_local_model: bool = False,
):
taesd_dir = snapshot_download(
repo_id=get_tiny_decoder_vae_model(pipeline.__class__.__name__),
local_files_only=use_local_model,
)
pipeline.vae_decoder = CustomOVModelVaeDecoder(
model=OVBaseModel.load_model(f"{taesd_dir}/vae_decoder/openvino_model.xml"),
parent_model=pipeline,
model_dir=taesd_dir,
)
def get_ov_text_to_image_pipeline(
model_id: str = LCM_DEFAULT_MODEL_OPENVINO,
use_local_model: bool = False,
) -> Any:
if "xl" in get_base_folder_name(model_id).lower():
pipeline = OVStableDiffusionXLPipeline.from_pretrained(
model_id,
local_files_only=use_local_model,
ov_config={"CACHE_DIR": ""},
device=DEVICE.upper(),
)
else:
pipeline = OVStableDiffusionPipeline.from_pretrained(
model_id,
local_files_only=use_local_model,
ov_config={"CACHE_DIR": ""},
device=DEVICE.upper(),
)
return pipeline
def get_ov_image_to_image_pipeline(
model_id: str = LCM_DEFAULT_MODEL_OPENVINO,
use_local_model: bool = False,
) -> Any:
if "xl" in get_base_folder_name(model_id).lower():
pipeline = OVStableDiffusionXLImg2ImgPipeline.from_pretrained(
model_id,
local_files_only=use_local_model,
ov_config={"CACHE_DIR": ""},
device=DEVICE.upper(),
)
else:
pipeline = OVStableDiffusionImg2ImgPipeline.from_pretrained(
model_id,
local_files_only=use_local_model,
ov_config={"CACHE_DIR": ""},
device=DEVICE.upper(),
)
return pipeline
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