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from constants import LCM_DEFAULT_MODEL
from diffusers import (
DiffusionPipeline,
AutoencoderTiny,
UNet2DConditionModel,
LCMScheduler,
)
import torch
from backend.tiny_decoder import get_tiny_decoder_vae_model
from typing import Any
from diffusers import (
LCMScheduler,
StableDiffusionImg2ImgPipeline,
StableDiffusionXLImg2ImgPipeline,
)
def _get_lcm_pipeline_from_base_model(
lcm_model_id: str,
base_model_id: str,
use_local_model: bool,
):
pipeline = None
unet = UNet2DConditionModel.from_pretrained(
lcm_model_id,
torch_dtype=torch.float32,
local_files_only=use_local_model,
)
pipeline = DiffusionPipeline.from_pretrained(
base_model_id,
unet=unet,
torch_dtype=torch.float32,
local_files_only=use_local_model,
)
pipeline.scheduler = LCMScheduler.from_config(pipeline.scheduler.config)
return pipeline
def load_taesd(
pipeline: Any,
use_local_model: bool = False,
torch_data_type: torch.dtype = torch.float32,
):
vae_model = get_tiny_decoder_vae_model(pipeline.__class__.__name__)
pipeline.vae = AutoencoderTiny.from_pretrained(
vae_model,
torch_dtype=torch_data_type,
local_files_only=use_local_model,
)
def get_lcm_model_pipeline(
model_id: str = LCM_DEFAULT_MODEL,
use_local_model: bool = False,
):
pipeline = None
if model_id == "latent-consistency/lcm-sdxl":
pipeline = _get_lcm_pipeline_from_base_model(
model_id,
"stabilityai/stable-diffusion-xl-base-1.0",
use_local_model,
)
elif model_id == "latent-consistency/lcm-ssd-1b":
pipeline = _get_lcm_pipeline_from_base_model(
model_id,
"segmind/SSD-1B",
use_local_model,
)
else:
pipeline = DiffusionPipeline.from_pretrained(
model_id,
local_files_only=use_local_model,
)
return pipeline
def get_image_to_image_pipeline(pipeline: Any) -> Any:
components = pipeline.components
pipeline_class = pipeline.__class__.__name__
if (
pipeline_class == "LatentConsistencyModelPipeline"
or pipeline_class == "StableDiffusionPipeline"
):
return StableDiffusionImg2ImgPipeline(**components)
elif pipeline_class == "StableDiffusionXLPipeline":
return StableDiffusionXLImg2ImgPipeline(**components)
else:
raise Exception(f"Unknown pipeline {pipeline_class}")
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