cog_sdxl/script/download_preprocessing_weights.py

import argparse
import os
import shutil

from transformers import (
    BlipForConditionalGeneration,
    BlipProcessor,
    CLIPSegForImageSegmentation,
    CLIPSegProcessor,
    Swin2SRForImageSuperResolution,
)

DEFAULT_BLIP = "Salesforce/blip-image-captioning-large"
DEFAULT_CLIPSEG = "CIDAS/clipseg-rd64-refined"
DEFAULT_SWINIR = "caidas/swin2SR-realworld-sr-x4-64-bsrgan-psnr"


def upload(args):
    blip_processor = BlipProcessor.from_pretrained(DEFAULT_BLIP)
    blip_model = BlipForConditionalGeneration.from_pretrained(DEFAULT_BLIP)

    clip_processor = CLIPSegProcessor.from_pretrained(DEFAULT_CLIPSEG)
    clip_model = CLIPSegForImageSegmentation.from_pretrained(DEFAULT_CLIPSEG)

    swin_model = Swin2SRForImageSuperResolution.from_pretrained(DEFAULT_SWINIR)

    temp_models = "tmp/models"
    if os.path.exists(temp_models):
        shutil.rmtree(temp_models)
    os.makedirs(temp_models)

    blip_processor.save_pretrained(os.path.join(temp_models, "blip_processor"))
    blip_model.save_pretrained(os.path.join(temp_models, "blip_large"))
    clip_processor.save_pretrained(os.path.join(temp_models, "clip_seg_processor"))
    clip_model.save_pretrained(os.path.join(temp_models, "clip_seg_rd64_refined"))
    swin_model.save_pretrained(
        os.path.join(temp_models, "swin2sr_realworld_sr_x4_64_bsrgan_psnr")
    )

    for val in os.listdir(temp_models):
        if "tar" not in val:
            os.system(
                f"sudo tar -cvf {os.path.join(temp_models, val)}.tar -C {os.path.join(temp_models, val)} ."
            )
            os.system(
                f"gcloud storage cp -R {os.path.join(temp_models, val)}.tar gs://{args.bucket}/{val}/"
            )


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--bucket", "-m", type=str)
    args = parser.parse_args()
    upload(args)