immich/machine-learning/export/run.py
Mert 87a0ba3db3
feat(ml): export clip models to ONNX and host models on Hugging Face (#4700)
* export clip models

* export to hf

refactored export code

* export mclip, general refactoring

cleanup

* updated conda deps

* do transforms with pillow and numpy, add tokenization config to export, general refactoring

* moved conda dockerfile, re-added poetry

* minor fixes

* updated link

* updated tests

* removed `requirements.txt` from workflow

* fixed mimalloc path

* removed torchvision

* cleaner np typing

* review suggestions

* update default model name

* update test
2023-10-31 05:02:04 -05:00

76 lines
2.5 KiB
Python

import gc
import os
from pathlib import Path
from tempfile import TemporaryDirectory
from huggingface_hub import create_repo, login, upload_folder
from models import mclip, openclip
from rich.progress import Progress
models = [
"RN50::openai",
"RN50::yfcc15m",
"RN50::cc12m",
"RN101::openai",
"RN101::yfcc15m",
"RN50x4::openai",
"RN50x16::openai",
"RN50x64::openai",
"ViT-B-32::openai",
"ViT-B-32::laion2b_e16",
"ViT-B-32::laion400m_e31",
"ViT-B-32::laion400m_e32",
"ViT-B-32::laion2b-s34b-b79k",
"ViT-B-16::openai",
"ViT-B-16::laion400m_e31",
"ViT-B-16::laion400m_e32",
"ViT-B-16-plus-240::laion400m_e31",
"ViT-B-16-plus-240::laion400m_e32",
"ViT-L-14::openai",
"ViT-L-14::laion400m_e31",
"ViT-L-14::laion400m_e32",
"ViT-L-14::laion2b-s32b-b82k",
"ViT-L-14-336::openai",
"ViT-H-14::laion2b-s32b-b79k",
"ViT-g-14::laion2b-s12b-b42k",
"M-CLIP/LABSE-Vit-L-14",
"M-CLIP/XLM-Roberta-Large-Vit-B-32",
"M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
"M-CLIP/XLM-Roberta-Large-Vit-L-14",
]
login(token=os.environ["HF_AUTH_TOKEN"])
with Progress() as progress:
task1 = progress.add_task("[green]Exporting models...", total=len(models))
task2 = progress.add_task("[yellow]Uploading models...", total=len(models))
with TemporaryDirectory() as tmp:
tmpdir = Path(tmp)
for model in models:
model_name = model.split("/")[-1].replace("::", "__")
config_path = tmpdir / model_name / "config.json"
def upload() -> None:
progress.update(task2, description=f"[yellow]Uploading {model_name}")
repo_id = f"immich-app/{model_name}"
create_repo(repo_id, exist_ok=True)
upload_folder(repo_id=repo_id, folder_path=tmpdir / model_name)
progress.update(task2, advance=1)
def export() -> None:
progress.update(task1, description=f"[green]Exporting {model_name}")
visual_dir = tmpdir / model_name / "visual"
textual_dir = tmpdir / model_name / "textual"
if model.startswith("M-CLIP"):
mclip.to_onnx(model, visual_dir, textual_dir)
else:
name, _, pretrained = model_name.partition("__")
openclip.to_onnx(openclip.OpenCLIPModelConfig(name, pretrained), visual_dir, textual_dir)
progress.update(task1, advance=1)
gc.collect()
export()
upload()