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feat(api): add conversion for SDXL models
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from logging import getLogger | ||
from os import path | ||
from typing import Dict, Optional, Tuple | ||
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import torch | ||
from optimum.pipelines.diffusers.pipeline_stable_diffusion_xl import StableDiffusionXLPipeline | ||
from optimum.exporters.onnx import main_export | ||
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from ..utils import ConversionContext | ||
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logger = getLogger(__name__) | ||
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@torch.no_grad() | ||
def convert_diffusion_diffusers_xl( | ||
conversion: ConversionContext, | ||
model: Dict, | ||
source: str, | ||
format: Optional[str], | ||
hf: bool = False, | ||
) -> Tuple[bool, str]: | ||
""" | ||
From https://github.com/huggingface/diffusers/blob/main/scripts/convert_stable_diffusion_checkpoint_to_onnx.py | ||
""" | ||
name = model.get("name") | ||
# TODO: support alternate VAE | ||
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device = conversion.training_device | ||
dtype = conversion.torch_dtype() | ||
logger.debug("using Torch dtype %s for pipeline", dtype) | ||
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dest_path = path.join(conversion.model_path, name) | ||
model_index = path.join(dest_path, "model_index.json") | ||
model_hash = path.join(dest_path, "hash.txt") | ||
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# diffusers go into a directory rather than .onnx file | ||
logger.info( | ||
"converting Stable Diffusion XL model %s: %s -> %s/", name, source, dest_path | ||
) | ||
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if "hash" in model and not path.exists(model_hash): | ||
logger.info("ONNX model does not have hash file, adding one") | ||
with open(model_hash, "w") as f: | ||
f.write(model["hash"]) | ||
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if path.exists(dest_path) and path.exists(model_index): | ||
logger.info("ONNX model already exists, skipping conversion") | ||
return (False, dest_path) | ||
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# safetensors -> diffusers directory with torch models | ||
temp_path = path.join(conversion.cache_path, f"{name}-torch") | ||
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if format == "safetensors": | ||
pipeline = StableDiffusionXLPipeline.from_single_file(source, use_safetensors=True) | ||
else: | ||
pipeline = StableDiffusionXLPipeline.from_pretrained(source) | ||
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pipeline.save_pretrained(temp_path) | ||
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# directory -> onnx using optimum exporters | ||
main_export( | ||
temp_path, | ||
output=dest_path, | ||
task="stable-diffusion-xl", | ||
device=device, | ||
fp16=conversion.half, | ||
framework="pt", | ||
) | ||
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# TODO: optimize UNet to fp16 | ||
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return False, dest_path |