Export Donut model to onnx and run it with onnxruntime
Project description
Onnx Donut
Package to export a Donut model from pytorch to ONNX, then run it with onnxruntime.
Installation
pip install onnx-donut
Export to onnx
from onnx_donut.exporter import export_onnx
from onnx_donut.quantizer import quantize
# Hugging Face model card or folder
model_path = "naver-clova-ix/donut-base-finetuned-docvqa"
# Folder where the exported model will be stored
dst_folder = "converted_donut"
# Export from Pytorch to ONNX
export_onnx(model_path, dst_folder, opset_version=16)
# Quantize your model to int8
quantize(dst_folder, dst_folder + "_quant")
Model inference with onnxruntime
from onnx_donut.predictor import OnnxPredictor
import numpy as np
from PIL import Image
# Image path to run on
img_path = "/path/to/your/image.png"
# Folder where the exported model will be stored
onnx_folder = "converted_donut"
# Read image
img = np.array(Image.open(img_path).convert('RGB'))
# Instantiate ONNX predictor
predictor = OnnxPredictor(model_folder=onnx_folder, sess_options=options)
# Write your prompt accordingly to the model you use
prompt = f"<s_docvqa><s_question>what is the title?</s_question><s_answer>"
# Run prediction
out = predictor.generate(img, prompt)
# Display prediction
print(out)
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