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Model Export Script
Export trained model to ONNX format for deployment.
Usage:
python scripts/export_model.py --model outputs/checkpoints/best_doctamper.pth --format onnx
"""
import argparse
import sys
from pathlib import Path
# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent))
import torch
from src.config import get_config
from src.models import get_model
from src.utils import export_to_onnx, export_to_torchscript
def parse_args():
parser = argparse.ArgumentParser(description="Export model for deployment")
parser.add_argument('--model', type=str, required=True,
help='Path to model checkpoint')
parser.add_argument('--format', type=str, default='onnx',
choices=['onnx', 'torchscript', 'both'],
help='Export format')
parser.add_argument('--output', type=str, default='outputs/exported',
help='Output directory')
parser.add_argument('--config', type=str, default='config.yaml',
help='Path to config file')
return parser.parse_args()
def main():
args = parse_args()
# Load config
config = get_config(args.config)
print("\n" + "="*60)
print("Model Export")
print("="*60)
print(f"Model: {args.model}")
print(f"Format: {args.format}")
print("="*60)
# Create output directory
output_dir = Path(args.output)
output_dir.mkdir(parents=True, exist_ok=True)
# Load model
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = get_model(config).to(device)
checkpoint = torch.load(args.model, map_location=device)
if 'model_state_dict' in checkpoint:
model.load_state_dict(checkpoint['model_state_dict'])
else:
model.load_state_dict(checkpoint)
model.eval()
print("Model loaded")
# Get image size
image_size = config.get('data.image_size', 384)
# Export
if args.format in ['onnx', 'both']:
onnx_path = output_dir / 'model.onnx'
export_to_onnx(model, str(onnx_path), input_size=(image_size, image_size))
if args.format in ['torchscript', 'both']:
ts_path = output_dir / 'model.pt'
export_to_torchscript(model, str(ts_path), input_size=(image_size, image_size))
print("\n" + "="*60)
print("Export Complete!")
print(f"Output: {output_dir}")
print("="*60)
if __name__ == '__main__':
main()
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