| """Evaluate labeled local audio without a server. Built with Qwen; see LICENSE.""" |
| import argparse |
| import json |
| from pathlib import Path |
| from toddler_jev import ToddlerJev |
| from train import read_data |
|
|
| def main(): |
| p=argparse.ArgumentParser() |
| p.add_argument('--data',required=True) |
| p.add_argument('--output',required=True) |
| p.add_argument('--batch-size',type=int,default=1) |
| p.add_argument('--model',default=str(Path(__file__).parent)) |
| p.add_argument('--revision',default='v1.0.0') |
| p.add_argument('--device',default=None) |
| args=p.parse_args() |
| if args.batch_size<1:p.error('Batch size must be positive') |
| target=Path(args.output) |
| if target.exists():p.error('Output must be a new file') |
| rows=read_data(args.data) |
| model=ToddlerJev.from_pretrained(args.model,revision=args.revision,device=args.device) |
| correct=0 |
| with target.open('x',encoding='utf-8') as f: |
| for i in range(0,len(rows),args.batch_size): |
| batch=rows[i:i+args.batch_size] |
| for row,result in zip(batch,model.predict_batch(batch)): |
| result['id']=row.get('id',i) |
| result['target_index']=row['target'] |
| result['correct']=result['decision_index']==row['target'] |
| correct+=result['correct'] |
| f.write(json.dumps(result)+'\n') |
| f.flush() |
| print(json.dumps({'examples':len(rows),'correct':correct,'accuracy':correct/len(rows)})) |
|
|
| if __name__=='__main__':main() |
|
|
