4. 固定选择后，再看保留集 · 实现代码

selected_mode=min(records,key=lambda m:records[m]['validation']['ce'])
for mode,model in models.items():
    records[mode]['heldout']=evaluate_binary(model,x[heldout_idx],y[heldout_idx])
print('只按验证 CE 选出的方案：',selected_mode)
print('mode | train acc | val acc | heldout acc | selected epoch')
for mode,r in records.items():
    print(mode,round(r['train']['accuracy'],4),round(r['validation']['accuracy'],4),round(r['heldout']['accuracy'],4),r['selected_epoch'])
LAB09_RESULT={'provenance':provenance,'protocol':{'train_n':TRAIN_LIMIT,'dx':DX,'epochs':EPOCHS,'batch_size':BATCH_SIZE,'learning_rate':LEARNING_RATE,'seed':SEED},
              'selected_by_validation':selected_mode,'scopes':scope_table,'records':records}
print('LAB09_RESULT_JSON='+json.dumps(LAB09_RESULT,ensure_ascii=False))

(OUT/'transfer-results.json').write_text(json.dumps(LAB09_RESULT,ensure_ascii=False,indent=2))
# 当前单元无法确认宿主平台或是否使用全新进程；unknown 不等于 False。
verification={'local_run':'unknown','cloud_run':'unknown','source_model_unchanged':hashlib.sha256(MODEL_PATH.read_bytes()).hexdigest()==model_sha256,'source_checkpoint_sha256':model_sha256,'sample_split_independent':True,'selected_by_validation':selected_mode,'scope':'complete student/teacher re-execution of 4 small transfer arms','torch':torch.__version__}
(OUT/'verification.json').write_text(json.dumps(verification,indent=2))