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| import sys | |
| from utils.dl.common.env import set_random_seed | |
| set_random_seed(1) | |
| from typing import List | |
| from data.dataloader import build_dataloader | |
| from data import CLScenario, build_cl_scenario | |
| from methods.elasticdnn.api.online_model_v2 import ElasticDNN_OnlineModel | |
| import torch | |
| import sys | |
| from utils.common.exp import save_models_dict_for_init, get_res_save_dir | |
| from utils.dl.common.env import create_tbwriter | |
| import os | |
| from utils.common.log import logger | |
| from utils.common.data_record import write_json | |
| # from methods.shot.shot import OnlineShotModel | |
| from methods.base.alg import BaseAlg | |
| from methods.base.model import BaseModel | |
| def baseline_cl(app_name: str, | |
| scenario: CLScenario, | |
| cl_alg: BaseAlg, | |
| cl_alg_hyp: dict, | |
| cl_model: BaseModel, | |
| device, | |
| __entry_file__, | |
| tag=None): | |
| # involve_fm = settings['involve_fm'] | |
| # task_name = app_name | |
| # online_model = elasticfm_model | |
| log_dir = get_res_save_dir(__entry_file__, tag=tag) | |
| tb_writer = create_tbwriter(os.path.join(log_dir, 'tb_log'), False) | |
| res = [] | |
| global_avg_after_acc = 0. | |
| global_iter = 0 | |
| for task_index, _ in enumerate(scenario.target_tasks_order): | |
| cur_target_task_name = scenario.target_tasks_order[scenario.cur_task_index] | |
| # if cur_target_domain_name in da_alg_hyp: | |
| # da_alg_hyp = da_alg_hyp[cur_target_domain_name] | |
| # logger.info(f'use dataset-specific hyps') | |
| # tmp_sd_path = os.path.join(log_dir, 'tmp_sd_model.pt') | |
| # torch.save({'main': sd}, tmp_sd_path) | |
| # if task_name != 'cls': | |
| # da_model_args = [f'{task_name}/{domain_index}', | |
| # tmp_sd_path, | |
| # device, | |
| # scenario.num_classes] | |
| # else: | |
| # da_model_args = [f'{task_name}/{domain_index}', | |
| # tmp_sd_path, | |
| # device] | |
| # cur_da_model = da_model(*da_model_args) | |
| cl_metrics, after_cl_model = cl_alg( | |
| {'main': cl_model}, | |
| os.path.join(log_dir, f'{app_name}/{task_index}') | |
| ).run(scenario, cl_alg_hyp) | |
| # os.remove(tmp_sd_path) | |
| if task_index > 0: | |
| import shutil | |
| shutil.rmtree(os.path.join(log_dir, f'{app_name}/{task_index}/backup_codes')) | |
| accs = cl_metrics['accs'] | |
| before_acc = accs[0]['acc'] | |
| after_acc = accs[-1]['acc'] | |
| tb_writer.add_scalars(f'accs/{app_name}', dict(before=before_acc, after=after_acc), task_index) | |
| tb_writer.add_scalar(f'times/{app_name}', cl_metrics['time'], task_index) | |
| for _acc in accs: | |
| tb_writer.add_scalar('total_acc', _acc['acc'], _acc['iter'] + global_iter) | |
| global_iter += _acc['iter'] + 1 | |
| scenario.next_task() | |
| logger.info(f"app: {app_name}, task {task_index}, acc: {before_acc:.4f} -> " | |
| f"{after_acc:.4f} ({cl_metrics['time']:.2f}s)") | |
| global_avg_after_acc += after_acc | |
| cur_res = cl_metrics | |
| res += [cur_res] | |
| write_json(os.path.join(log_dir, 'res.json'), res, backup=False) | |
| global_avg_after_acc /= (task_index + 1) | |
| logger.info(f'-----> final metric: {global_avg_after_acc:.4f}') | |
| write_json(os.path.join(log_dir, f'res_{global_avg_after_acc:.4f}.json'), res, backup=False) | |