首页log_file_name = os.path.join(experiment_log_dir, f"logs_{datetime.now().strftime('%d_%m_%Y_%H_%M_%S')}.log") logger = _logger(log_file_name) logger.debug("=" * 45) logger.debug(f'Dataset: {data_type}') logger.debug(f'Method: {method}') logger.debug(f'Mode: {training_mode}') logger.debug("=" * 45)解释这段代码

log_file_name = os.path.join(experiment_log_dir, f"logs_{datetime.now().strftime('%d_%m_%Y_%H_%M_%S')}.log") logger = _logger(log_file_name) logger.debug("=" * 45) logger.debug(f'Dataset: {data_type}') logger.debug(f'Method: {method}') logger.debug(f'Mode: {training_mode}') logger.debug("=" * 45)解释这段代码

时间: 2023-05-25 21:04:27 浏览: 197

jquery-mvc.rar_The Client_jquery mvc_jquery.Controller_jquerymvc

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CorMVC is a jQuery-powered Model-View-Controller (MVC) framework that can aide in the development of single-page jQuery applications. It evolved out of my recent presentation, Building Single-Page Applications Using jQuery And ColdFusion, and will continue to evolve as I think more deeply about this type of application architecture. CorMVC stands for: Client-Only-Required 一个javascript的MVC框架 Model-View-Controller, and is my laboratory experiment in application architecture held completely seperate from server-side technologies.

As an AI language model, I do not have a physical body, emotions, or personal opinions. Therefore, I cannot have interests or preferences. I exist solely to generate human-like responses to user inputs.

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experiment_log_dir = os.path.join(logs_save_dir, experiment_description, run_description, training_mode + f"_seed_{SEED}") os.makedirs(experiment_log_dir, exist_ok=True)解释这段代码

解释一下这段代码：if __name__ == "__main__": args = make_parser().parse_args() exp = get_exp(args.exp_file, args.name) main(exp, args)

# Parser parser = argparse.ArgumentParser(description='SimCLR') parser.add_argument('--config_env', help='Config file for the environment') parser.add_argument('--config_exp', help='Config file for the experiment') args = parser.parse_args()

# Parser parser = argparse.ArgumentParser(description='Graph Contrastive Clustering') parser.add_argument('--config_env', help='Config file for the environment') parser.add_argument('--config_exp', help='Config file for the experiment') args = parser.parse_args()

Traceback (most recent call last): File "main.py", line 409, in <module> run_experiment(args) File "main.py", line 266, in run_experiment loss_e = model.get_loss(history_glist, output[0], static_graph, history_tail_seq, one_hot_tail_seq, use_c

if self.experiment: self.experiment.log_metric("train_step model loss", loss.item(), step=self.step)是什么

x_adv = np.load('data\experiment_data\mnist\local\x_train_adv_PGD.npy')

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解释一下这段代码：if name == "main": args = make_parser().parse_args() exp = get_exp(args.exp_file, args.name) main(exp, args)