Updated logger format

[vfdev-5]

Changed logger's format in the training-info.log from

�[32m[ignite]�[0m: Configuration: {'seed': 777, 'data_path': './', 'train_batch_size': 512, 'eval_batch_size': 1024, 'num_workers': 4, 'max_epochs': 20, 'use_amp': False, 'debug': False, 'train_epoch_length': None, 'eval_epoch_length': None, 'filename_prefix': 'training', 'n_saved': 2, 'save_every_iters': 1000, 'patience': 3, 'output_dir': PosixPath('logs/20230826-220744-backend-None-lr-0.0001'), 'log_every_iters': 10, 'lr': 0.0001, 'model': 'resnet18', 'backend': None, 'num_iters_per_epoch': None} �[32m[ignite]�[0m: Engine run starting with max_epochs=20. �[32m[ignite]�[0m: Engine run starting with max_epochs=1. �[32m[ignite]�[0m: Epoch[1] Complete. Time taken: 00:00:04.522 �[32m[ignite]�[0m: Engine run complete. Time taken: 00:00:04.672 �[32m[ignite]�[0m: train [1/10]: {'epoch': 1, 'train_loss': 2.417194128036499} �[32m[ignite]�[0m: train [1/20]: {'epoch': 1, 'train_loss': 2.387004852294922} 

to

2023-08-26 22:04:06,500 �[32m[ignite]�[0m INFO: Configuration: {'seed': 777, 'data_path': './', 'train_batch_size': 512, 'eval_batch_size': 1024, 'num_workers': 4, 'max_epochs': 20, 'use_amp': False, 'debug': False, 'train_epoch_length': None, 'eval_epoch_length': None, 'filename_prefix': 'training', 'n_saved': 2, 'save_every_iters': 1000, 'patience': 3, 'output_dir': PosixPath('logs/20230826-220341-backend-None-lr-0.0001'), 'log_every_iters': 10, 'lr': 0.0001, 'model': 'resnet18', 'backend': None, 'num_iters_per_epoch': None} 2023-08-26 22:04:09,164 �[32m[ignite]�[0m INFO: Engine run starting with max_epochs=20. 2023-08-26 22:04:09,164 �[32m[ignite]�[0m INFO: Engine run starting with max_epochs=1. 2023-08-26 22:04:19,865 �[32m[ignite]�[0m INFO: Epoch[1] Complete. Time taken: 00:00:10.583 2023-08-26 22:04:19,866 �[32m[ignite]�[0m INFO: Engine run complete. Time taken: 00:00:10.702 2023-08-26 22:04:22,919 �[32m[ignite]�[0m INFO: train [1/10]: {'epoch': 1, 'train_loss': 2.417192220687866} 2023-08-26 22:04:24,589 �[32m[ignite]�[0m INFO: train [1/20]: {'epoch': 1, 'train_loss': 2.3869330883026123}``` 

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