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_base_ = [ |
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'/home/liuziyuan/proj/rmcd-kd/configs/_base_/models/KD-cgnet.py', |
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'/home/liuziyuan/proj/rmcd-kd/configs/common/standard_512x512_200k_cgwx.py'] |
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dataset_type = 'LEVIR_CD_Dataset' |
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data_root = '/nas/datasets/lzy/RS-ChangeDetection/CGWX' |
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crop_size = (512, 512) |
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checkpoint_student = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints/CGNet/CGNet/best_mIoU_iter_155000.pth' |
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checkpoint_teacher_l = '/nas/datasets/lzy/RS-ChangeDetection/Best_ckpt_3/CGNet/large/best_mIoU_iter_77500.pth' |
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checkpoint_teacher_m = '/nas/datasets/lzy/RS-ChangeDetection/Best_ckpt_3/CGNet/medium/best_mIoU_iter_9000.pth' |
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checkpoint_teacher_s = '/nas/datasets/lzy/RS-ChangeDetection/Best_ckpt-KD/CGNet/small/best_mIoU_iter_92000.pth' |
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model = dict( |
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init_cfg=dict(type='Pretrained', checkpoint=checkpoint_student), |
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init_cfg_t_l = dict(type='Pretrained', checkpoint=checkpoint_teacher_l), |
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init_cfg_t_m = dict(type='Pretrained', checkpoint=checkpoint_teacher_m), |
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init_cfg_t_s = dict(type='Pretrained', checkpoint=checkpoint_teacher_s), |
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test_cfg=dict(mode='slide', crop_size=crop_size, stride=(crop_size[0]//2, crop_size[1]//2)), |
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) |
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optimizer = dict( |
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type='AdamW', |
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lr=5e-4, |
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betas=(0.9, 0.999), |
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weight_decay=0.0025) |
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optim_wrapper = dict( |
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_delete_=True, |
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type='OptimWrapper', |
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optimizer=optimizer) |
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param_scheduler = [ |
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dict( |
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type='LinearLR', start_factor=1e-6, by_epoch=False, begin=0, end=1000), |
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dict( |
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type='PolyLR', |
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power=1.0, |
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begin=1000, |
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end=100000, |
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eta_min=0.0, |
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by_epoch=False, |
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) |
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] |
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train_cfg = dict(type='IterBasedTrainLoop', max_iters=100000, val_interval=1000) |
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val_cfg = dict(type='ValLoop') |
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test_cfg = dict(type='TestLoop') |
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default_hooks = dict( |
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timer=dict(type='IterTimerHook'), |
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logger=dict(type='LoggerHook', interval=100, log_metric_by_epoch=False), |
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param_scheduler=dict(type='ParamSchedulerHook'), |
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checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=1000, |
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save_best='mIoU'), |
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sampler_seed=dict(type='DistSamplerSeedHook'), |
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visualization=dict(type='CDVisualizationHook', interval=1, |
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img_shape=(512, 512, 3))) |
