| _base_ = './detr_r50_8xb2-150e_coco.py' | |
| # learning policy | |
| max_epochs = 500 | |
| train_cfg = dict( | |
| type='EpochBasedTrainLoop', max_epochs=max_epochs, val_interval=10) | |
| param_scheduler = [ | |
| dict( | |
| type='MultiStepLR', | |
| begin=0, | |
| end=max_epochs, | |
| by_epoch=True, | |
| milestones=[334], | |
| gamma=0.1) | |
| ] | |
| # only keep latest 2 checkpoints | |
| default_hooks = dict(checkpoint=dict(max_keep_ckpts=2)) | |
| # NOTE: `auto_scale_lr` is for automatically scaling LR, | |
| # USER SHOULD NOT CHANGE ITS VALUES. | |
| # base_batch_size = (8 GPUs) x (2 samples per GPU) | |
| auto_scale_lr = dict(base_batch_size=16) | |