| _base_ = [ | |
| '../_base_/models/faster-rcnn_r50_fpn.py', | |
| '../common/lsj-200e_coco-detection.py' | |
| ] | |
| image_size = (1024, 1024) | |
| batch_augments = [dict(type='BatchFixedSizePad', size=image_size)] | |
| model = dict(data_preprocessor=dict(batch_augments=batch_augments)) | |
| train_dataloader = dict(batch_size=8, num_workers=4) | |
| # Enable automatic-mixed-precision training with AmpOptimWrapper. | |
| optim_wrapper = dict( | |
| type='AmpOptimWrapper', | |
| optimizer=dict( | |
| type='SGD', lr=0.02 * 4, momentum=0.9, weight_decay=0.00004)) | |
| # NOTE: `auto_scale_lr` is for automatically scaling LR, | |
| # USER SHOULD NOT CHANGE ITS VALUES. | |
| # base_batch_size = (8 GPUs) x (8 samples per GPU) | |
| auto_scale_lr = dict(base_batch_size=64) | |