retinanet_r50_fpn_1x_objects365v2.py 926 B

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  1. _base_ = [
  2. '../_base_/models/retinanet_r50_fpn.py',
  3. '../_base_/datasets/objects365v2_detection.py',
  4. '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
  5. ]
  6. model = dict(bbox_head=dict(num_classes=365))
  7. # Using 8 GPUS while training
  8. optim_wrapper = dict(
  9. type='OptimWrapper',
  10. optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001),
  11. clip_grad=dict(max_norm=35, norm_type=2))
  12. # learning rate
  13. param_scheduler = [
  14. dict(
  15. type='LinearLR',
  16. start_factor=1.0 / 1000,
  17. by_epoch=False,
  18. begin=0,
  19. end=10000),
  20. dict(
  21. type='MultiStepLR',
  22. begin=0,
  23. end=12,
  24. by_epoch=True,
  25. milestones=[8, 11],
  26. gamma=0.1)
  27. ]
  28. # NOTE: `auto_scale_lr` is for automatically scaling LR,
  29. # USER SHOULD NOT CHANGE ITS VALUES.
  30. # base_batch_size = (8 GPUs) x (2 samples per GPU)
  31. auto_scale_lr = dict(base_batch_size=16)