mask_rcnn_lit_s_fpn_1x_coco.py

_base_ = [
    '../_base_/models/mask_rcnn_fpn_lit_s.py',
    '../_base_/datasets/coco_instance.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]

model = dict(
    pretrained='pretrained/lit_s.pth',
    backbone=dict(
        embed_dim=96,
        depths=[2, 2, 6, 2],
        num_heads=[3, 6, 12, 24],
        window_size=7,
        ape=False,
        drop_path_rate=0.2,
        patch_norm=True,
        use_checkpoint=True
    ),
    neck=dict(in_channels=[96, 192, 384, 768]))

optimizer = dict(type='AdamW', lr=0.0002, weight_decay=0.0001,
                 paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.),
                                                 'relative_position_bias_table': dict(decay_mult=0.),
                                                 'norm': dict(decay_mult=0.)})
                 )

lr_config = dict(step=[8, 11])
runner = dict(type='EpochBasedRunnerAmp', max_epochs=12)

# do not use mmdet version fp16
fp16 = None
optimizer_config = dict(
    type="DistOptimizerHook",
    update_interval=1,
    grad_clip=None,
    coalesce=True,
    bucket_size_mb=-1,
    use_fp16=True,
)