_base_ = [
    '../_base_/models/cascade_mask_rcnn_r50_fpn.py',
    '../_base_/datasets/coco_instance.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]

checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth'  # noqa
model = dict(
    backbone=dict(
        init_cfg=dict(
            type='Pretrained', prefix='backbone.', checkpoint=checkpoint)))

optim_wrapper = dict(
    optimizer=dict(_delete_=True, type='AdamW', lr=0.0002, weight_decay=0.05),
    paramwise_cfg=dict(norm_decay_mult=0., bypass_duplicate=True))

_base_ = [
    '../_base_/models/cascade_mask_rcnn_r50_fpn.py',
    '../_base_/datasets/coco_instance.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]

checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth'  # noqa
model = dict(
    backbone=dict(
        init_cfg=dict(
            type='Pretrained', prefix='backbone.', checkpoint=checkpoint)))

optimizer = dict(
    _delete_=True,
    type='AdamW',
    lr=0.0002,
    weight_decay=0.05,
    paramwise_cfg=dict(norm_decay_mult=0., bypass_duplicate=True))
