retinanet_convmlp_s_fpn_1x_coco.py

_base_ = [
    '../_base_/models/retinanet_r50_fpn.py',
    '../_base_/datasets/coco_detection.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]

pretrained = 'http://ix.cs.uoregon.edu/~alih/conv-mlp/checkpoints/convmlp_s_imagenet.pth'  # noqa
model = dict(
    backbone=dict(
        _delete_=True,
        type='ConvMLPSmall',
        init_cfg=dict(type='Pretrained', checkpoint=pretrained)),
    neck=dict(
        type='FPN',
        in_channels=[64, 128, 256, 512],
        out_channels=256,
        num_outs=5))

optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)