soft_teacher_faster_rcnn_r50_caffe_fpn_coco_full_720k.py

_base_="base.py"

data = dict(
    samples_per_gpu=8,
    workers_per_gpu=8,
    train=dict(

        sup=dict(

            ann_file="data/coco/annotations/instances_train2017.json",
            img_prefix="data/coco/train2017/",

        ),
        unsup=dict(

            ann_file="data/coco/annotations/instances_unlabeled2017.json",
            img_prefix="data/coco/unlabeled2017/",

        ),
    ),
    sampler=dict(
        train=dict(
            sample_ratio=[1, 1],
        )
    ),
)

semi_wrapper = dict(
    train_cfg=dict(
        unsup_weight=2.0,
    )
)

lr_config = dict(step=[120000 * 4, 160000 * 4])
runner = dict(_delete_=True, type="IterBasedRunner", max_iters=180000 * 4)