# evaluation
evaluation = dict(interval=1, metric="mAP")
# optimizer
optimizer = dict(type="SGD", lr=0.0025, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
# learning policy
lr_config = dict(
    policy="step",
    warmup="linear",
    warmup_iters=500,
    warmup_ratio=1.0 / 3,
    step=[80000, 110000],
)
runner = dict(type="EpochBasedRunner", max_epochs=12)
checkpoint_config = dict(interval=1)
