text: _base_ = [
      '../_base_/models/liteflownet2/liteflownet2_pre_M3S3R3.py',
      '../_base_/datasets/flyingchairs_320x448.py',
      '../_base_/default_runtime.py'
  ]
  
  optimizer = dict(type='Adam', lr=6e-5, weight_decay=0.0004, betas=(0.9, 0.999))
  optimizer_config = dict(grad_clip=None)
  # learning policy
  lr_config = dict(
      policy='step', by_epoch=False, gamma=0.5, step=[120000, 160000, 200000])
  runner = dict(type='IterBasedRunner', max_iters=240000)
  checkpoint_config = dict(by_epoch=False, interval=40000)
  evaluation = dict(interval=40000, metric='EPE')
  
  # Weights are initialized from model of previous stage
  load_from = 'https://download.openmmlab.com/mmflow/liteflownet2/liteflownet2_pre_M4S4R4_8x1_flyingchairs_320x448.pth'  # noqa
  