text: USE_MMCLS = True
  _base_ = [
      '../_base_/datasets/mot_challenge_reid.py', '../_base_/default_runtime.py'
  ]
  model = dict(
      reid=dict(
          type='BaseReID',
          backbone=dict(
              type='ResNet',
              depth=50,
              num_stages=4,
              out_indices=(3, ),
              style='pytorch'),
          neck=dict(type='GlobalAveragePooling', kernel_size=(8, 4), stride=1),
          head=dict(
              type='LinearReIDHead',
              num_fcs=1,
              in_channels=2048,
              fc_channels=1024,
              out_channels=128,
              num_classes=378,
              loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
              loss_pairwise=dict(
                  type='TripletLoss', margin=0.3, loss_weight=1.0),
              norm_cfg=dict(type='BN1d'),
              act_cfg=dict(type='ReLU')),
          init_cfg=dict(
              type='Pretrained',
              checkpoint=  # noqa: E251
              'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_batch256_imagenet_20200708-cfb998bf.pth'  # noqa: E501
          )))
  # optimizer
  optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0001)
  optimizer_config = dict(grad_clip=None)
  # learning policy
  lr_config = dict(
      policy='step',
      warmup='linear',
      warmup_iters=1000,
      warmup_ratio=1.0 / 1000,
      step=[5])
  total_epochs = 6
  