old_contents: _base_ = [
      '../_base_/models/retinanet_r50_fpn.py',
      '../_base_/datasets/coco_detection.py',
      '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
  ]
  pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth'  # noqa
  model = dict(
      backbone=dict(
          _delete_=True,
          type='SwinTransformer',
          embed_dims=96,
          depths=[2, 2, 6, 2],
          num_heads=[3, 6, 12, 24],
          window_size=7,
          mlp_ratio=4,
          qkv_bias=True,
          qk_scale=None,
          drop_rate=0.,
          attn_drop_rate=0.,
          drop_path_rate=0.2,
          patch_norm=True,
          out_indices=(1, 2, 3),
          # Please only add indices that would be used
          # in FPN, otherwise some parameter will not be used
          with_cp=False,
          init_cfg=dict(type='Pretrained', checkpoint=pretrained)),
      neck=dict(in_channels=[192, 384, 768], start_level=0, num_outs=5))
  
  optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
  
new_contents: _base_ = [
      '../_base_/models/retinanet_r50_fpn.py',
      '../_base_/datasets/coco_detection.py',
      '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
  ]
  pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth'  # noqa
  model = dict(
      backbone=dict(
          _delete_=True,
          type='SwinTransformer',
          embed_dims=96,
          depths=[2, 2, 6, 2],
          num_heads=[3, 6, 12, 24],
          window_size=7,
          mlp_ratio=4,
          qkv_bias=True,
          qk_scale=None,
          drop_rate=0.,
          attn_drop_rate=0.,
          drop_path_rate=0.2,
          patch_norm=True,
          out_indices=(1, 2, 3),
          # Please only add indices that would be used
          # in FPN, otherwise some parameter will not be used
          with_cp=False,
          convert_weights=True,
          init_cfg=dict(type='Pretrained', checkpoint=pretrained)),
      neck=dict(in_channels=[192, 384, 768], start_level=0, num_outs=5))
  
  optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
  
subject: Update retinanet_swin-t-p4-w7_fpn_1x_coco.py (#6973)