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code_test/configs/hrnet/cascade_rcnn_hrnetv2p_w32_2...

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  1. _base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py'

  2. model = dict(

  3.     backbone=dict(

  4.         _delete_=True,

  5.         type='HRNet',

  6.         extra=dict(

  7.             stage1=dict(

  8.                 num_modules=1,

  9.                 num_branches=1,

  10.                 block='BOTTLENECK',

  11.                 num_blocks=(4, ),

  12.                 num_channels=(64, )),

  13.             stage2=dict(

  14.                 num_modules=1,

  15.                 num_branches=2,

  16.                 block='BASIC',

  17.                 num_blocks=(4, 4),

  18.                 num_channels=(32, 64)),

  19.             stage3=dict(

  20.                 num_modules=4,

  21.                 num_branches=3,

  22.                 block='BASIC',

  23.                 num_blocks=(4, 4, 4),

  24.                 num_channels=(32, 64, 128)),

  25.             stage4=dict(

  26.                 num_modules=3,

  27.                 num_branches=4,

  28.                 block='BASIC',

  29.                 num_blocks=(4, 4, 4, 4),

  30.                 num_channels=(32, 64, 128, 256))),

  31.         init_cfg=dict(

  32.             type='Pretrained', checkpoint='open-mmlab://msra/hrnetv2_w32')),

  33.     neck=dict(

  34.         _delete_=True,

  35.         type='HRFPN',

  36.         in_channels=[32, 64, 128, 256],

  37.         out_channels=256))

  38. # learning policy

  39. lr_config = dict(step=[16, 19])

  40. runner = dict(type='EpochBasedRunner', max_epochs=20)