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- _base_ = './dino-4scale_r50_8xb2-12e_coco.py'
- fp16 = dict(loss_scale=512.)
- pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth' # noqa
- num_levels = 5
- model = dict(
- num_feature_levels=num_levels,
- backbone=dict(
- _delete_=True,
- type='SwinTransformer',
- pretrain_img_size=384,
- embed_dims=192,
- depths=[2, 2, 18, 2],
- num_heads=[6, 12, 24, 48],
- window_size=12,
- 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=(0, 1, 2, 3),
- # Please only add indices that would be used
- # in FPN, otherwise some parameter will not be used
- with_cp=True,
- convert_weights=True,
- init_cfg=dict(type='Pretrained', checkpoint=pretrained)),
- neck=dict(in_channels=[192, 384, 768, 1536], num_outs=num_levels),
- encoder=dict(layer_cfg=dict(self_attn_cfg=dict(num_levels=num_levels))),
- decoder=dict(layer_cfg=dict(cross_attn_cfg=dict(num_levels=num_levels))))
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