open-mmlab/mmdetection · error · TypeError

pretrained must be a str or None

Error message

pretrained must be a str or None

What it means

SwinTransformer.__init__ raises TypeError when the deprecated `pretrained` argument is not a str or None. str is wrapped into init_cfg; None falls back to the init_cfg parameter. Other types are rejected.

Source

Thrown at mmdet/models/backbones/swin.py:570

        if isinstance(pretrain_img_size, int):
            pretrain_img_size = to_2tuple(pretrain_img_size)
        elif isinstance(pretrain_img_size, tuple):
            if len(pretrain_img_size) == 1:
                pretrain_img_size = to_2tuple(pretrain_img_size[0])
            assert len(pretrain_img_size) == 2, \
                f'The size of image should have length 1 or 2, ' \
                f'but got {len(pretrain_img_size)}'

        assert not (init_cfg and pretrained), \
            'init_cfg and pretrained cannot be specified at the same time'
        if isinstance(pretrained, str):
            warnings.warn('DeprecationWarning: pretrained is deprecated, '
                          'please use "init_cfg" instead')
            self.init_cfg = dict(type='Pretrained', checkpoint=pretrained)
        elif pretrained is None:
            self.init_cfg = init_cfg
        else:
            raise TypeError('pretrained must be a str or None')

        super(SwinTransformer, self).__init__(init_cfg=init_cfg)

        num_layers = len(depths)
        self.out_indices = out_indices
        self.use_abs_pos_embed = use_abs_pos_embed

        assert strides[0] == patch_size, 'Use non-overlapping patch embed.'

        self.patch_embed = PatchEmbed(
            in_channels=in_channels,
            embed_dims=embed_dims,
            conv_type='Conv2d',
            kernel_size=patch_size,
            stride=strides[0],
            norm_cfg=norm_cfg if patch_norm else None,
            init_cfg=None)

View on GitHub (pinned to cfd5d3a985)

Solutions

1. Use init_cfg=dict(type='Pretrained', checkpoint='swin_tiny.pth') and omit pretrained
2. If using pretrained, pass a str URL/path with value None for init_cfg

Example fix

// before
backbone=dict(type='SwinTransformer', pretrained='swin_tiny_patch4_window7_224.pth')
// after
backbone=dict(type='SwinTransformer', init_cfg=dict(type='Pretrained', checkpoint='swin_tiny_patch4_window7_224.pth'))

assert pretrained is None or isinstance(pretrained, str)

When it happens

Trigger: SwinTransformer(pretrained=dict(...)) or pretrained=Path(...); providing both pretrained and a non-None init_cfg.

Common situations: Migrating old Swin configs (mmdet 2.x) that used pretrained='...'; passing a state_dict instead of a path string.

Related errors

• pretrained must be a str or None
• pretrained must be a str or None
• pretrained must be a str or None
• pretrained must be a str or None
• pretrained must be a str or None

AI-assisted analysis of open-mmlab/mmdetection@cfd5d3a985 (2026-08-27). Data as JSON: /api/errors/e881adf81834fe4a. Report an issue: GitHub.