open-mmlab/mmdetection · error · TypeError

pretrained must be a str or None

Error message

pretrained must be a str or None

What it means

ResLayer (shared head) accepts pretrained as either a str checkpoint path (converted into an init_cfg) or None; any other type raises TypeError in __init__.

Source

Thrown at mmdet/models/roi_heads/shared_heads/res_layer.py:67

        self.add_module(f'layer{stage + 1}', res_layer)

        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 a deprecated, '
                          'please use "init_cfg" instead')
            self.init_cfg = dict(type='Pretrained', checkpoint=pretrained)
        elif pretrained is None:
            if init_cfg is None:
                self.init_cfg = [
                    dict(type='Kaiming', layer='Conv2d'),
                    dict(
                        type='Constant',
                        val=1,
                        layer=['_BatchNorm', 'GroupNorm'])
                ]
        else:
            raise TypeError('pretrained must be a str or None')

    def forward(self, x):
        res_layer = getattr(self, f'layer{self.stage + 1}')
        out = res_layer(x)
        return out

    def train(self, mode=True):
        super(ResLayer, self).train(mode)
        if self.norm_eval:
            for m in self.modules():
                if isinstance(m, nn.BatchNorm2d):
                    m.eval()

View on GitHub (pinned to cfd5d3a985)

Solutions

1. Pass a str path: pretrained='torchvision://resnet50' or a local .pth path string
2. Pass pretrained=None and use init_cfg=dict(type='Pretrained', checkpoint=...) instead
3. Convert Path objects with str(path) before passing

Example fix

# before
shared_head=dict(type='ResLayer', pretrained={'ckpt': 'r50.pth'})
# after
shared_head=dict(type='ResLayer', pretrained='r50.pth')

p = cfg.get('pretrained', None)
assert p is None or isinstance(p, str)

def valid_pretrained(v) -> bool: return v is None or isinstance(v, str)

When it happens

Trigger: shared_head=dict(type='ResLayer', pretrained=123) or pretrained={'checkpoint': ...} or a list of paths.

Common situations: Old-style configs or code passing the newer init_cfg dict into pretrained; programmatic construction passing a Path object or bool.

Understand the failure class

Background: Invalid argument type errors: "must be of type string", "expected X, got Y", and ERR_INVALID_ARG_TYPE explained — this error's family across 15 libraries.

Related errors

• LoadImageFromFile is not found in the test pipeline
• Visualization needs the "visualizer" termdefined in the conf
• config must be a filename or Config object, but got {type(co
• Unrecognized dataset: {dataset}
• The `file_client_args` is deprecated, please use `backend_ar

AI-assisted analysis of open-mmlab/mmdetection@cfd5d3a985 (2026-08-27). Data as JSON: /api/errors/4247ba5b9e20e4bd. Report an issue: GitHub.