how to use local .pth file, not to use model_urls like https://s3... to load weight file to train network

[pistachio0812]

when i run train.py to train network, i meet this error:
Downloading: "F:\ssd-v13\model_data\ssd_weights.pth" to C:\Users\zzh/.torch\models\ssd_weights.pth
Traceback (most recent call last):
File "train.py", line 128, in
main()
File "train.py", line 119, in main
model = train(cfg, args)
File "train.py", line 25, in train
model = build_detection_model(cfg)
File "F:\ssd-v13\ssd\modeling\detector_init_.py", line 10, in build_detection_model
return meta_arch(cfg)
File "F:\ssd-v13\ssd\modeling\detector\ssd_detector.py", line 12, in init
self.backbone = build_backbone(cfg)
File "F:\ssd-v13\ssd\modeling\backbone_init_.py", line 13, in build_backbone
return registry.BACKBONES[cfg.MODEL.BACKBONE.NAME](cfg, cfg.MODEL.BACKBONE.PRETRAINED)
File "F:\ssd-v13\ssd\modeling\backbone\frassd_net\frassd_net.py", line 160, in frassd_net
model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1']))
File "F:\ssd-v13\ssd\utils\model_zoo.py", line 61, in load_state_dict_from_url
cached_file = cache_url(url)
File "F:\ssd-v13\ssd\utils\model_zoo.py", line 55, in cache_url
download_url_to_file(url, cached_file, hash_prefix, progress=progress)
File "D:\anaconda\envs\pytorch-gpu\lib\site-packages\torch\hub.py", line 437, in download_url_to_file
u = urlopen(req)
File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 222, in urlopen
return opener.open(url, data, timeout)
File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 525, in open
response = self._open(req, data)
File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 547, in _open
return self._call_chain(self.handle_open, 'unknown',
File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 502, in _call_chain
result = func(*args)
File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 1425, in unknown_open
raise URLError('unknown url type: %s' % type)
urllib.error.URLError:

train.py:
model_urls ={
'vgg': 'https://s3.amazonaws.com/amdegroot-models/vgg16_reducedfc.pth',
'ssdv1': 'F:\ssd-v13\model_data\ssd_weights.pth',
'ssd300_voc0712': '../model_data/vgg_ssd300_voc0712.pth',
'ssd300_coco2014': '../model_data/vgg_ssd300_coco_trainval35k.pth',
'ssd512_voc0712': '../model_data/vgg_ssd512_voc0712.pth',
'ssd512_coco2014': '../model_data/vgg_ssd512_coco_trainval35k.pth',
}

@registry.BACKBONES.register('my_net')
def my_net(cfg, pretrained=True):
model = MY_NET(cfg)
if pretrained:
model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1']))
return model

how to solove it, thanks!!!!

[ksv87]

try this

@registry.BACKBONES.register('my_net')
def my_net(cfg, pretrained=True):
    model = MY_NET(cfg)
    if pretrained:
        if model_urls['ssdv1'].startswith("http"):
            model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1']))
        else:
            model.load_state_dict(torch.load(model_urls['ssdv1']), strict=False)
    return model