load_from, pretrained_loc = _resolve_pretrained_source(pretrained_cfg) 解析出来load_from,根据load_from进行参数加载 因为pretrained_cfg中存在hf相关参数,所以解析得到的load_from是hf-hub,这里中断打印一下也可以发现是load_from为hf-hub 所以问题变得明了了,只要我们在这里修改代码,强制赋值load_from为url,就...
'architecture': 'vit_base_patch16_224', 'tag': 'augreg2_in21k_ft_in1k', 'custom_load': False, 'input_size': (3, 224, 224), 'fixed_input_size': True, 'interpolation': 'bicubic', 'crop_pct': 0.9, 'crop_mode': 'center', 'mean': (0.5, 0.5, 0.5), 'std': (0.5, 0.5,...
from ._builder import build_model_with_cfg, load_pretrained, load_custom_pretrained, resolve_pretrained_cfg, \ set_pretrained_download_progress, set_pretrained_check_hash from ._factory import create_model, parse_model_name, safe_model_name from ._features import FeatureInfo, FeatureHooks, Feature...
net = timm.create_model(name, pretrained=True) 会从huggingface自动下载model.safetensors,有时候由于网络问题,会访问不了,进而报错。 解决方法:(需要能登录 huggingface.co, 下载预训练权重) 使用情况:电脑1能访问 huggingface.co,现在代码想迁移到电脑2,但电脑2访问不了 huggingface.co ...
print(pretrained_cfg) 執行後輸出配置資訊: {'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnet50_a1_0-14fe96d1.pth', 'hf_hub_id': 'timm/resnet50.a1_in1k', 'architecture': 'resnet50', 'tag': 'a1_in1k', 'custom_load': False,...
_logger.warning("Removing representation layer for fine-tuning.") repr_size = None model = build_model_with_cfg( VisionTransformer, variant, pretrained, default_cfg=default_cfg, representation_size=repr_size, pretrained_filter_fn=checkpoint_filter_fn, pretrained_custom_load=...
{'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnet50_a1_0-14fe96d1.pth', 'hf_hub_id': 'timm/resnet50.a1_in1k', 'architecture': 'resnet50', 'tag': 'a1_in1k', 'custom_load': False, 'input_size': (3, 224, 224), 'test...
{'url': 'https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnet50_a1_0-14fe96d1.pth', 'hf_hub_id': 'timm/resnet50.a1_in1k', 'architecture': 'resnet50', 'tag': 'a1_in1k', 'custom_load': False, 'input_size': (3, 224, 224), 'test...
timm.create_model('resnet50', pretrained=True, in_chans=3, num_classes=6) 这里的主要参数有四个: 第一个是模型名称model_name, 第二个是是否预训练pretrained, 第三个是输入图像的通道数in_chans, 第四个是分类类别数num_classes,指最后输出FC层的维度。
(self): if self._optimizer is None: if self._img_cls_cfg.pretrained and not self._custom_net \ and (self._train_cfg.transfer_lr_mult != 1 or self._train_cfg.output_lr_mult != 1): # adjust feature/last_fc learning rate multiplier in optimizer self._logger.debug(f'Reduce netw...