在处理“missing key(s) in state_dict”这类问题时,通常是因为在尝试加载一个预训练模型的状态字典(state_dict)到另一个模型中时,两个模型的结构不完全匹配。这里有几个步骤和考虑点可以帮助你解决这个问题: 1. 确认state_dict中缺失的key 首先,需要打印出加载state_dict时缺失的keys。这通常在加载过程中由PyT...
我们可以通过以下步骤来解决"Missing key(s) in state_dict"错误: 导入所需的库和模块: pythonCopy codeimporttorchimporttorchvision.modelsasmodels 创建模型的实例,并加载之前保存的state_dict: pythonCopy code model=models.resnet50()# 创建一个ResNet实例state_dict=torch.load('model.pth')# 加载之前保存的...
3. 使用strict=False:当调用load_state_dict方法时,你可以设置strict=False。这样,即使state_dict中的某些键不存在于当前模型中,也不会引发错误。但是,请注意,这可能会导致某些层没有加载权重。 # 使用strict=False加载state_dict model.load_state_dict(state_dict, strict=False) 4. 使用部分加载:如果你只想加...
state_dict=torch.load('model.pth')model.load_state_dict(state_dict) 通过以上方法,我们可以成功解决"Missing key(s) in state_dict"错误,并成功加载模型的状态。 总结: 当遇到"Missing key(s) in state_dict"错误时,首先要分析模型的架构是否一致,然后确保在加载模型时使用了正确的模型类。根据实际情况,对...
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for Generator: Missing key(s) in state_dict: "fc4.weight", "fc4.bias", "fc5.weight", "fc5.bias". ...
state_dict = torch.load('myfile.pth') # create new OrderedDict that does not contain `module.` from collections import OrderedDict new_state_dict = OrderedDict() for k, v in state_dict.items(): name = k[7:] # remove `module.` ...
Missing key(s) in state_dict: "module.backbone.layers.0.stage_1.layers.0.weight", 这是因为加载的预训练模型之前使用了torch.nn.DataParallel(),而此时没有使用,所以可以加上该模块或者去掉。 1,加上torch.nn.DataParallel()模块 model = torch.nn.DataParallel(model) ...
model = nn.DataParallel(model) cudnn.benchmark =True 否则加载时会出现错误: RuntimeError: Error(s) in loading state_dict for ResNet: Missing key(s) in state_dict: xxxxxxxx Unexpected key(s) in state_dict: xxxxxxxxxx
模型代码及checkpoint: GitHub - hanjanghoon/BERT_FP: Fine-grained Post-training for Improving Retrieval-based Dialogue Systems - NAACL 2021 git上提供的模型,加载报错: RuntimeError: Error(s) in loading state_dict for BertModel:Missing key(s) in state_dict: "embeddings.position_ids". ...
Unexpected key(s) in state_dict: "up_blocks.0.attentions.2.conv.bias", "up_blocks.0.attentions.2.conv.weight". Any help on this?Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees...