optimizer = t.optim.SGD(net.parameters(), lr=0.2) for key, value in optimizer.state_dict().items(): print(key, value) for i, param_group in enumerate(optimizer.param_groups): print(i+1) print(param_group) 1、optimizer.state_dict() """ state {} param_groups [{'lr': 0.2, 'mom...
state_dict”的键）。您可以使用.keys（）方法打印字典键，并检查检查点是否包含“optimizer_state_dict...
state_dict”的键）。您可以使用.keys（）方法打印字典键，并检查检查点是否包含“optimizer_state_dict...
set_optimizer_state_dict( model=self.model, optimizers=optimizer, optim_state_dict=optim_state_dict, options=StateDictOptions( full_state_dict=self.fsdp_state_dict_type == 'full', strict=strict, cpu_offload=True, ), ) we hit an error with this approach in the below function: ...
nn.Module.load_state_dict和optim.Optimizer.load_state_dict的行为是不同的。前者 * 返回 * 预期和...
A proposal addressing Issue #1489: Optimizer should track parameter names and not id. (also mentioned in here: [RFC] Introducing FQNs/clarity eyeglasses to optim state_dict Summary This PR introduc...
model.load_state_dict({k.replace('module.', ''): v for k, v in state_dict.items()}) 1. 2. 方案2. 训练好的模型文件好像字典键值有很多个,如optimizer,epoch,args等,我们只需要模型参数文件state_dict state_dict = torch.load(new_model) ...
这个错误一般是发生在optimizer.load_state_dict(checkpoint['optimizer'])优化器load的时候,定义的优化器里面的参数和加载进来的模型优化器里面的参数数量不匹配。 需要我们检查模型里面定义的参数,我的报错是因为训练的时候定义了一个没有在forward里面使用的linear层,后面resume的时候把这个线性层注释掉了导致加载的参数...
defload_state_dict(self,state_dict):r"""Loads the optimizer state.Args:state_dict (dict): optimizer state. Should be an object returnedfrom a call to :meth:`state_dict`."""# deepcopy, to be consistent with module APIstate_dict=deepcopy(state_dict)# Validate the state_dictgroups=self...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - [BE] Test foreach optimizer for FSDP1 optimizer state_dict (#132933) · pytorch/pytorch@9e584d0