我正在基于PyTorch开发一个聊天机器人，即使在NeuralNet类中添加了super，我仍然无法找出属性错误的原因。我使用的是Jupyter Notebook进行这个项目。

这是我目前的代码，来自model.ipynb和train.ipynb的部分内容

class NeuralNet(nn.Module):    def __init__(self, input_size, hidden_size, num_classes):        super().__init__()        self.l1 = nn.Linear(input_size, hidden_size)         self.l2 = nn.Linear(hidden_size, hidden_size)         self.l3 = nn.Linear(hidden_size, num_classes)        self.relu = nn.ReLU()        #Trainimport torchimport torch.nn as nnfrom torch.utils.data import Dataset, DataLoaderfrom ipynb.fs.full.model import NeuralNetclass ChatDataset(Dataset):    def __init__(self):        self.n_samples = len(x_train)        self.x_data = x_train        self.y_data = y_train    #hyperParametersbatch_size = 8hidden_size = 8output_size = len(tags)input_size = len(all_words)# print(input_size, len(all_words))# print(output_size, tags)learning_rate = 0.001num_epochs = 1000    dataset = ChatDataset()train_loader = DataLoader(dataset = dataset , batch_size=batch_size, shuffle=True, num_workers=2)  model = NeuralNet(input_size, hidden_size, output_size)``` ERROR:~\Untitled Folder\model.ipynb in __init__(self, input_size, hidden_size, num_classes)      9    "source": [     10     "import torch\n",---> 11     "import torch.nn as nn"     12    ]     13   },~\anaconda3a\lib\site-packages\torch\nn\modules\module.py in __setattr__(self, name, value)   1234             if isinstance(value, Module):   1235                 if modules is None:-> 1236                     raise AttributeError(   1237                         "cannot assign module before Module.__init__() call")   1238                 remove_from(self.__dict__, self._parameters, self._buffers, self._non_persistent_buffers_set)AttributeError: cannot assign module before Module.__init__() call

回答：

这很可能是由于你在NeuralNet的__init__函数中没有在注册子模块之前调用super().__init__。请参阅这里获取更多详细信息。

唯一缺少的部分是ChatDataset类上的__len__函数。除此之外，提供的代码运行正常。