nn.Module 的 Pytorch 子类没有属性“参数”

Question

Python 版本：Python 3.8.5
Pytorch 版本：'1.6.0'

我正在定义 LSTM，它是 nn.Module 的子类。我正在尝试创建优化器，但收到以下错误：torch.nn.modules.module.ModuleAttributeError: 'LSTM' object has no attribute 'paramters'

我有两个代码文件，train.py 和 lstm_class.py（包含 LSTM 类）。我将尝试制作一个最小的工作示例，如果有任何其他信息有帮助，请告诉我。

lstm_class.py中的代码：

import torch.nn as nn

class LSTM(nn.Module):

    def __init__(self, vocab_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.2):
        super(LSTM, self).__init__()

        # network size parameters
        self.n_layers = n_layers
        self.hidden_dim = hidden_dim
        self.vocab_size = vocab_size
        self.embedding_dim = embedding_dim


        # the layers of the network
        self.embedding = nn.Embedding(self.vocab_size, self.embedding_dim)
        self.lstm = nn.LSTM(self.embedding_dim, self.hidden_dim, self.n_layers, dropout=drop_prob, batch_first=True)
        self.dropout = nn.Dropout(drop_prob)
        self.fc = nn.Linear(self.hidden_dim, self.vocab_size)



    def forward(self, input, hidden):
        # Defines forward pass, probably isn't relevant

    def init_hidden(self, batch_size):
        #Initializes hidden state, probably isn't relevant

train.py 中的代码

import torch
import torch.optim
import torch.nn as nn
import lstm_class

vocab_size = 1000
embedding_dim = 256
hidden_dim = 256
n_layers = 2

net = lstm_class.LSTM(vocab_size, embedding_dim, hidden_dim, n_layers)
optimizer = torch.optim.Adam(net.paramters(), lr=learning_rate) 

我在上面写的最后一行收到错误。完整的错误消息：

Traceback (most recent call last):
  File "train.py", line 58, in <module>
    optimizer = torch.optim.Adam(net.paramters(), lr=learning_rate)
  File "/usr/local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 771, in __getattr__
    raise ModuleAttributeError("'{}' object has no attribute '{}'".format(
torch.nn.modules.module.ModuleAttributeError: 'LSTM' object has no attribute 'paramters'

任何有关如何解决此问题的提示将不胜感激。同样如上所述，如果还有其他相关的内容，请告诉我。谢谢

Answer 1

不是net.paramters()，是net.parameters():)