实现pytorch时出现空参数问题

import torch
import torch.nn as nn
import numpy as np

x_train = [i for i in range(10)]
x_train = np.array(x_train, dtype=np.float32)
x_train.reshape(-1, 1)
y_train = [2 * i + 1 for i in range(10)]
y_train = np.array(y_train, dtype=np.float32)
y_train.reshape(-1, 1)


class MyModule(nn.Module):
    def __int__(self, input_dim, output_dim):
        super(MyModule, self).__int__()
        self.linear = nn.Linear(1, 1)

    def forward(self, x):
        return self.linear(x)


# 定义网络结果，损失函数，优化器
if torch.cuda.is_available():
    model = MyModule().cuda()
else:
    model = MyModule()
lea = 0.0001
optimizer = torch.optim.SGD(model.parameters(), lr=lea)
criterion = nn.MSELoss()
epochs = 10
for epoch in range(epochs):
    optimizer.zero_grad()
    if torch.cuda.is_available():
        inputs = torch.from_numpy(x_train).cuda()
        labels = torch.from_numpy(y_train).cuda()
    else:
        inputs = torch.from_numpy(x_train)
        labels = torch.from_numpy(y_train)
    outs = model(x_train)
    loss = criterion(labels, y_train)
    loss.backward()
    optimizer.step()
    print('epoch {}\tloss {}'.format(epoch, loss))

pytorch版本 1.12.1+cu116
代码如上，优化器那行报错了，如下。
ValueError: optimizer got an empty parameter list

int是什么鬼？改成__init__，不然你都没有初始化model，导致你的model就是空的