写一个验证数据在基于pytorch中lstm模型训练的代码

答案：下面是一个使用PyTorch中LSTM模型训练验证数据的示例代码：# 定义模型
model = torch.nn.LSTM(input_size, hidden_size, num_layers, batch_first=True)# 设置损失函数
criterion = torch.nn.MSELoss()# 构建训练数据
train_data = torch.tensor(X_train, dtype=torch.float).view(batch_size, -1, input_size)
train_labels = torch.tensor(y_train, dtype=torch.float).view(batch_size, -1, output_size)# 训练模型
for epoch in range(num_epochs):
# 将模型设置为训练模式
model.train()
# 运行模型
out = model(train_data)
# 计算损失
loss = criterion(out, train_labels)
# 打印损失
print('Epoch: ', epoch, ' Loss: ', loss.item())
# 计算梯度
loss.backward()
# 优化权重
optimizer.step()# 验证数据
val_data = torch.tensor(X_val, dtype=torch.float).view(batch_size, -1, input_size)
val_labels = torch.tensor(y_val, dtype=torch.float).view(batch_size, -1, output_size)# 测试模型
with torch.no_grad():
out = model(val_data)
loss = criterion(out, val_labels)
print('Validation Loss: ', loss.item())