鍦≒yTorch涓鐞嗘椂闂村簭鍒楁暟鎹换鍔￠€氬父闇€瑕佷娇鐢?code>torch.nn.RNN, torch.nn.LSTM, torch.nn.GRU绛夐€掑綊绁炵粡缃戠粶妯″潡锛屼互鍙?code>torch.utils.data.Dataset鍜?code>torch.utils.data.DataLoader绛夋暟鎹姞杞藉伐鍏枫€?/p>

浠ヤ笅鏄竴涓畝鍗曠殑绀轰緥锛屾紨绀哄浣曚娇鐢≒yTorch澶勭悊涓€涓椂闂村簭鍒楁暟鎹换鍔★細

1. 鍒涘缓涓€涓嚜瀹氫箟鐨?code>Dataset绫伙紝鐢ㄤ簬鍔犺浇鏃堕棿搴忓垪鏁版嵁锛?/li>

import torch
from torch.utils.data import Dataset

class TimeSeriesDataset(Dataset):
    def __init__(self, data):
        self.data = data
    
    def __len__(self):
        return len(self.data)
    
    def __getitem__(self, idx):
        return self.data[idx]

2. 瀹氫箟涓€涓寘鍚玆NN鐨勬ā鍨嬶細

import torch.nn as nn

class RNNModel(nn.Module):
    def __init__(self, input_size, hidden_size, num_layers, output_size):
        super(RNNModel, self).__init__()
        self.rnn = nn.RNN(input_size, hidden_size, num_layers, batch_first=True)
        self.fc = nn.Linear(hidden_size, output_size)
    
    def forward(self, x):
        out, _ = self.rnn(x)
        out = self.fc(out[:, -1, :])
        return out

3. 鍑嗗鏁版嵁骞惰缁冩ā鍨嬶細

# 瀹氫箟瓒呭弬鏁?/span>
input_size = 1
hidden_size = 64
num_layers = 1
output_size = 1
num_epochs = 100
learning_rate = 0.001

# 鍑嗗鏁版嵁
data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
dataset = TimeSeriesDataset(data)
dataloader = DataLoader(dataset, batch_size=1, shuffle=True)

# 鍒濆鍖栨ā鍨?/span>
model = RNNModel(input_size, hidden_size, num_layers, output_size)

# 瀹氫箟鎹熷け鍑芥暟鍜屼紭鍖栧櫒
criterion = nn.MSELoss()
optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)

# 璁粌妯″瀷
for epoch in range(num_epochs):
    for i, batch in enumerate(dataloader):
        inputs = batch.float().unsqueeze(2)
        targets = inputs.clone()
        
        outputs = model(inputs)
        loss = criterion(outputs, targets)
        
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
        
        if (i+1) % 10 == 0:
            print('Epoch [{}/{}], Step [{}/{}], Loss: {:.4f}'.format(epoch+1, num_epochs, i+1, len(dataloader), loss.item()))

鍦ㄤ笂杩扮ず渚嬩腑锛屾垜浠鍏堝垱寤轰簡涓€涓嚜瀹氫箟鐨?code>Dataset绫绘潵鍔犺浇鏃堕棿搴忓垪鏁版嵁锛岀劧鍚庡畾涔変簡涓€涓寘鍚玆NN鐨勬ā鍨?code>RNNModel锛屾渶鍚庡噯澶囨暟鎹苟璁粌妯″瀷銆傚湪璁粌杩囩▼涓紝鎴戜滑浣跨敤浜嗗潎鏂硅宸崯澶卞嚱鏁板拰Adam浼樺寲鍣ㄦ潵浼樺寲妯″瀷銆?/p>