使用torch,实现音频分类,给出代码示例

用PyTorch实现音频分类，可以参照以下代码示例：import torch
import torch.nn as nn
# 加载训练和测试数据
train_data, test_data = load_data()
# 定义网络模型
net = Net()
# 定义损失函数和优化器
criterion = nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(net.parameters(), lr=0.001)
# 训练模型
for epoch in range(num_epochs):
for i, (inputs, labels) in enumerate(train_data):
# 前向传播
outputs = net(inputs)
# 计算损失
loss = criterion(outputs, labels)
# 反向传播
optimizer.zero_grad()
loss.backward()
optimizer.step()
# 测试模型
correct = 0
total = 0
with torch.no_grad():
for i, (inputs, labels) in enumerate(test_data):
outputs = net(inputs)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels).sum().item()
print('准确率：{:.2f}%'.format(100 * correct / total))