CentOS上如何运行PyTorch示例代码

<pre class="brush:php;toolbar:false;">sudo yum install python3

<pre class="brush:php;toolbar:false;">sudo yum install python3-pip

<pre class="brush:php;toolbar:false;">pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu111

<pre class="brush:php;toolbar:false;">pip3 install torch torchvision torchaudio

<pre class="brush:php;toolbar:false;">python3 -c "import torch; print(torch.__version__)"

<pre class="brush:php;toolbar:false;">import torch
import torch.nn as nn
import torch.optim as optim

# 定义一个简单的神经网络
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = x.view(-1, 784)
        x = torch.relu(self.fc1(x))
        x = self.fc2(x)
        return x

# 创建网络实例
net = Net()

# 定义损失函数和优化器
criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(net.parameters(), lr=0.01)

# 示例输入数据（假设是MNIST数据集的一张图片）
input_data = torch.randn(1, 1, 28, 28)
target = torch.tensor([5])  # 假设目标标签是5

# 前向传播
output = net(input_data)
loss = criterion(output, target)

# 反向传播和优化
optimizer.zero_grad()
loss.backward()
optimizer.step()

print(f'Loss: {loss.item()}')

example.py

<pre class="brush:php;toolbar:false;">python3 example.py