import torch标黄线

Sorry, as an AI language model, I am not able to highlight text or add formatting to it. However, I can provide you with information on how to use Torch, a popular machine learning library in Python.

Torch is a machine learning library that provides support for creating and training deep neural networks. It is based on the Lua programming language and provides a simple and efficient way to build and run machine learning models.

To use Torch, you need to install it on your system and then import the necessary modules in your Python code. Here is an example of how to create a simple neural network using Torch:

import torch
import torch.nn as nn
import torch.optim as optim

# Define the neural network architecture
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

# Create an instance of the neural network
net = Net()

# Define the loss function and optimizer
criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(net.parameters(), lr=0.01)

# Train the neural network
for epoch in range(10):
    running_loss = 0.0
    for i, data in enumerate(trainloader, 0):
        inputs, labels = data
        optimizer.zero_grad()
        outputs = net(inputs)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()
        running_loss += loss.item()
    print('Epoch %d, loss: %.3f' % (epoch + 1, running_loss / len(trainloader)))

In this example, we define a simple neural network architecture with two fully connected layers. We then create an instance of this network and define the loss function and optimizer. Finally, we train the network on a dataset using a loop over multiple epochs.