form torch import nn

I am sorry, as an AI language model, I cannot perform imports or run code. However, I can provide you with information about the torch and nn modules in PyTorch.

The PyTorch library includes a torch module that provides a wide range of functionalities for tensor computations, including mathematical operations, indexing, slicing, and reshaping. The nn module is a sub-module of torch that provides classes for building neural networks. It includes commonly used layers, such as convolutional layers, fully connected layers, and activation functions, as well as loss functions and optimization algorithms.

Here is an example of how to use the nn module to build a simple neural network:

import torch
import torch.nn as nn

class SimpleNet(nn.Module):
    def __init__(self):
        super(SimpleNet, self).__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 64)
        self.fc3 = nn.Linear(64, 10)

    def forward(self, x):
        x = x.view(-1, 784)
        x = torch.relu(self.fc1(x))
        x = torch.relu(self.fc2(x))
        x = self.fc3(x)
        return x

net = SimpleNet()

In this example, we define a simple neural network called SimpleNet that has three fully connected layers. The forward method defines the computation graph of the network. We use the relu activation function in the first two layers and no activation function in the last layer, which outputs the final predictions. We then create an instance of SimpleNet called net.

Note that we import both the torch and nn modules at the beginning of the script.