python-pytorchHow can I use PyTorch with Python 3.10?

PyTorch is a Python-based open source deep learning platform that provides maximum flexibility and speed. It is compatible with Python 3.10, and can be used to develop and train deep learning models.

To use PyTorch with Python 3.10, first install the PyTorch package with the command:

pip install torch

Then, import the PyTorch library into your Python code with the following command:

import torch

The following code block shows an example of how to use PyTorch with Python 3.10 to define and train a simple neural network:

import torch

# define the neural network
model = torch.nn.Sequential(
    torch.nn.Linear(2, 3),
    torch.nn.ReLU(),
    torch.nn.Linear(3, 1)
)

# define the loss and optimizer
loss_fn = torch.nn.MSELoss(reduction='sum')
optimizer = torch.optim.SGD(model.parameters(), lr=1e-4)

# train the model
for t in range(500):
    # forward pass
    y_pred = model(x)

    # compute and print loss
    loss = loss_fn(y_pred, y)
    print(t, loss.item())

    # zero gradients, perform a backward pass, and update the weights
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()

Code explanation

1. import torch: imports the PyTorch library
2. model = torch.nn.Sequential(...): defines the neural network
3. loss_fn = torch.nn.MSELoss(reduction='sum'): defines the loss function
4. optimizer = torch.optim.SGD(...): defines the optimizer
5. y_pred = model(x): performs a forward pass
6. loss = loss_fn(y_pred, y): computes the loss
7. optimizer.zero_grad(): zeros the gradients
8. loss.backward(): performs a backward pass
9. optimizer.step(): updates the weights

Helpful links

• PyTorch Documentation: https://pytorch.org/docs/stable/index.html
• PyTorch Tutorials: https://pytorch.org/tutorials/

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