from torch.utils.tensorboard import SummaryWriter # Create a SummaryWriter object writer = SummaryWriter() # Log the loss and accuracy for epoch in range(num_epochs): # Train the model and compute the loss and accuracy # ... # Log the loss and accuracy using add_text() writer.add_text('Loss and Accuracy', f'Epoch {epoch}: loss={loss}, accuracy={accuracy}') # Close the SummaryWriter writer.close()In this example, we created a `SummaryWriter` object and used the `add_text()` method to log the loss and accuracy values for each epoch during training. We passed a string that describes the content of the text entry ('Loss and Accuracy') and the actual text to log, which was formatted using f-strings. Overall, `torch.utils.tensorboard.SummaryWriter` is part of the `torch` library in Python, which is a popular framework for deep learning.