What are the basics of visualization in PyTorch?

What are the basics of visualization in PyTorch?

In PyTorch, visualization is essential for understanding model performance. You can use libraries like Matplotlib and TensorBoard.

How do I use Matplotlib with PyTorch?

You can use Matplotlib to plot tensors. First, convert your PyTorch tensor to a NumPy array using .numpy().

Can you show me a simple example?

Sure! Here's a basic example:

import torch
import matplotlib.pyplot as plt

# Create a tensor
x = torch.linspace(-10, 10, 100)
y = torch.sin(x)

# Convert to NumPy and plot
plt.plot(x.numpy(), y.numpy())
plt.title('Sine Wave')
plt.show()

What about using TensorBoard for visualization?

TensorBoard is great for visualizing training metrics. You can log metrics using SummaryWriter and then launch TensorBoard to view them.