How do I handle latent space exploration in GAN models

Question

With the help of python programming can you tell me How do I handle latent space exploration in GAN models?

Answer 1

To handle latent space exploration in GAN models, you can interpolate between latent vectors or manipulate specific dimensions of the latent space to observe their effects on generated outputs.

Here is the code reference you can refer to:

In the above code, we are using the following key techniques:

• Latent Interpolation: Smoothly blends features between two latent vectors to explore latent space transitions.
• Dimension Manipulation: Modify specific dimensions of z to study their impact on generation.
• Visualization: Plot generated images to observe the effects of latent space changes.

Hence, by referring to the above, you can handle latent space exploration in GAN models.