How do I implement multi-scale loss in PyTorch to improve image generation

Question

Can you tell me how I implement multi-scale loss in PyTorch to improve image generation?

Answer 1

To implement multi-scale loss in PyTorch, compare images at multiple resolutions by downscaling the real and generated images and computing losses at each scale. This helps capture both fine details and global structures.

Here is the code snippet you can refer to:

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

• Resizing: Use F.interpolate to downscale images to multiple resolutions.
• Loss Function: Compute a loss (e.g., L1 or L2) at each resolution and sum them.
• Benefits: Captures both global structure (low resolution) and fine details (high resolution).

Hence, by referring to the above, you can implement multi-scale loss in PyTorch to improve image generation.