How to calculate the loss

i didn't fully understand how the loss is calculated

regular diffusion models takes input image adding noise and during backward stage we learn how to undo that noise
the loss calculate base on how good we learn that noise for every stage in T

so what i don't understand is what the part of the target image ? ( we add the noise to input image )

that is what says in the paper


I also not sure what is it "task-specific conditions cf" in the loss , is it the target image ?

thanks

Start by reviewing the linked paper excerpt and the existing comment discussion, focusing on the roles of the noisy input, target image, and task-specific conditions. Done means documenting a clear explanation of how the loss is calculated and resolving whether the target image is the task-specific condition; no repository file or test is named.

Written by the indexing model from the issue text.