Training VGGT from scratch

Hi, thank you for sharing such great work! I'm interested in the from-scratch training recipe for VGGT, and had a few clarification questions on the config:

• the paper mentions that 64 A100s were used, with [2,24] frames sampled per sequence and "maintaining the constant total of 48 frames within each batch"
  • does this mean that the effective batch size was 64 gpus * (48 frames/gpu) / ([2, 24] frames/sequence) = [128, 1536] sequences? Or were the samples reduced in a different way?
• is there a general range of loss magnitudes that we should expect to indicate proper convergence at the end? Especially for the tracking loss term, as there is not a clean version integrated into the codebase yet.
• was data from the list here #36 sampled uniformly over the course of training?