Inquiry about the Definition of "Training Gradient Norm" in SANA-Srint's Figure 3 Subplots

[Hanbo-Cheng]

Hello, I would like to inquire about Figure 3 in SANA-Srint. In the two subplots, does the "training gradient norm" mentioned refer to the gradients of trainable parameters (\theta) during training or the (d_F / d_t )?

Because when calculating the loss, the normalization of d_f/d_t ( g = g / (||g|| + c)) has already been considered. Logically, an excessively large d_f/d_t should not significantly affect training stability. I'm not sure is that right?