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* add huber loss and huber_c compute to train_util * add reduction modes * add huber_c retrieval from timestep getter * move get timesteps and huber to own function * add conditional loss to all training scripts * add cond loss to train network * add (scheduled) huber_loss to args * fixup twice timesteps getting * PHL-schedule should depend on noise scheduler's num timesteps * *2 multiplier to huber loss cause of 1/2 a^2 conv. The Taylor expansion of sqrt near zero gives 1/2 a^2, which differs from a^2 of the standard MSE loss. This change scales them better against one another * add option for smooth l1 (huber / delta) * unify huber scheduling * add snr huber scheduler --------- Co-authored-by: Kohya S <52813779+kohya-ss@users.noreply.github.com>