Gradual Pruning Schedule

CLI Equivalent: apr prune --method magnitude --schedule cubic --target-sparsity 0.8 --steps 100 model.apr

What This Demonstrates

Gradual and cubic pruning schedules that incrementally increase sparsity over training steps. Avoids the accuracy shock of one-shot pruning by allowing the model to adapt between pruning rounds.

Run

cargo run --example prune_gradual_schedule

Key APIs

  • CubicSchedule::new(initial, target, start_step, end_step) -- cubic sparsity ramp
  • .sparsity_at(step) -- get target sparsity for current training step
  • GradualPruner::new(schedule) -- pruner that follows the schedule
  • .prune_step(model, step) -- apply pruning at current step

Source

examples/optimize/prune_gradual_schedule.rs