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How-To Guides

How-to guides are goal-oriented recipes. Each one solves a specific task and assumes you already know the basics from the Getting Started tutorial.

Available guides

  • Use Focal Loss: SigmoidFocalLoss for binary/multi-label, SoftmaxFocalLoss for multiclass, with alpha, gamma, and mean_positive reduction
  • Use Ranking Losses: SmoothAPLoss, RecallAtQuantileLoss, and PAUCAtBudgetLoss with queue sizing, band selection, and temperature guidance
  • Weight Samples by Value: sample_weight for value-weighted objectives (e.g. dollar-weighted recall@budget) across every loss
  • Configure Warmup and Blending: tune phase schedules, blend epochs, and temperature decay in LossWarmupWrapper
  • Train with DDP: multi-GPU all-gather setup for all losses
  • Log Per-Class Metrics: retrieve per-class loss tensors without a second forward pass
  • Migrate from BCE / CrossEntropyLoss: drop-in migration checklist, common mistakes, and a decision table for choosing the right loss