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Explanation

Explanation answers why rather than how. These articles cover design decisions, trade-offs, and the non-obvious behavior behind the library.

Articles

  • Why Imbalanced Losses — why standard cross-entropy fails under class imbalance, and what each loss in this library actually optimizes
  • Memory Queue Design — why a circular buffer is necessary for ranking losses at low positive rates, and how it interacts with DDP
  • Temperature and Soft Ranking — how the sigmoid approximation replaces the discrete rank function and what temperature controls
  • DDP All-Gather and Gradients — why rank-based losses are biased under standard DDP sharding and how all-gather fixes this without breaking autograd