Why fused DeepLIFT is fast: PyTorch does the op fusion when attribution is a computation graph
jmschreiber91 · x · 2026-10-26
jmschreiber91 closes the thread by explaining why fused DeepLIFT works: PyTorch excels at optimizing general computation graphs, so once DeepLIFT is defined on a specific model as a computation graph, PyTorch automatically merges and fuses the operations — eliminating the many small ops that plague hook-based implementations.
Related event: Fused DeepLIFT: Rewriting Attribution as a Computation Graph for 7x Speedup(4 posts)→
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