[discussion] Refactor spectral_norm to use the newly merged lowrank solvers and proposal for Linear Algebra Cookbook page #36314
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module: linear algebra
Issues related to specialized linear algebra operations in PyTorch; includes matrix multiply matmul
triaged
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LOBPCG variants were merged in #29488
However, spectral_norm implementation contains an older power iteration implementation to get an estimate for leading eigenvalue.
I propose (also in #8049 (comment)) to either:
In general I think it'd be nice to have some dedicated page "Linear Algebra PyTorch Cookbook" and detail for typical linear algebra tasks (linear system solvers, eigenproblem solvers, ...) what methods are currently supported (wrt sparsity, symmetric, p.s.d, problem sizes, differentiability, space/time complexity, cpu/gpu support, batchability, what external libraries are used, is parallelization across batches used, numerical stability considerations, etc)
cc @vincentqb @vishwakftw @ssnl @jianyuh @nikitaved
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