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pytorch-hessian-eigenthings

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Preview status · 2026-05-16

What is pytorch-hessian-eigenthings?

hessian-eigenthings is a PyTorch library that provides efficient and scalable computation of eigendecomposition for the Hessian matrix and related curvature operators in neural networks. T...
Best fit: Users who want source-backed project understanding before installing it.
Capability added to an AI workflow: skill, recipe, host_instruction, eval, preflight
Evidence base: https://github.com/noahgolmant/pytorch-hessian-eigenthings, https://news.ycombinator.com/item?id=48132232, https://github.com/noahgolmant/pytorch-hessian-eigenthings#readme
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Best forUsers who want source-backed project understanding before installing it.

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Capabilityskill, recipe, host_instruction, eval, preflight

pytorch-hessian-eigenthings

Repositorynoahgolmant/pytorch-hessian-eigenthings

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What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Introduction to hessian-eigenthings

Related topics: Curvature Matrices Explained, System Architecture

Sources: [README.md:1]()

Installation Guide

Related topics: Introduction to hessian-eigenthings

Sources: [CONTRIBUTING.md:5-12]()

Curvature Matrices Explained

Related topics: Why Hessian-Vector Products, Curvature Operators

Sources: [hessian_eigenthings/operators/hessian.py:1-30](https://github.com/noahgolmant/pytorch-hessian-eigenthings/blob/main/hessian_eigenthings/operators/hessian.py)

Why Hessian-Vector Products

Related topics: Curvature Matrices Explained, Eigendecomposition Algorithms

Sources: [hessian_eigenthings/operators/hessian.py:1-50]()

System Architecture

Related topics: Curvature Operators, Eigendecomposition Algorithms, Loss Functions

Sources: [hessian_eigenthings/operators/hessian.py:1-50]()

Sources: https://github.com/noahgolmant/pytorch-hessian-eigenthings, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

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Community Discussion Evidence

9 source-linked items

Review these external discussions before using pytorch-hessian-eigenthings with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
ValueError: PENet on the Kitti benchmark suite
github / github_issue
02
RuntimeError: One of the differentiated Tensors appears to not have been
github / github_issue
03
AttributeError: 'HVPOperator' object has no attribute 'zero_grad'
github / github_issue
04
Python Error: the following arguments are required: experimentname
github / github_issue
05
v1.0.0a5 — comprehensive LLM-scale memory fixes + regression tests
github / github_release
06
v1.0.0a4 — backend handles CPU-generator + CUDA-tensor combo
github / github_release
07
v1.0.0a3 — fix lanczos OOM
github / github_release
08
v1.0.0a2 — packaging fix
github / github_release
09
Project risk needs validation
GitHub / issue

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Official start command · https://github.com/noahgolmant/pytorch-hessian-eigenthings#readme · verified: yes

Human Manual

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8+ sections · Human Manual