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Flamehaven-Tensor-Canon

Universal Data Governance Engine ∴ Enforcing structural covenants and detecting drift (MMD) for PyTorch & NumPy pipelines.

GitHub RepositoryREADME

About This Work

Universal Data Governance Engine ∴ Enforcing structural covenants and detecting drift (MMD) for PyTorch & NumPy pipelines.

aidata-qualitydata-validationdrift-detectionmlopsmmdnumpypythonpytorchschematensorvalidation

Repository Overview

Universal Data Governance Engine ∴ Enforcing structural covenants and detecting drift (MMD) for PyTorch & NumPy pipelines.

Use & Documentation

Detailed installation, commands, examples, and deeper usage notes live in the repository README and docs.

Open README

README Map

  • ⚡ Why Tensor Canon?
  • 📦 Installation
  • 🚀 Quick Start (30 seconds)
  • 1. Shape Validation - Catch Bugs Early
  • 2. Drift Detection - Monitor Data Quality
  • 3. Large-Scale Drift Detection (Linear Time)

Key Signals

  • Drift Detection : Only library with built-in MMD for real-time distribution monitoring
  • O(N) Linear MMD : Random Fourier Features for large-scale datasets ( 10k samples)
  • Defensive Validation : Auto-converts numpy/lists, handles 0D/1D edge cases
  • Developer-Friendly Errors : Tells you exactly what's wrong and where
  • Validation Overhead : <0.5ms per check (negligible in training loops)

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