Metadata-Version: 2.2
Name: bayesian_dpddm
Version: 1.0.0
Summary: Implements Bayesian D-PDDM for Post-Deployment Deterioration Monitoring of ML models.
Author-email: viet <viet@cs.toronto.edu>
License: MIT License
        
        Copyright (c) 2025 Viet Nguyen
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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Project-URL: homepage, https://github.com/opent03/bayesian_dpddm
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.26.4
Requires-Dist: torch>=2.5.1
Requires-Dist: torchvision>=0.20.1
Requires-Dist: vbll>=0.2.6
Requires-Dist: tqdm>=4.66.5
Requires-Dist: matplotlib>=3.10.0
Requires-Dist: pillow>=11.0.0

# Bayesian D-PDDM

Bayesian implementation of the D-PDDM algorithm for post-deployment deterioration monitoring. Bayesian D-PDDM is a Bayesian approximation to the D-PDDM algorithm which provably monitors model deterioration at deployment time. Bayesian D-PDDM:

- Flags deteriorating shifts in the unsupervised deployment data distribution
- Resists flagging non-deteriorating shifts, unlike classical OOD detection leveraging distances and/or metrics between data distributions. 

## Install

The easiest way to install ``bayesian_dpddm`` is with ``pip``:

``pip install bayesian_dpddm``

You can also install by cloning the GitHub repo:

```
# Clone the repo
git clone https://github.com/opent03/bayesian_dpddm.git

# Navigate into repo directory 
cd bayesian_dpddm

# Install the required dependencies
pip install .
```

## Usage and Tutorials

Coming soon.

## Citation

Coming soon.



