Metadata-Version: 2.1
Name: pmlayer
Version: 1.0.1
Summary: pmlayer: partially monotone layer
Home-page: https://github.com/IBM/pmlayer
Author: Hiroki Yanagisawa
Author-email: yanagis@jp.ibm.com
Maintainer: Hiroki Yanagisawa
Maintainer-email: yanagis@jp.ibm.com
License: Apache 2.0
Download-URL: https://github.com/IBM/pmlayer
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.6
License-File: LICENSE

# Partially Monotone Layer

Partially monotome layer (`pmlayer`) is a library for neural network models.
It provides several neural network layers to add monotonicity constraints on neural network models.
Current implementation is available only for PyTorch.

Read the [documentation](https://ibm.github.io/pmlayer/) to get started, and feel free to contact us for any inquiry.

# Installation

You can install `pmlayer` by using the `pip` command:

```pip install pmlayer```


# Citation

Please consider citing this paper.
> H. Yanagisawa, K. Miyaguchi, and T. Katsuki, "Hierarchical Lattice Layer for Partially Monotone Regression," NeurIPS 2022.


