DisCoPy: Monoidal Categories in Python

Abstract

We introduce DisCoPy, an open source toolbox for computing with monoidal categories. The library provides an intuitive syntax for defining string diagrams and monoidal functors. Its modularity allows the efficient implementation of computational experiments in the various applications of category theory where diagrams have become a lingua franca. As an example, we used DisCoPy to perform natural language processing on quantum hardware for the first time.

arXiv commentIn Proceedings ACT 2020, arXiv:2101.07888

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Cited by in corpus (13)

• QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer
• Grammar-aware sentence classification on quantum computers
• Foundations for Near-Term Quantum Natural Language Processing
• Operads for complex system design specification, analysis and synthesis
• A CCG-Based Version of the DisCoCat Framework
• Diagrammatic Differentiation for Quantum Machine Learning
• lambeq: An Efficient High-Level Python Library for Quantum NLP
• Quantum Linear Optics via String Diagrams
• A category theory framework for Bayesian learning
• SQL2Circuits: Estimating Cardinalities, Execution Times, and Costs for SQL Queries with Quantum Natural Language Processing
• A dataflow programming framework for linear optical distributed quantum computing
• Functorial Language Models
• Learning a Deep Generative Model like a Program: the Free Category Prior