This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)

Overview

nfa-to-dfa

This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)

Using convert.py

You may provide an input NFA in one of two ways.

  1. Define the NFA via a CLI

    • When invoking the program, provide a name for the output file
      • > python convert.py
    • After walking you through the NFA definition, it will create a DFA in the form of .fa
  2. Define the NFA via an input file

    • When invoking the program, provide an input file of type .nfa
      • > python convert.py .nfa
    • This will create a DFA in the form of .fa

Formatting a .nfa file

The input .nfa should be formatted as follows:

  1. The first line holds a set of states the NFA could initially be on, enclosed in curly braces, delimted by commas
  2. The second line holds a set of states that the NFA will accept, enclosed in curly braces, delimted by commas
  3. The following lines will define the state transitions, as a tuple, for each state you wish to define.
    • The first symbol is the current state.
    • The second symbol will be the transition symbol.
    • The following symbol (or symbols, delimted by space) will define the set of all states the automata will transition into.
example.nfa
{1}
{1, 3}

1 a 2 3
1 b 1

2 a 3
2 b 1

3 a 3
3 b 3
Owner
Quinn Herden
Quinn Herden
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

Sriram Ravula 26 Dec 10, 2022
Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity

Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity Indic TTS Samples can be found at https://peter-yh-wu.github.io/cross-

Peter Wu 1 Nov 12, 2022
YOLOv5 in PyTorch > ONNX > CoreML > TFLite

This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and e

Ultralytics 34.1k Dec 31, 2022
VisionKG: Vision Knowledge Graph

VisionKG: Vision Knowledge Graph Official Repository of VisionKG by Anh Le-Tuan, Trung-Kien Tran, Manh Nguyen-Duc, Jicheng Yuan, Manfred Hauswirth and

Continuous Query Evaluation over Linked Stream (CQELS) 9 Jun 23, 2022
Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn?

Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn? Repository Structure: DSAN |└───amazon |    └── dataset (Amazo

DMIRLAB 17 Jan 04, 2023
Exploiting a Zoo of Checkpoints for Unseen Tasks

Exploiting a Zoo of Checkpoints for Unseen Tasks This repo includes code to reproduce all results in the above Neurips paper, authored by Jiaji Huang,

Baidu Research 8 Sep 06, 2022
Source code of our BMVC 2021 paper: AniFormer: Data-driven 3D Animation with Transformer

AniFormer This is the PyTorch implementation of our BMVC 2021 paper AniFormer: Data-driven 3D Animation with Transformer. Haoyu Chen, Hao Tang, Nicu S

24 Nov 02, 2022
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased

Kaihua Tang 824 Jan 03, 2023
A library for uncertainty representation and training in neural networks.

Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re

DeepMind 211 Dec 12, 2022
An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.

ImageCompressionSimulation An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects o

James Park 1 Dec 11, 2021
Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper

LEXA Benchmark Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper (Discovering and Achieving Goals via World Models

Oleg Rybkin 36 Dec 22, 2022
Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation (RA-L/ICRA 2020)

Aerial Depth Completion This work is described in the letter "Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation", by Lucas

ETHZ V4RL 70 Dec 22, 2022
Explaining Hyperparameter Optimization via PDPs

Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex

2 Nov 16, 2022
This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian

Aryclenio Xavier Barros 26 Oct 14, 2022
an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

Simon Niklaus 985 Jan 08, 2023
PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021

Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.

Siyu Huang 33 Dec 06, 2022
Implementation for Curriculum DeepSDF

Curriculum-DeepSDF This repository is an implementation for Curriculum DeepSDF. Full paper is available here. Preparation Please follow original setti

Haidong Zhu 69 Dec 29, 2022
CVAT is free, online, interactive video and image annotation tool for computer vision

Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our

OpenVINO Toolkit 8.6k Jan 04, 2023
Geometric Sensitivity Decomposition

Geometric Sensitivity Decomposition This repo is the official implementation of A Geometric Perspective towards Neural Calibration via Sensitivity Dec

16 Dec 26, 2022
Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Peter Schaldenbrand 247 Dec 23, 2022