This code implements constituency parse tree aggregation

Related tags

Deep LearningCPTAM
Overview

README

This code implements constituency parse tree aggregation.

Folder details

  • code: This folder contains the code that implements constituency parse tree aggregation.
  • sample_dataset: This folder contains 100 sentences from Penn Treebank dataset. This is the input for the method. Ground Truth is only used for evaluation purposes.

Code description

  • hanlp_resources.py: The output of Hanlp parser follows a different format. This code is used to convert it into the format of other parsers.
  • resources.py: This code does character indexing of the input, obtains cluster list and stores the formatted input into a dictionary.
  • compatibility.py: This code contains implementation of maximum independent set.
  • medcpt.py: This code does constituency parse tree aggregation.
  • evaluation.py: This code does performance evaluation and stores the results as a dictionary file.
  • print_results.py: This code prints evaluation results.

Input parsers

Dataset details

Baseline Aggregation methods

The implementation of baseline aggregation methods can be found at https://evolution.genetics.washington.edu/phylip/getme-new1.html

Steps for code execution

Required packages

  • python 3
  • pickle
  • numpy

Execution flow

  • python resources.py
  • python medcpt.py
  • python evaluation.py
  • python print_results.py
Owner
Adithya Kulkarni
Adithya Kulkarni
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition

AdaFocusV2 This repo contains the official code and pre-trained models for AdaFo

79 Dec 26, 2022
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Zhiqiang Shen 52 Dec 24, 2022
Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. This implementation is written in JAX, and is a fork of Google's JaxNeRF

Google 625 Dec 30, 2022
Code for the paper "How Attentive are Graph Attention Networks?"

How Attentive are Graph Attention Networks? This repository is the official implementation of How Attentive are Graph Attention Networks?. The PyTorch

175 Dec 29, 2022
Optimizes image files by converting them to webp while also updating all references.

About Optimizes images by (re-)saving them as webp. For every file it replaced it automatically updates all references. Works on single files as well

Watermelon Wolverine 18 Dec 23, 2022
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

AI4Finance Foundation 2.5k Jan 05, 2023
PyTorch implementation for Partially View-aligned Representation Learning with Noise-robust Contrastive Loss (CVPR 2021)

2021-CVPR-MvCLN This repo contains the code and data of the following paper accepted by CVPR 2021 Partially View-aligned Representation Learning with

XLearning Group 33 Nov 01, 2022
CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning

CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning This repository contains the code and relevant instructions

XiaoMing 5 Aug 19, 2022
Evolutionary Scale Modeling (esm): Pretrained language models for proteins

Evolutionary Scale Modeling This repository contains code and pre-trained weights for Transformer protein language models from Facebook AI Research, i

Meta Research 1.6k Jan 09, 2023
An exploration of log domain "alternative floating point" for hardware ML/AI accelerators.

This repository contains the SystemVerilog RTL, C++, HLS (Intel FPGA OpenCL to wrap RTL code) and Python needed to reproduce the numerical results in

Facebook Research 373 Dec 31, 2022
GPU-Accelerated Deep Learning Library in Python

Hebel GPU-Accelerated Deep Learning Library in Python Hebel is a library for deep learning with neural networks in Python using GPU acceleration with

Hannes Bretschneider 1.2k Dec 21, 2022
PyTorch framework for Deep Learning research and development.

Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati

Catalyst-Team 29 Jul 13, 2022
Turn based roguelike in python

pyTB Turn based roguelike in python Documentation can be found here: http://mcgillij.github.io/pyTB/index.html Screenshot Dependencies Written in Pyth

Jason McGillivray 4 Sep 29, 2022
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision

A Light in the Dark: Deep Learning Practices for Industrial Computer Vision This is the repository for our Paper/Contribution to the WI2022 in Nürnber

Maximilian Harl 6 Jan 17, 2022
Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering (NAACL 2021)

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering Abstract In open-domain question answering (QA), retrieve-and-read mec

Clova AI Research 34 Apr 13, 2022
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF

Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr

Shuaifeng Zhi 243 Jan 07, 2023
Datasets and pretrained Models for StyleGAN3 ...

Datasets and pretrained Models for StyleGAN3 ... Dear arfiticial friend, this is a collection of artistic datasets and models that we have put togethe

lucid layers 34 Oct 06, 2022
DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

DeepMetaHandles (CVPR2021 Oral) [paper] [animations] DeepMetaHandles is a shape deformation technique. It learns a set of meta-handles for each given

Liu Minghua 73 Dec 15, 2022
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Google 148 Nov 18, 2022