Author: Deep Learner

Semi-supervised

The Rich Get Richer: Disparate Impact of Semi-Supervised Learning

Preprocess file of the dataset used in implicit sub-populations:(Demographic groups: race and gender) The following code will pre-process the jigsaw dataset and return train/test dataset files including demographic groups information. Step-1: Download the jigsaw dataset: identity_individual_annotations.csv from https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data. Step-2: python preprocecss_jiasaw_toxicity_gender_and_race_balanced.py Implementation of SSL methods Please follow the official implementations of MixMatch, MixText, and UDA. [1] https://github.com/google-research/mixmatch [2] https://github.com/GT-SALT/MixText [3] https://github.com/google-research/uda GitHub – UCSC-REAL/Disparate-SSL at pythonawesome.com Contribute to UCSC-REAL/Disparate-SSL development by creating an account on GitHub. GitHubUCSC-REAL    

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TIME SERIES

Dynamical Wasserstein Barycenters for Time Series Modeling

Dynamical Wasserstein Barycenters for Time Series Modeling This is the code related for the Dynamical Wasserstein Barycenter model published in Neurips 2021. To run the code and replicate the results reported in our paper, # usage: DynamicalWassersteinBarycenters.py dataSet dataFile debugFolder interpModel [–ParamTest PARAMTEST] [–lambda LAM] [–s S] # Sample run on MSR data >> python DynamicalWassersteinBarycenters.py MSR_Batch ../Data/MSR_Data/subj090_1.mat ../debug/MSR/subj001_1.mat Wass # Sample run for parameter test >> python DynamicalWassersteinBarycenters.py MSR_Batch ../Data/MSR_Data/subj090_1.mat ../debug/ParamTest/subj001_1.mat Wass –ParamTest 1 –lambda 100 –s 1.0 The […]

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Scripts

Formerly Codalab Competitions v2

(formerly Codalab Competitions v2) Installation $ cp .env_sample .env $ docker-compose up -d $ docker-compose exec django ./manage.py migrate $ docker-compose exec django ./manage.py generate_data $ docker-compose exec django ./manage.py collectstatic –noinput You can now login as username “admin” with password “admin” at http://localhost:8000 If you ever need to reset the database, use the script ./reset_db.sh Running tests # Non “end to end tests” $    

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Management System

A Python Tkinter based Inventory managment System

Introduction Inventory managemrnt system is an open source platform for manage business. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets businesses push to manage their system most effectively. This is a software for practice of developing a system from completely scratch. Understanding this will help a lot in system development and basic structure of a system along with GUI with python library Tkinter. This software was originally developed by Amit Kumar Datta This project […]

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Tkinter

TkVideoplayer : a simple library to play video files in tkinter

This is a simple library to play video files in tkinter. This library also provides the ability to play , pause, skip and seek specific frames. Example: import tkinter as tk from tkVideoPlayer import TkinterVideo root = tk.Tk() videoplayer = TkinterVideo(master=root, scaled=True, pre_load=False) videoplayer.load(r”samplevideo.mp4″) videoplayer.pack(expand=True, fill=”both”) videoplayer.play() # play the video root.mainloop() read the documentation here

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PyTorch

LayoutTransformer: Layout Generation and Completion with Self-attention

arXiv | BibTeX | Project Page This repo contains code for single GPU training of LayoutTransformer from LayoutTransformer: Layout Generation and Completion with Self-attention. This code was rewritten from scratch using a cleaner GPT codebase. Some of the details such as training hyperparameters might differ from the arxiv version of the paper. How To Use This Code Start a new conda environment conda env create -f environment.yml conda activate layout or update an existing environment conda env    

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