PyTorch

Implementation of OmniNet, Omnidirectional Representations from Transformers in Pytorch

Omninet – Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be attending to all the tokens of the previous layers, leveraging recent efficient attention advances to achieve this goal. Install $ pip install omninet-pytorch Usage import torch from omninet_pytorch import Omninet omninet = Omninet( dim = 512, # model dimension depth = 6, # depth dim_head = 64, # dimension per head heads =

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Scripts

Collection of scripts to pinpoint obfuscated code

Author: Tim Blazytko Automatically detect control-flow flattening and other state machines Description: Scripts and binaries to automatically detect control-flow flattening and other state machines in binaries. Implementation is based on Binary Ninja. Check out the following blog post for more information: Automated Detection of Control-flow Flattening Usage $ ./detect_flattening.py samples/finspy Function 0x401602 has a flattening score of 0.9473684210526315. Function 0x4017c0 has a flattening score of 0.9981378026070763. Function 0x405150 has a flattening score of 0.9166666666666666. Function 0x405270 has a flattening score […]

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Keyboard

A social media platform for connecting and learning more about mechanical keyboards built on React and Redux

This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github.com/appacademy-starters/python-project-starter.git Install dependencies pipenv install –dev -r dev-requirements.txt && pipenv install -r requirements.txt Create a .env file based on the example with proper settings for your development environment Setup your PostgreSQL user, password and database and make sure it matches your .env file Get into your pipenv, migrate your database, seed your database, and run your flask app To run the […]

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Messenger

Universal messaging and notifications api

Pronounced “boat-shahft” Botschaft is unified messaging & notifications appliance. Want to text yourself when a long-running task completes, but don’t want to remember your account id or store credentials on your job server? Or maybe you want to send a slack message, a discord message, and an SNS message, all at once? Define a botschaft topic and hit it whenever you want. It’s as easy as curl http://my.botschaft.server/slack?channel=general&message=Hello! Botschaft, German, noun, feminine (genitive Botschaft, plural Botschaften) Botschaft is “message” in […]

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Telegram

Telegram Voice Chat Music Player UserBot Written with Pyrogram Smart Plugin and tgcalls

A Telegram UserBot to Play Audio in Voice Chats. This is also the source code of the userbot which is being used for playing DJ/Live Sets music in VC DJ/Live Sets group. Made with tgcalls and Pyrogram Smart Plugin vc.player vc.recorder ping Description Voice Chat Audio Player Voice Chat Audio Recorder ping and uptime Dependencies ffmpeg ffmpeg, opus-tools, bpm-tools Conflict vc.recorder vc.player Requirements Python 3.6 or higher A Telegram API key and a Telegram account Choose plugins you need, install […]

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Natural Language Processing

DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Art performance on all Benchmark tasks for Danish. This repository contains code for reproducing DaCy. To download the models use the DaNLP package (request pending), SpaCy (request pending) or downloading the project directly here. Reproduction the folder DaCy contains a SpaCy project which will allow for a reproduction of the results. This folder also includes the evaluation metrics on DaNE. Usage To   […]

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JAX

Turning SymPy expressions into JAX functions

Turn SymPy expressions into parametrized, differentiable, vectorizable, JAX functions. All SymPy floats become trainable input parameters. SymPy symbols become columns of a passed matrix. Installation pip install git+https://github.com/MilesCranmer/sympy2jax.git Example import sympy from sympy import symbols import jax import jax.numpy as jnp from jax import random from sympy2jax import sympy2jax Let’s create an expression in SymPy: x, y = symbols(‘x y’) expression = 1.0 * sympy.cos(x) +

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App

A shopping list and kitchen inventory management app

This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github.com/appacademy-starters/python-project-starter.git Install dependencies pipenv install –dev -r dev-requirements.txt && pipenv install -r requirements.txt Create a .env file based on the example with proper settings for your development environment Setup your PostgreSQL user, password and database and make sure it matches your .env file Get into your pipenv, migrate your database, seed your database, and run your flask app To run the […]

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Optimization

Optimization for Oriented Object Detection via Representation Invariance Loss

By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. The repository hosts the codes for our paper Optimization for Oriented Object Detection via Representation Invariance Loss (paper link), based on mmdetection and s2anet. Introduction To be updated. Installation conda create -n ridet python=3.7 -y source activate ridet conda install pytorch=1.3 torchvision cudatoolkit=10.0 -c pytorch pip install -r requirements.txt python setup.py develop cd mmdet/ops/orn python setup.py build_ext –inplace apt-get update apt-get install swig apt-get install zip cd DOTA_devkit […]

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