Python Parallel-wavegan Resources

Parallel and High-Fidelity Text-to-Lip Generation This repository is the official PyTorch implementation of our AAAI-2022 paper, in which we propose P

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability

README Code for Two-stage Identifier: "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022. For details of the model a

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Authors: Tao Yu* Yichi Zhang* Zhiru Zhang Christopher De Sa *: Equal Contri

Shashank Ojha, Sabrina Button, Abdellah Ghassel, Joshua Gonzales "Reduce Reuse R

Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !

PaRT: Parallel Learning for Robust and Transparent AI This repository contains the code for PaRT, an algorithm for training a base network on multiple

We provide a notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository. The notebook also shows how to segment the corpus using BPE tokenization which can be used to train an English-Hindi MT System.

EasyRequests EasyRequests is a minimalistic HTTP-Request Library that wraps aiohttp and asyncio in a small package that allows for sequential, paralle

Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In

aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

nextPARS, a novel Illumina-based implementation of in-vitro parallel probing of RNA structures. Here you will find the scripts necessary to produce th

ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extraction and generation.

mpgitleaks A Python script that wraps the gitleaks tool to enable scanning of multiple repositories in parallel. The motivation behind writing this sc

Parallel Machine Learning with scikit-learn and IPython Video recording of this tutorial given at PyCon in 2013. The tutorial material has been rearra

PDVC Official implementation for End-to-End Dense Video Captioning with Parallel Decoding (ICCV 2021) [paper] [valse论文速递(Chinese)] This repo supports:

AutoParaSelenium A library to make parallel selenium tests that automatically download and setup webdrivers Usage Installation pip install autoparasel

(简体中文|English) Quick Start | Documents | Models List PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks i

ILI9341-parallel-TFT-driver-for-micropython For use with an 8-bit parallel TFT touchscreen using micropython. Many thanks to prenticedavid and his MCU

rosny is a lightweight library for building concurrent systems. Installation Tested on: Linux Python = 3.6 From pip: pip install rosny From source: p

About Python's multithreading and GIL

🚀 IPpy Parallel testing of IP addresses and domains in python. Reads IP addresses and domains from a CSV file and gives two lists of accessible and i

qbatch Execute shell command lines in parallel on Slurm, S(on) of Grid Engine (SGE), PBS/Torque clusters qbatch is a tool for executing commands in pa

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb

pyeventbus pyeventbus is a publish/subscribe event bus for Python 2.7. simplifies the communication between python classes decouples event senders and

Numba A Just-In-Time Compiler for Numerical Functions in Python Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaco

Parallel WaveGAN implementation with Pytorch This repository provides UNOFFICIAL pytorch implementations of the following models: Parallel WaveGAN Mel

Jug: A Task-Based Parallelization Framework Jug allows you to write code that is broken up into tasks and run different tasks on different processors.

pybnb A parallel branch-and-bound engine for Python. This software is copyright (c) by Gabriel A. Hackebeil (gabe.hacke

About The ROOT system provides a set of OO frameworks with all the functionality needed to handle and analyze large amounts of data in a very efficien

Table of contents Mesh Transformer JAX Updates Pretrained Models GPT-J-6B Links Acknowledgments License Model Details Zero-Shot Evaluations Architectu

GPT Neo 🎉 1T or bust my dudes 🎉 An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here t

Veros is the versatile ocean simulator -- it aims to be a powerful tool that makes high-performance ocean modeling approachable and fun. Because Veros

mtpng A parallelized PNG encoder in Rust by Brion Vibber [email protected] Background Compressing PNG files is a relatively slow operation at large imag

DataSelection-NMT Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts Quick update: The paper got accepted o

Welcome to fastcore Python goodies to make your coding faster, easier, and more maintainable Python is a powerful, dynamic language. Rather than bake

Parallel TTS web demo based on Flask + Vue (Vuetify).

This is a project of data parallel that running on NLP tasks.

Disimpy Disimpy is a Python package for generating simulated diffusion-weighted MR signals that can be useful in the development and validation of dat

adaptive Adaptive: parallel active learning of mathematical functions. adaptive is an open-source Python library designed to make adaptive parallel fu

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks Requirements python 0.10+ rdkit 2020.03.3.0 biopython 1.78 openbabel 2.4

RL algorithm PPO and IRL algorithm AIRL written with Tensorflow. They have a parallel sampling feature in order to increase computation speed (especially in high-performance computing (HPC)).

FastTrees This repository contains the experimental code supporting the FastTrees paper by Bill Pung. Software Requirements Python 3.6, NLTK and PyTor

Pandaral·lel Without parallelization With parallelization Installation $ pip install pandarallel [--upgrade] [--user] Requirements On Windows, Pandara

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized C

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

Automatic Parallel Parking: Path Planning, Path Tracking & Control This repository contains a python implementation of an automatic parallel parking s

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

Taichi is a parallel programming language for high-performance numerical computations.

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software

ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst

Rapid is an open-source software library that implements a novel “parallel-in-time” (Parareal) algorithm and semi-analytical solutions for co-simulation of integrated transmission and distribution systems.

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:

ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

typesafe_parmap pip install pip install typesafe-parmap Run functions in parallel safely with typesafe parmap! GitHub: https://github.com/thejaminato

Data-centric machine learning powered by DaCe

impy is All You Need in Image Analysis impy is an all-in-one image analysis library, equipped with parallel processing, GPU support, GUI based tools a

squid-dl squid-dl is a massively parallel yt-dlp-based YouTube downloader. Installation Run the setup.py, which will install squid-dl and its two depe

Multi-Task Framework for Cross-Lingual Abstractive Summarization (MCLAS) The code for ACL2021 paper Cross-Lingual Abstractive Summarization with Limit

pyHype: Computational Fluid Dynamics in Python pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve

Python Command-Line Interface Package to copy Dynamodb data in parallel batch processing + query natural & Global Secondary Indexes (GSIs).

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

tox-gh is a tox plugin which helps running tox on GitHub Actions with multiple different Python versions on multiple workers in parallel. This project is inspired by tox-travis.

WobblyStitcher Introduction A scalable implementation of WobblyStitcher Dependencies $ python -m pip install numpy scikit-image Visualization ImageJ

AVATAR Official code of our work, AVATAR: A Parallel Corpus for Java-Python Program Translation. AVATAR stands for jAVA-pyThon progrAm tRanslation. AV

Wrangl Ray-based parallel data preprocessing for NLP and ML. pip install wrangl # for latest pip install git+https://github.com/vzhong/wrangl See exa

StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversion Yinghao Aaron Li, Ali Zare, Nima Mesgarani We pres

In-place Parallel Super Scalar Samplesort (IPS⁴o) This is the implementation of the algorithm IPS⁴o presented in the paper Engineering In-place (Share

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA

ClariNet A Pytorch Implementation of ClariNet (Mel Spectrogram -- Waveform) Requirements PyTorch 0.4.1 & python 3.6 & Librosa Examples Step 1. Downlo

MLP Singer Official implementation of MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis. Audio samples are available on our demo page.

Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather than invoking the Python interpreter, Tuplex generates optimized LLVM bytecode for the given pipeline and input data set.

MALib: A parallel framework for population-based multi-agent reinforcement learning MALib is a parallel framework of population-based learning nested

Cable Driven Parallel Robots (CDPR) is also known as Cable-Suspended Robots are the emerging and flexible end effector manipulation system. Cable-driven parallel robots (CDPRs) are categorized as a type of parallel manipulators

Corset is a web-based data selection portal that helps you getting relevant data from massive amounts of parallel data. So, if you don't need the whole corpus, but just a suitable subset (indeed, a cor(pus sub)set, this is what Corset will do for you--and the reason of the name of the tool.

SYMPAIS: Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Overview | Installation | Documentation | Examples | Notebo

A lightweight (serverless) native python parallel processing framework based on simple decorators and call graphs, supporting both control flow and dataflow execution paradigms as well as de-centralized CPU & GPU scheduling.

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Multi-Task Framework for Cross-Lingual Abstractive Summarization (MCLAS) The code for ACL2021 paper Cross-Lingual Abstractive Summarization with Limit

MALib A general-purpose multi-agent training framework. Installation step1: build environment conda create -n malib python==3.7 -y conda activate mali

MaskCycleGAN-VC Unofficial PyTorch implementation of Kaneko et al.'s MaskCycleGAN-VC (2021) for non-parallel voice conversion. MaskCycleGAN-VC is the

Word2Wave is a simple method for text-controlled GAN audio generation. You can either follow the setup instructions below and use the source code and CLI provided in this repo or you can have a play around in the Colab notebook provided. Note that, in both cases, you will need to train a WaveGAN model first

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and GPT) or huge classes (millions). It has the same API design as PyTorch.

dask-rasterio dask-rasterio provides some methods for reading and writing rasters in parallel using Rasterio and Dask arrays. Usage Read a multiband r

monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical algebra libraries.

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c

redo - a recursive build system Smaller, easier, more powerful, and more reliable than make. This is an implementation of Daniel J. Bernstein's redo b

🤪 TensorFlowTTS provides real-time state-of-the-art speech synthesis architectures such as Tacotron-2, Melgan, Multiband-Melgan, FastSpeech, FastSpeech2 based-on TensorFlow 2. With Tensorflow 2, we can speed-up training/inference progress, optimizer further by using fake-quantize aware and pruning, make TTS models can be run faster than real-time and be able to deploy on mobile devices or embedded systems.