An Efficient Model Parallelization Toolkit for Deployment

parallelformers An Efficient Model Parallelization Toolkit for Deployment. Parallelformers, which is based on Megatron LM, is designed to make model parallelization easier. You can parallelize various models in HuggingFace Transformers on multiple GPUs with a single line of code. Currently, Parallelformers only supports inference. Training features are NOT included. Why Parallelformers? You can load a model that is too large for a single GPU. For example, using Parallelformers, you can load a model of 12GB on two 8 GB GPUs. […]

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Speed up image analysis in Python with efficient reading

impy Speed up image analysis in Python with efficient reading, batch-processing, viewing functions and easily extend your own function for batch processing. Image analysis programatically is sometimes troublesome like … for multi-dimensional images, you need to check which is time-axis and which is channel axis and so on. you need to consider the output data types and shapes for every batch image processing. you need to care about all the images’ information such as the names and directories of original […]

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Library for Python 3 to communicate with the Google Chromecast

pychromecast Library for Python 3.6+ to communicate with the Google Chromecast. It currently supports: Auto discovering connected Chromecasts on the network Start the default media receiver and play any online media Control playback of current playing media Implement Google Chromecast api v2 Communicate with apps via channels Easily extendable to add support for unsupported namespaces Multi-room setups with Audio cast devices Check out Home Assistant for a ready-made solution using PyChromecast for controlling and automating your Chromecast or Cast-enabled device […]

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Simple and convenient bot discord on Python

Parzibot Simple and convenient bot discord on Python. The source code of the bot is available to everyone. The bot used the English language. This is free open source software and if anyone wants to change things in advance. Commands Bot commands /8ball question – Ball of predictions /about – About bot /admin_help – Admin commands /clear Quantity – Clear chat /gg [game1 game2 … gameN] – Randomly chooses a game /help – Bot commands /ping – You ping /users […]

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Variable Transformer Calculator with python

VASCO – VAriable tranSformer CalculatOr Software que calcula informações de transformadores feita para a matéria de “Conversão Eletromecânica de Energia I” do curso de “Engenharia Elétrica” da Universidade Federal de Santa Maria Campus Cachoeira do Sul (UFSM-CS). Autores: Arthur Cordeiro Andrade João Gabriel Silva de Avellar Dependências pip install pygame Dependências: pip install pyinstaller Comando Compilar pyinstaller –noconfirm –onefile –windowed –icon “Images/Cruz-De-Malta.ico” –add-data “Images;Images/” –add-data “Sounds;Sounds/” “./VASCO.py” GitHub https://github.com/ArthurCoAnd/VASCO    

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Service for visualisation of high dimensional for hydrosphere

Service for visualization of high dimensional for hydrosphere DEPENDENCIES DEBUG_ENV = bool(os.getenv(“DEBUG_ENV”, False)) APP_PORT = int(os.getenv(“APP_PORT”, 5000)) GRPC_PORT = os.getenv(“GRPC_PORT”, 5001) GRPC_UI_ADDRESS = os.getenv(“GRPC_UI_ADDRESS”, “localhost:9090”) HS_CLUSTER_ADDRESS = os.getenv(“HTTP_UI_ADDRESS”, “http://localhost”) SECURE = os.getenv(“SECURE”, False) MONGO_URL = os.getenv(“MONGO_URL”, “mongodb”) MONGO_PORT = int(os.getenv(“MONGO_PORT”, 27017)) MONGO_AUTH_DB = os.getenv(“MONGO_AUTH_DB”, “admin”) MONGO_USER = os.getenv(“MONGO_USER”) MONGO_PASS = os.getenv(“MONGO_PASS”) AWS_STORAGE_ENDPOINT = os.getenv(‘AWS_STORAGE_ENDPOINT’, ”) AWS_REGION = os.getenv(‘AWS_REGION’, ”) HYDRO_VIS_BUCKET_NAME = os.getenv(‘AWS_BUCKET’, ‘hydro-vis’) Assumptions: Model must have in it’s contract ’embedding’ output If model returns class prediction and confidence these […]

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NeuroMorphic Predictive Model with Spiking Neural Networks in Python

pynm NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) in Python using Pytorch. pynm is an open source, low-code library in python to build neuromorphic predictive models (Classification & Regression problems) using [Spiking Neural Networks (SNNs)] (https://en.wikipedia.org/wiki/Spiking_neural_network) at ease. It allows you to go from preparing your data to deploying your spiking model within minutes. SNNs are neural networks that mimics the biological brain. In the case of SNNs, the neurons accumulate the input activation until a threshold is reached, […]

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Library for managing and writing git hooks in Python

Autohooks Library for managing and writing git hooks in Python. Looking for automatic formatting or linting, e.g., with black and pylint, while creating a git commit using a pure Python implementation? Welcome to autohooks! Why? Several outstanding libraries for managing and executing git hooks exist already.To name a few: husky,lint-staged,precise-commits orpre-commit. However, they either need another interpreter besides python (like husky) or aretoo ambiguous (like pre-commit). pre-commit is written in python but has supporthooks written in all kind of languages. […]

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Plotting and analysis tools for ARTIS simulations

Artistools is collection of plotting, analysis, and file format conversion tools for the ARTIS radiative transfer code. Installation First clone the repository, for example: git clone https://github.com/artis-mcrt/artistools.git Then from within the repository directory run: python3 -m pip install -e . Usage Type “artistools” at the command-line to get a full list of commands. The most frequently used commands are: plotartisestimators plotartislightcurve plotartisnltepops plotartisnonthermal plotartisradfield plotartisspectrum Use the -h option to get a list of command-line arguments for each command. Most […]

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Modest utility collection for development with AIOHTTP framework

aiohttp-things Modest utility collection for development with AIOHTTP framework. Installation Installing aiohttp-things with pip: pip install aiohttp-things Simple example Example of AIOHTTP application import json import uuid import aiohttp_things as ahth from aiohttp import web def safe_json_value(value): try: json.dumps(value) return value except (TypeError, OverflowError): return str(value) class Base(web.View, ahth.JSONMixin, ahth.PrimaryKeyMixin): async def get(self): self.context[‘Type of primary key’] = safe_json_value(type(self.pk)) self.context[‘Value of primary key’] = safe_json_value(self.pk) return await self.finalize_response() class IntegerExample(Base): pk_adapter = int class UUIDExample(Base): pk_adapter = uuid.UUID UUID = […]

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