Efficient Batched Reinforcement Learning in TensorFlow
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Updated
Jan 11, 2019 - Python
Efficient Batched Reinforcement Learning in TensorFlow
Mpcurses is an abstraction of the Python curses and multiprocessing libraries providing function execution and runtime visualization capabilities.
Notes for multi-processing and multi-threading
Python implementation of a multi-processed gRPC client/server with streaming capabilities.
This short little python module can help you with running your iteratable functions on multi process without any hassle of creating process by yourself.
Using celery framework with AI models (Documentation)
a hybrid CPU-GPU combined multi-processing approach for optimized performance in AES128 algorithm. The encryption key is derived using the HKDF (HMAC-based Key Derivation Function) combined with the scrypt algorithm for added security.
Examples on multi-processing and multi-threading in Python.
Simple multi-processing python cli to set the default audio and/or subtitles of a single matroska (.mkv) file or a library of files WITHOUT having to remux the file
Simple Python multithreading examples
This project implements a robust, multi-threaded transaction processing system for managing user accounts, complete with real-time analytics, error metrics, and Flask API integration. It leverages Mojo for high-performance concurrency and a SQLite backend for storage, making it ideal for both testing and deployment in controlled environments.
Demonstration of multithreading and multiprocessing in basic prime number searching maner.
Executing lengthy functions using python Rest API and processes.
Enables you to convert a PettingZoo environment to a Gym environment while supporting multiple agents (MARL). Gym's default setup doesn't easily support multi-agent environments, but this wrapper resolves that by running each agent in its own process and sharing the environment across those processes.
Picture Frame that uses face recognition to identify and display images of users and uses Flickr API to import images
[Phase II: Consumer] This repository holds the code developed in partial fulfilment of online credit course "CS370 - OS" offered at Colorado State University Online for Spring 2024.
Secure multi threading and multi processing python socket programming implementation
Python image processing pipeline with multiple concurrency approaches (serial, multithreading, multiprocessing, asyncio, Ray)
A python implementation of CBDT
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