Search Results for "hardware"
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Showing 14 open source projects for "hardware"
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blinker-py
Blinker python library for hardware. Works with Raspberry Pi
blinker-py is a Python library for connecting hardware projects to the Blinker IoT platform. It is designed for Raspberry Pi, Banana Pi, Linux devices, and similar single-board or embedded systems. The library helps developers control hardware through the Blinker mobile app, where users can build graphical interfaces with drag-and-drop widgets. It supports common IoT communication patterns such as Wi-Fi, MQTT, WebSocket, and BLE-related platform workflows. -
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CoreNet
CoreNet: A library for training deep neural networks
...CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
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The Arcade Library
Easy to use Python library for creating 2D arcade games
Arcade is an easy-to-use Python library for creating 2D video games. It provides a modern and straightforward API, enabling developers to craft engaging games and graphical applications efficiently. Arcade supports rendering shapes, handling user input, and managing game physics, making it suitable for both beginners and experienced developers. -
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AIMET
AIMET is a library that provides advanced quantization and compression
...With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware accelerators. Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. Plus, an 8-bit model also has a 4x smaller memory footprint relative to a 32-bit model. However, often when quantizing a machine learning model (e.g., from 32-bit floating point to an 8-bit fixed point value), the model accuracy is sacrificed. -
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation... -
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eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original... -
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Amazon Braket Strawberry Fields Plugin
An open source framework for using Amazon Braket devices
...This plugin provides a BraketEngine class for running photonic quantum circuits created in Strawberry Fields on the Amazon Braket service. The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. This plugin provides the classes BraketEngine for submitting photonic circuits to Amazon Braket and BraketJob for tracking the status of the Braket task. Strawberry Fields is an open source library for writing and running programs for photonic quantum computers. BraketEngine and BraketJob have the same interfaces as RemoteEngine in Strawberry Fields and Job in the Xanadu Cloud Client, respectively, and can be used as drop-in replacements. -
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MMdnn
Tools to help users inter-operate among deep learning frameworks
...We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform. -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
...It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile for performance analysis. It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. The framework includes a comprehensive set of predefined benchmarks covering areas such as compute, storage, networking, and distributed systems workloads. ... -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
...The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics. -
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cnn-benchmarks
Benchmarks for popular CNN models
...The repository includes scripts for running benchmarks on various architectures and datasets, making it easy to gather comparative metrics. By simplifying performance evaluation, it helps developers make informed decisions about model design and hardware selection. Overall, cnn-benchmarks is a practical tool for performance analysis in deep learning workflows. -
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pyhard2, control hardware from python
An object-oriented framework for the development of instrument drivers
pyhard2 is an object-oriented framework to help in the development of instrument drivers. pyhard2 is proposed as an alternative to LabVIEW. Emphasis is given on serial drivers but the framework can be used with any socket. The source also contains the implementation of a PID controller and a setpoint ramp generator. The instrument drivers may further be incorporated in a GUI, using, e.g. PyQt or PySide. Threading is automatically taken care of. Furthermore, generic GUI (called... -
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PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
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A Python module to seamlessly interact with the Velleman K8055 kit via the K8055D.dll for Windows using Python ctypes
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