Search Results for "linux gpib support"
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Showing 14 open source projects for "linux gpib support"
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1
PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
No-Nonsense Code-to-Cloud Security for Devs | AikidoAikido provides a unified security platform for developers, combining 12 powerful scans like SAST, DAST, and CSPM. AI-driven AutoFix and AutoTriage streamline vulnerability management, while runtime protection blocks attacks.
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5
Neural Network Intelligence
AutoML toolkit for automate machine learning lifecycle
Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'... -
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NeuMan
Neural Human Radiance Field from a Single Video (ECCV 2022)
NeuMan is a reference implementation that reconstructs both an animatable human and its background scene from a single monocular video using neural radiance fields. It supports novel view and novel pose synthesis, enabling compositional results like transferring reconstructed humans into new scenes. The pipeline separates human/body and environment, learning consistent geometry and appearance to support animation. Demos showcase sequences such as dance and handshake, and the code provides... -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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Nerfies
This is the code for Deformable Neural Radiance Fields
Nerfies demonstrates deformation-aware neural radiance fields that reconstruct and render dynamic, real-world scenes from casual video. Instead of assuming a static world, the method learns a canonical space plus a deformation field that maps changing poses or expressions back to that space during training. This lets the system generate photorealistic novel views of nonrigid subjects—faces, bodies, cloth—while preserving fine detail and consistent lighting. The training pipeline handles... -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
Stigg | SaaS Monetization and Entitlements APIA monetization platform is a standalone middleware that sits between your application and your business applications, as part of the modern enterprise billing stack. Stigg unifies all the APIs and abstractions billing and platform engineers had to build and maintain in-house otherwise. Acting as your centralized source of truth, with a highly scalable and flexible entitlements management, rolling out any pricing and packaging change is now a self-service, risk-free, exercise.
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read...
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