Abstract is: PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, Uber's Pyro, Hugging Face's Transformers, PyTorch Lightning, and Catalyst. PyTorch provides two high-level features: * Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU) * Deep neural networks built on a tape-based automatic differentiation system
software library | Q188860 |
free and open-source software | Q506883 |
machine learning framework | Q21169670 |
Python package | Q29642950 |
P144 | based on | Torch | Q17087180 |
P275 | copyright license | 3-clause BSD License | Q18491847 |
P6216 | copyright status | copyrighted | Q50423863 |
P1547 | depends on software | typing-extensions | Q107380511 |
P1343 | described by source | PyTorch: An Imperative Style, High-Performance Deep Learning Library | Q76472044 |
P6104 | maintained by WikiProject | WikiProject Software | Q15659621 |
P306 | operating system | Linux | Q388 |
Microsoft Windows | Q1406 | ||
macOS | Q14116 | ||
P277 | programmed in | C++ | Q2407 |
C | Q15777 | ||
Python | Q28865 | ||
CUDA | Q477690 | ||
P577 | publication date | 2016-08-24 | |
P8687 | social media followers | 41600 | |
299138 | |||
P348 | software version identifier | 2.3.1 | |
P2283 | uses | NCHW | Q115729428 |
Q124759406 | FastSD CPU |
Q96631404 | PyKEEN |
Q85847011 | PyTorch Lightning |
Q117030340 | Real-ESRGAN |
Q116908797 | STonKGs |
Q120550372 | Stanza |
Q112181165 | YOLO |
Q116908792 | accelerate |
Q107382302 | allennlp |
Q107382376 | attacut |
Q107382224 | bert-score |
Q107382330 | botorch |
Q107382311 | captum |
Q107382139 | catalyst |
Q120549792 | clean-fid |
Q120596958 | effdet |
Q120550306 | face-alignment |
Q120549805 | facexlib |
Q107382238 | fairseq |
Q107382314 | fastai |
Q107386786 | flair |
Q120733208 | flexgen |
Q120733123 | fschat |
Q120549808 | gfpgan |
Q107382323 | gpytorch |
Q120634941 | hummingbird-ml |
Q120550406 | invisible-watermark |
Q107382312 | kornia |
Q97126903 | kraken |
Q120550319 | lion-pytorch |
Q120550308 | lpips |
Q107385611 | memcnn |
Q120550358 | nerfacc |
Q120550360 | open-clip-torch |
Q120634951 | peft |
Q120550139 | pgmpy |
Q107382321 | pyro-ppl |
Q107381754 | pytorch-ignite |
Q107385500 | pytorch-pretrained-bert |
Q120550386 | pytorch-ranger |
Q107385836 | pytorch-transformers |
Q120550396 | pytorch-wavelets |
Q120549810 | pytorch_lightning |
Q120759101 | qdrant_haystack |
Q120550392 | rotary-embedding-torch |
Q120550300 | salesforce-lavis |
Q120550363 | smplx |
Q107386398 | snorkel |
Q107382388 | spacy-transformers |
Q120634948 | span-marker |
Q120550393 | speechbrain |
Q120550365 | taming-transformers-rom1504 |
Q107381748 | thop |
Q107382194 | timm |
Q120549814 | tomesd |
Q107381755 | torch-fidelity |
Q116908631 | torch-max-mem |
Q120550387 | torch-optimizer |
Q116908634 | torch-ppr |
Q107381747 | torchaudio |
Q120549815 | torchdiffeq |
Q121785328 | torchjpeg |
Q107381756 | torchmetrics |
Q120549817 | torchsde |
Q107381760 | torchtext |
Q107381670 | torchvision |
Q121435758 | triton |
Q120550499 | xformers |
Q125510158 | AI-based pathology predicts origins for cancers of unknown primary |
Q61726888 | Assessing BERT's Syntactic Abilities |
Q67202761 | Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages |
Q109686686 | Bounds all around: training energy-based models with bidirectional bounds |
Q124743842 | Context-Gated Convolution |
Q112074412 | Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy |
Q62428109 | Excessive Invariance Causes Adversarial Vulnerability |
Q113531353 | Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex Spaces |
Q124359239 | KGTN-ens: few-shot image classification with knowledge graph ensembles |
Q108652400 | LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignment |
Q119496035 | Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction |
Q84078340 | Multi-hop Reading Comprehension through Question Decomposition and Rescoring |
Q76470807 | Multi-relational Poincaré Graph Embeddings |
Q109583780 | PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings |
Q112208223 | TERA: optimizing stochastic regression tests in machine learning projects |
Q110572878 | The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central |
Q126325520 | ptwt - The PyTorch Wavelet Toolbox |
Q110502055 | 3D Image Segmentation of MRI Prostate Based on a Pytorch Implementation of V-Net |
Q120789632 | A publicly available PyTorch-ABAQUS UMAT deep-learning framework for level-set plasticity |
Q120789713 | AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch |
Q110502076 | An Efficient Face Mask Detector with PyTorch and Deep Learning |
Q120789816 | Analysis of the Application Efficiency of TensorFlow and PyTorch in Convolutional Neural Network |
Q120789740 | Applying pytorch toolkit to plan optimization for circular cone based robotic radiotherapy |
Q110502061 | Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL |
Q114658434 | CP-AGCN: Pytorch-based attention informed graph convolutional network for identifying infants at risk of cerebral palsy |
Q120789648 | Evaluation of gene expression programming and artificial neural networks in PyTorch for the prediction of local scour depth around a bridge pier |
Q110502071 | Face Mask And Crowd Detection Using Pytorch and Multi-Task Cascade Convolutional Neural Network |
Q110502060 | Face mask detection for covid_19 pandemic using pytorch in deep learning |
Q110502065 | Fireworks: Reproducible Machine Learning and Preprocessing with PyTorch |
Q110500246 | Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX |
Q120789805 | Fractional Gradient Optimizers for PyTorch: Enhancing GAN and BERT |
Q96835410 | GPU-Accelerated Semi-Empirical Born Oppenheimer Molecular Dynamics using PyTorch |
Q110499914 | Gamma/Hadron Separation in Imaging Air Cherenkov Telescopes Using Deep Learning Libraries TensorFlow and PyTorch |
Q110502047 | HexagDLy—Processing hexagonally sampled data with CNNs in PyTorch |
Q64057334 | Highly parallel simulation and optimization of photonic circuits in time and frequency domain based on the deep-learning framework PyTorch |
Q120789626 | Improving Oversubscribed GPU Memory Performance in the PyTorch Framework |
Q55950822 | Introduction to PyTorch |
Q110502063 | LSTM Deep Learning Stock Prediction System Based on PyTorch Framework |
Q110502070 | Learning Word Embeddings from 10-K Filings Using PyTorch |
Q110502078 | Machine Learning Model for IRIS Flower Classification using Tensor Flow and PyTorch |
Q110502067 | MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks |
Q110502043 | MobileStyleGAN.pytorch: PyTorch-based toolkit to compress StyleGAN2 model |
Q110502059 | Monte Carlo Collision method for Particle-In-Cell plasma simulation: PyTorch implementation |
Q110502057 | Optical-imaging detection of apple sugar content based on OpenCv and Pytorch |
Q120789752 | PYLON: A PyTorch Framework for Learning with Constraints |
Q110500022 | Performance Analysis of Deep Learning Libraries: TensorFlow and PyTorch |
Q120789820 | Performance Comparison between Pytorch and Mindspore |
Q110502041 | Physics-informed neural network method for solving one-dimensional advection equation using PyTorch |
Q120789685 | PocketFinderGNN: A manufacturing feature recognition software based on Graph Neural Networks (GNNs) using PyTorch Geometric and NetworkX |
Q112680746 | Prediction of Hearing Prognosis of Large Vestibular Aqueduct Syndrome Based on the PyTorch Deep Learning Model |
Q110502053 | PyLightcurve-torch: a transit modeling package for deep learning applications in PyTorch |
Q110502072 | PyTorch Operations Based Approach for Computing Local Binary Patterns |
Q110502074 | PyTorch YOLOv3 Object Detection for Vehicle Identification |
Q110502064 | PyTorch distributed |
Q62657788 | PyTorch-BigGraph: A Large-scale Graph Embedding System |
Q120789628 | PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta |
Q110502045 | PyTorch-based implementation of label-aware graph representation for multi-class trajectory prediction |
Q110502080 | PyTorch/Pyro Implementation for Representation of Motion in Latent Space |
Q76472044 | PyTorch: An Imperative Style, High-Performance Deep Learning Library |
Q120789765 | Pytorch Image Quality: Metrics for Image Quality Assessment |
Q114103467 | REANN: A PyTorch-based end-to-end multi-functional deep neural network package for molecular, reactive, and periodic systems |
Q110502056 | Research on Image Classification Algorithm Based on Pytorch |
Q110499872 | Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment |
Q92688575 | Selene: a PyTorch-based deep learning library for sequence data |
Q120789689 | Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation |
Q110502042 | TedNet: A Pytorch toolkit for tensor decomposition networks |
Q120789788 | Torch-NILM: An Effective Deep Learning Toolkit for Non-Intrusive Load Monitoring in Pytorch |
Q96615384 | TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials |
Q113306532 | TorchMetrics - Measuring Reproducibility in PyTorch |
Q120789671 | Variational Neural Networks implementation in Pytorch and JAX |
Q119714832 | Volume Segmantics: A Python Package for Semantic Segmentation of Volumetric Data Using Pre-trained PyTorch Deep Learning Models |
Q120789757 | normflows: A PyTorch Package for Normalizing Flows |
Q126325520 | ptwt - The PyTorch Wavelet Toolbox |
Q120789754 | pytorch-widedeep: A flexible package for multimodal deep learning |
Q110502068 | torchquad: Numerical Integration in Arbitrary Dimensions with PyTorch |
Q110502044 | vid-SAMGRAH: A PyTorch framework for multi-latent space reinforcement learning driven video summarization in ultrasound imaging |
Q120789692 | ænet-PyTorch: A GPU-supported implementation for machine learning atomic potentials training |
Q110502075 | 基于 PyTorch 和 CNN 的图片验证码识别 |
Q120847752 | PyTorch Foundation | field of work | P101 |
Q114878822 | SidechainNet | based on | P144 |
Q45364276 | AllenNLP | uses | P2283 |
Q96482388 | Detectron | programmed in | P277 |
PyTorch | wikibooks | |
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