mlsanityData to 7 Oct 2026

Ivy: Templated Deep Learning for Inter-Framework Portability

arXiv 2102.02886 ↗First posted 4 Feb 2021cs.LG cs.AI cs.CVcited by 6

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Abstract (arXiv)

We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks. Ivy unifies the core functions of these frameworks to exhibit consistent call signatures, syntax and input-output behaviour. New high-level framework-agnostic functions and classes, which are usable alongside framework-specific code, can then be implemented as compositions of the unified low-level Ivy functions. Ivy currently supports TensorFlow, PyTorch, MXNet, Jax and NumPy. We also release four pure-Ivy libraries for mechanics, 3D vision, robotics, and differentiable environments. Through our evaluations, we show that Ivy can significantly reduce lines of code with a runtime overhead of less than 1% in most cases. We welcome developers to join the Ivy community by writing their own functions, layers and libraries in Ivy, maximizing their audience and helping to accelerate DL research through inter-framework codebases. More information can be found at https://ivy-dl.org.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 16 of its 39 references that are in the map. First posted on arXiv 4 Feb 2021.

Builds on

16 of 39 references.

References · 16

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
  3. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  4. 2014Neural Turing Machinescited by 630
  5. 2014Caffe: Convolutional Architecture for Fast Feature Embeddingcited by 287
  6. 2015MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systemscited by 195
  7. 2018BA-Net: Dense Bundle Adjustment Networkcited by 173
  8. 2016Value Iteration Networkscited by 158
  9. 2018CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAMcited by 151
  10. 2020Scalable Differentiable Physics for Learning and Controlcited by 72
  11. 2016Theano: A Python framework for fast computation of mathematical expressionscited by 64
  12. 2019PyRep: Bringing V-REP to Deep Robot Learningcited by 43
4 more
  1. 2019GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processingcited by 31
  2. 2019Chainer: A Deep Learning Framework for Accelerating the Research Cyclecited by 22
  3. 2017DLTK: State of the Art Reference Implementations for Deep Learning on Medical Imagescited by 11
  4. 2017ZhuSuan: A Library for Bayesian Deep Learningcited by 8

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Cited by year

Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 0; 2025: 2.

6 papers.

  1. 2021Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisationcited by 120
  2. 2022Adversarial Cheap Talkcited by 16
  3. 2025When LLMs Meet API Documentation: Can Retrieval Augmentation Aid Code Generation Just as It Helps Developers?cited by 12
  4. 2022Learning Graph Search Heuristicscited by 7
  5. 2021End-to-End Egospheric Spatial Memorycited by 3
  6. 2025Towards Migrating Neural Network Implementationscited by 1