pytorch/pytorchGitHub
calls Arraymancer “choose if you want a Nim tensor library with deep learning support for CPU, GPU, and embedded devices.”
Tensors and Dynamic neural networks in Python with strong GPU acceleration
102.7kPythonactive
mratsim/Arraymancer Alternatives
Arraymancer is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
Listed as an alternative to
These projects were analysed and named Arraymancer among their alternatives. The relationship is not symmetric — how Arraymancer rates them is a separate judgement, made when Arraymancer is analysed in its own right.
keras-team/kerasGitHub
calls Arraymancer “Choose for Nim projects needing a tensor library with deep learning support and embedded/GPU targets.”
Deep Learning for humans
64.3kPythonactive
tensorflow/tfjsGitHub
calls Arraymancer “when you need a Nim tensor library for CPU/GPU with metaprogramming.”
A WebGL accelerated JavaScript library for training and deploying ML models.
19.1kTypeScriptactive
tracel-ai/burnGitHub
calls Arraymancer “Choose when you work in Nim and need a tensor library with autograd and GPU/OpenCL backends.”
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
15.8kRustactive
Oneflow-Inc/oneflowGitHub
calls Arraymancer “choose if you program in Nim and need a tensor/DL library for CPU, GPU, or embedded targets”
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
9.4kC++slowing
apple/corenetGitHub
calls Arraymancer “When you need a Nim tensor/deep-learning library for a Nim codebase.”
CoreNet: A library for training deep neural networks
7.0kJupyter Notebookslowing