Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4][5][6]

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

Jun 6, 2017 · Torch provides lua wrappers to the THNN library while Pytorch provides Python wrappers for the same. PyTorch's recurrent nets, weight sharing and memory usage with the flexibility of interfacing with C, and the current speed of Torch.

The first script installs the basic package dependencies that LuaJIT and Torch require. The second script installs LuaJIT, LuaRocks, and then uses LuaRocks (the lua package manager) to install core packages like torch, nn and paths, as well as a few other packages.

具体来讲，我会将Torch中搭建网络的常用技巧，变量，模型，以及支持计算图的nngraph包都进行一个简单的介绍。 相比于官方教程，本篇博客更像是一个学习笔记，目的在于帮助自己快速回忆起Torch相关的开发细节。 阅读时间：30分钟。 符合如下条件之一： 1. 了解过Torch，或对Torch有过开发经验。 2. 了解其他某个深度学习框架，并掌握了LUA语言的基本语法。 安装教程： torch.ch/docs/getting-s. 注意Torch不支持9.2之后的CUDA版本。 因此，不能再RTX 20XX系列 …

Covers the basics (Lua, Torch ’s Tensor and image package) and intruduces the concepts of neural networks, forward and backward propagation (both by-hand using Tensor s and with the nn package).

Jan 17, 2018 · Introduction: Torch is a scientific computing framework which is based on LuaJIT (Lua just in-time compiler) and of we will code in Lua language.

Torch is a scientific computing framework based on Lua with CPU and GPU backends. You can imagine like a Numpy but with CPU and GPU implementation. Some nice features:

This article is a collection of Torch examples meant as introduction to get started with Lua and Torch for deep learning research. The examples can also be considered individually and cover common use cases such as training on CPU and GPU, weight initialization and visualization, custom modules and criteria as well as saving and fine-tuning models.

Nov 15, 2022 · There are several options to run Torch on Windows. At the moment, the easiest approach is to run Ubuntu inside a virtual machine and install Torch there. This way everything just works, but the downside is that you will quite likely lose GPU acceleration.