https://github.com/mlverse/torch

R Interface to Torch
https://github.com/mlverse/torch

autograd deep-learning r torch

Last synced: 2 months ago
JSON representation

R Interface to Torch

• Host: GitHub
• URL: https://github.com/mlverse/torch
• Owner: mlverse
• License: other
• Created: 2020-01-07T14:56:32.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2025-04-08T13:51:54.000Z (3 months ago)
• Last Synced: 2025-04-13T06:14:57.424Z (3 months ago)
• Topics: autograd, deep-learning, r, torch
• Language: C++
• Homepage: https://torch.mlverse.org
• Size: 137 MB
• Stars: 525
• Watchers: 18
• Forks: 79
• Open Issues: 114
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

README

        
---

output: github_document

---

 

```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

torch::torch_manual_seed(1)

```

# torch 

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html)

[![Test](https://github.com/mlverse/torch/actions/workflows/main.yaml/badge.svg)](https://github.com/mlverse/torch/actions/workflows/main.yaml)

[![CRAN status](https://www.r-pkg.org/badges/version/torch)](https://CRAN.R-project.org/package=torch)

[![](https://cranlogs.r-pkg.org/badges/torch)](https://cran.r-project.org/package=torch)

[![Discord](https://img.shields.io/discord/837019024499277855?logo=discord)](https://discord.com/invite/s3D5cKhBkx)

## Installation

torch can be installed from CRAN with:

```r

install.packages("torch")

```

You can also install the development version with:

```r

remotes::install_github("mlverse/torch")

```

At the first package load additional software will be 

installed. See also the full [installation guide](https://torch.mlverse.org/docs/articles/installation.html) here.

## Examples

You can create torch tensors from R objects with the `torch_tensor` function and convert them back to R objects with `as_array`.

```{r}

library(torch)

x <- array(runif(8), dim = c(2, 2, 2))

y <- torch_tensor(x, dtype = torch_float64())

y

identical(x, as_array(y))

```

### Simple Autograd Example

In the following snippet we let torch, using the autograd feature, calculate the derivatives:

```{r}

x <- torch_tensor(1, requires_grad = TRUE)

w <- torch_tensor(2, requires_grad = TRUE)

b <- torch_tensor(3, requires_grad = TRUE)

y <- w * x + b

y$backward()

x$grad

w$grad

b$grad

```

## Contributing

No matter your current skills it's possible to contribute to `torch` development.

See the [contributing guide](https://torch.mlverse.org/docs/contributing) for more information.