README.Rmd

---
output: github_document
---
 
<!-- README.md is generated from README.Rmd. Please edit that file -->

```{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 <a href='https://torch.mlverse.org'><img src='man/figures/torch.png' align="right" height="139" /></a>

[![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.