Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/orktes/go-torch
LibTorch (PyTorch) bindings for Golang
https://github.com/orktes/go-torch
golang golang-library machine-learning pytorch
Last synced: 3 months ago
JSON representation
LibTorch (PyTorch) bindings for Golang
- Host: GitHub
- URL: https://github.com/orktes/go-torch
- Owner: orktes
- License: other
- Created: 2019-02-18T18:44:22.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-04-23T06:00:20.000Z (over 3 years ago)
- Last Synced: 2024-07-22T23:51:36.955Z (4 months ago)
- Topics: golang, golang-library, machine-learning, pytorch
- Language: Go
- Size: 31.3 KB
- Stars: 245
- Watchers: 9
- Forks: 34
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-ai-ml-dl - Go-Torch Go binding for pytorch
README
EVERYHING IS REALLY OUT-OF-DATE. FOR A MORE UP-TO-DATE BINDINGS I RECOMMEND CHECKING OUT https://github.com/wangkuiyi/gotorch OR OTHER PACKAGES AVAILABLE.
WORK IN PROGRESS... USE AT OWN RISK :-)
[![Build Status](https://travis-ci.org/orktes/go-torch.svg?branch=master)](https://travis-ci.org/orktes/go-torch)
[![GoDoc](https://godoc.org/github.com/orktes/go-torch?status.svg)](http://godoc.org/github.com/orktes/go-torch)# go-torch
LibTorch (PyTorch) bindings for Golang. Library is first and foremost designed for running inference against serialized models exported from Python version of PyTorch. Library can also be used to compile TorchScript applications directly from Go.
## Installing
```sh
$ go get github.com/orktes/go-torch
```## Usage
go-torch depends on the LibTorch shared library to be available. For more information refer to https://pytorch.org/cppdocs/. The is also an example [Dockerfile](https://github.com/orktes/go-torch/blob/master/scripts/Dockerfile) which is used for executing tests for the library.
```go
import (
"github.com/orktes/go-torch"
)
```### Creating Tensors
Supported scalar types:
- torch.Byte `uint8`
- torch.Char `int8`
- torch.Int `int32`
- torch.Long `int64`
- torch.Float `float32`
- torch.Double `float64````go
matrix := []float32{
[]float32{1,2,3},
[]float32{4,5,6},
}
tensor, _ := torch.NewTensor(matrix)
tensor.Shape() // [2, 3]
tensor.DType() // torch.Float
```### Using serialized PyTorch models
For instructions on how to export models for PyTorch refer to the [PyTorch documentation](https://pytorch.org/tutorials/advanced/cpp_export.html)
```go
// Load model
module, _ := torch.LoadJITModule("model.pt")// Create an input tensor
inputTensor, _ := torch.NewTensor([][]float32{
[]float32{1, 2, 3},
})// Forward propagation
res, _ := module.Forward(inputTensor)```
### Using TorchScript
[TorchScript documentation](https://pytorch.org/docs/stable/jit.html)
Currently supported input and output types
- Tensor
- Tuple (of Tensor and/or nested Tuples)```go
sumScript = `
def sum(a, b):
return a + b
`// Compile TorchScript
module, _ := torch.CompileTorchScript(sumScript)// Create inputs
a, _ := torch.NewTensor([]float32{1})
b, _ := torch.NewTensor([]float32{2})res, _ := module.RunMethod("sum", a, b)
fmt.Printf("[1] + [2] = %+v\n", res.(*torch.Tensor).Value())
// output: [1] + [2] = [3]```
## Acknowledgements
Lots of the functionality related to converting Golang types to PyTorch Tensors are a shameless copy on what Google is doing with their Go Tensorflow bindings. Therefore big part of the credit definetely goes to The TensorFlow Authors.
## LICENSE
[See here](https://github.com/orktes/go-torch/blob/master/LICENSE)