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https://github.com/ekrich/stensorflow

Scala Native support for the TensorFlow C API on Linux and macOS
https://github.com/ekrich/stensorflow

linux machine-learning macos neural-networks scala scala-native tensorflow

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Scala Native support for the TensorFlow C API on Linux and macOS

Host: GitHub
URL: https://github.com/ekrich/stensorflow
Owner: ekrich
License: other
Created: 2019-06-14T19:48:05.000Z (over 5 years ago)
Default Branch: main
Last Pushed: 2024-09-16T15:38:29.000Z (11 days ago)
Last Synced: 2024-09-18T11:30:20.024Z (9 days ago)
Topics: linux, machine-learning, macos, neural-networks, scala, scala-native, tensorflow
Language: Scala
Homepage:
Size: 192 KB
Stars: 39
Watchers: 8
Forks: 2
Open Issues: 1
Metadata Files:
- Readme: README.md
- License: LICENSE.md

Awesome Lists containing this project

README

# stensorflow - Scala Native TensorFlow
![CI](https://github.com/ekrich/stensorflow/workflows/CI/badge.svg)

This library implements the C TensorFlow API adapted for the Scala Native platform.

Scala Native is a unique platform that
marries the high level language of Scala but compiles to native code with a
lightweight managed runtime which includes a state of the art garbage collector.
The combination allows for great programming and the ability to use high
performance C language libraries like TensorFlow.

Scala Native uses the Scala compiler to produce
[NIR](https://scala-native.readthedocs.io/en/latest/contrib/nir.html)
(Native Intermediate Representation) that is optimized and then
converted to [LLVM IR](http://llvm.org/). Finally LLVM code is optimized
and compiled by [Clang](http://clang.llvm.org/) to produce a native executable.

## Getting started
[![Maven Central](https://img.shields.io/maven-central/v/org.ekrich/stensorflow_native0.5_3.svg)](https://maven-badges.herokuapp.com/maven-central/org.ekrich/stensorflow_native0.5_3)

You can use the Gitter8 template [stensorflow.g8](https://github.com/ekrich/stensorflow.g8#stensorflowg8) to get started. The linked directions will send you back here to install the Tensorflow library below but it should be easier overall.

If you are already familiar with Scala Native you can jump right in by adding the following dependency in your `sbt` build file. Refer to the `TensorflowTest.scala` source in this repository or in the template referred to above for an example.

```scala
libraryDependencies += "org.ekrich" %%% "stensorflow" % "x.y.z"
```

To use in `sbt`, replace `x.y.z` with the version from Maven Central badge above.
All available versions can be seen at the [Maven Repository](https://mvnrepository.com/artifact/org.ekrich/stensorflow).

Otherwise follow the [Getting Started](https://scala-native.readthedocs.io/en/latest/user/setup.html)
instructions for Scala Native if you are not already setup.

## Scala Build Versions

| Scala Version | Native (0.5.x) |
| ---------------------- | :-------------------: |
| 3.3.x (LTS) | ✅ |

* Use version `0.5.0` for Scala Native `0.5.x`.
* Use version `0.3.0` for Scala Native `0.4.9+`.

Note: Refer to release notes for older versions of Scala and Scala Native

## Tensorflow library

The TensorFlow C library is required and the current version is `2.16.1`
with `2.5.0` pre-built for Linux.

* Linux/Ubuntu can TensorFlow following the following directions:

https://www.tensorflow.org/install/lang_c

The essential directions are repeated here replacing `` with the above:

```
$ FILENAME=libtensorflow-cpu-linux-x86_64-.tar.gz
$ wget -q --no-check-certificate https://storage.googleapis.com/tensorflow/libtensorflow/${FILENAME}
$ sudo tar -C /usr/local -xzf ${FILENAME}
$ sudo ldconfig /usr/local/lib
```

* macOS can install TensorFlow using [Homebrew](https://formulae.brew.sh/formula/libtensorflow)
which will install into the `/usr/local/Cellar/libtensorflow/` directory.

Note: macOS 12 or greater is recommended to install TensorFlow via
Homebrew and is used in CI. Tensorflow `2.16.1` is built for macos `13.1` so you
will get a linking warning if using an older OS version.

```
$ brew install libtensorflow
```

* Other OSes need to have `libtensorflow` available on the system.

## Usage and Help
[![scaladoc](https://www.javadoc.io/badge/org.ekrich/stensorflow_native0.5_3.svg?label=scaladoc)](https://www.javadoc.io/doc/org.ekrich/stensorflow_native0.5_3)
[![Discord](https://img.shields.io/discord/633356833498595365.svg?label=&logo=discord&logoColor=ffffff&color=404244&labelColor=6A7EC2)](https://discord.gg/XSj6hQs)

Reference the link above for Scaladoc. The documentation is a little sparse but hopefully will improve with time.

After `sbt` is installed and any other Scala Native prerequisites are met you can use the following Gitter G8 template instructions to get a fully functional Scala Native application with an example in the body of the main program.

```
$ sbt new ekrich/stensorflow.g8
$ cd
$ sbt run
```

In addition, look at the [stensorflow unit tests](https://github.com/ekrich/stensorflow/blob/main/stensorflow/src/test/scala/org/ekrich/tensorflow/unsafe/TensorflowTest.scala) for other examples of usage.

## TensorFlow References and External Documentation

[TensorFlow Website](https://www.tensorflow.org/)

[TensorFlow for JVM using JNI](https://platanios.org/tensorflow_scala/)

## Tensorflow for Scala Native contributors

The Language Server `clangd` can be used to help development using VSCode or other editors. For VSCode see the `clangd` plugin on the [Visual Studio Marketplace](https://marketplace.visualstudio.com/items?itemName=llvm-vs-code-extensions.vscode-clangd) for more info.

Add a `compile_flags.txt` with the following content to the `stensorflow/src/main/resources/scala-native` directory.

```
# Tensorflow Setup
# Standard path on macOS arm
-I
/opt/homebrew/include
```

Change the path to match your include path. There is a small amount of official documentation that contains info about [compile_flags.txt](https://clang.llvm.org/docs/JSONCompilationDatabase.html). Otherwise some other info can be found online.

## Versions

Release [0.5.0](https://github.com/ekrich/stensorflow/releases/tag/v0.5.0) - (2024-04-11)

Release [0.4.0](https://github.com/ekrich/stensorflow/releases/tag/v0.4.0) - (2024-03-01)

Release [0.3.0](https://github.com/ekrich/stensorflow/releases/tag/v0.3.0) - (2022-11-29)

Release [0.2.0](https://github.com/ekrich/stensorflow/releases/tag/v0.2.0) - (2021-12-13)

Release [0.1.0](https://github.com/ekrich/stensorflow/releases/tag/v0.1.0) - (2021-07-02)