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https://github.com/ankane/tensorflow-ruby
Deep learning for Ruby
https://github.com/ankane/tensorflow-ruby
Last synced: 4 days ago
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Deep learning for Ruby
- Host: GitHub
- URL: https://github.com/ankane/tensorflow-ruby
- Owner: ankane
- License: apache-2.0
- Created: 2019-09-18T06:37:23.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-12-26T14:50:20.000Z (10 months ago)
- Last Synced: 2024-05-19T03:00:34.833Z (6 months ago)
- Language: Ruby
- Homepage:
- Size: 233 KB
- Stars: 369
- Watchers: 16
- Forks: 13
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# TensorFlow Ruby
:fire: [TensorFlow](https://github.com/tensorflow/tensorflow) - the end-to-end machine learning platform - for Ruby
This gem is currently experimental and only supports basic tensor operations at the moment. Check out [Torch.rb](https://github.com/ankane/torch-rb) for a more complete deep learning library.
To run a TensorFlow model in Ruby, [convert it to ONNX](https://github.com/onnx/tensorflow-onnx) and use [ONNX Runtime](https://github.com/ankane/onnxruntime). Check out [this tutorial](https://ankane.org/tensorflow-ruby) for a full example.
[](https://github.com/ankane/tensorflow-ruby/actions)
## Installation
[Install TensorFlow](#tensorflow-installation). For Homebrew, use:
```sh
brew install libtensorflow
```
Add this line to your application’s Gemfile:
```ruby
gem "tensorflow"
```
## Getting Started
This library follows the TensorFlow 2 [Python API](https://www.tensorflow.org/api_docs/python/tf). Many methods and options are missing at the moment. Here’s the [current plan](https://github.com/ankane/tensorflow/issues/1). Additional PRs welcome!
## Constants
```ruby
a = Tf.constant([1, 2, 3])
b = Tf.constant([4, 5, 6])
a + b
```
## Variables
```ruby
v = Tf::Variable.new(0.0)
w = v + 1
```
## Math
```ruby
Tf::Math.abs([-1, -2])
Tf::Math.sqrt([1.0, 4.0, 9.0])
```
## FizzBuzz
```ruby
def fizzbuzz(max_num)
max_num.times do |i|
num = Tf.constant(i + 1)
if (num % 3).to_i == 0 && (num % 5).to_i == 0
puts "FizzBuzz"
elsif (num % 3).to_i == 0
puts "Fizz"
elsif (num % 5).to_i == 0
puts "Buzz"
else
puts num.to_i
end
end
end
fizzbuzz(15)
```
## Data::Dataset
```ruby
# load
train_dataset = Tf::Data::Dataset.from_tensor_slices([train_examples, train_labels])
test_dataset = Tf::Data::Dataset.from_tensor_slices([test_examples, test_labels])
# shuffle and batch
train_dataset = train_dataset.shuffle(100).batch(32)
test_dataset = test_dataset.batch(32)
# iterate
train_dataset.each do |examples, labels|
# ...
end
```
## Keras [coming soon]
```ruby
mnist = Tf::Keras::Datasets::MNIST
(x_train, y_train), (x_test, y_test) = mnist.load_data
x_train = x_train / 255.0
x_test = x_test / 255.0
model = Tf::Keras::Models::Sequential.new([
Tf::Keras::Layers::Flatten.new(input_shape: [28, 28]),
Tf::Keras::Layers::Dense.new(128, activation: "relu"),
Tf::Keras::Layers::Dropout.new(0.2),
Tf::Keras::Layers::Dense.new(10, activation: "softmax")
])
model.compile(optimizer: "adam", loss: "sparse_categorical_crossentropy", metrics: ["accuracy"])
model.fit(x_train, y_train, epochs: 5)
model.evaluate(x_test, y_test)
```
## TensorFlow Installation
### Mac
Run:
```sh
brew install tensorflow
```
Alternatively, download the [shared library](https://www.tensorflow.org/install/lang_c#download) and move the files in `lib` to `/usr/local/lib`.
### Linux
Download the [shared library](https://www.tensorflow.org/install/lang_c#download) and move the files in `lib` to `/usr/local/lib`.
### Windows
Download the [shared library](https://www.tensorflow.org/install/lang_c#download) and move `tensorflow.dll` to `C:\Windows\System32`.
## History
View the [changelog](https://github.com/ankane/tensorflow-ruby/blob/master/CHANGELOG.md)
## Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- [Report bugs](https://github.com/ankane/tensorflow-ruby/issues)
- Fix bugs and [submit pull requests](https://github.com/ankane/tensorflow-ruby/pulls)
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
```sh
git clone https://github.com/ankane/tensorflow-ruby.git
cd tensorflow-ruby
bundle install
bundle exec rake test
```