The package provides an interface to TensorFlow.
Create a graph in Python:
```python import tensorflow as tf
with tf.Session() as session: a = tf.Variable(0.0, name='a') b = tf.Variable(0.0, name='b') c = tf.mul(a, b, name='c') tf.train.writegraph(session.graphdef, '', 'graph.pb', as_text=False) ```
Evaluate the graph in Rust:
```rust use tensorflux::{Definition, Input, Options, Output, Session, Tensor};
let mut session = Session::new(&Options::new().unwrap()).unwrap(); session.extend(&Definition::load(GRAPH_PATH).unwrap()).unwrap(); // c = a * b
let mut inputs = vec![Input::new("a"), Input::new("b")]; inputs[0].set(Tensor::new(vec![1f32, 2.0, 3.0], &[3]).unwrap()); inputs[1].set(Tensor::new(vec![4f32, 5.0, 6.0], &[3]).unwrap());
let mut outputs = vec![Output::new("c")];
session.run(&mut inputs, &mut outputs, &vec![]).unwrap();
let result = outputs[0].get::
Your contribution is highly appreciated. Do not hesitate to open an issue or a pull request. Note that any contribution submitted for inclusion in the project will be licensed according to the terms given in LICENSE.md.