The package provides an interface to TensorFlow.
Create a graph in Python:
```python import tensorflow as tf
a = tf.placeholder(tf.float32, name='a') b = tf.placeholder(tf.float32, name='b') c = tf.mul(a, b, name='c')
tf.train.writegraph(tf.Session().graphdef, '', 'graph.pb', as_text=False) ```
Evaluate the graph in Rust:
```rust use tensorflux::{Buffer, Input, Options, Output, Session, Tensor};
macro_rules! ok(($result:expr) => ($result.unwrap()));
let graph = "graph.pb"; // c = a * b let mut session = ok!(Session::new(&ok!(Options::new()))); ok!(session.extend(&ok!(Buffer::load(graph))));
let a = ok!(Tensor::new(vec![1f32, 2.0, 3.0], &[3])); let b = ok!(Tensor::new(vec![4f32, 5.0, 6.0], &[3]));
let inputs = vec![Input::new("a", a), Input::new("b", b)]; let mut outputs = vec![Output::new("c")]; ok!(session.run(&inputs, &mut outputs, &[], None, None));
let c = ok!(outputs[0].get::
This and other examples can be found in the examples directory.
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.