Crate tensorflux

Interface to TensorFlow.

Example

Create a graph in 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.write_graph(tf.Session().graph_def, '', 'graph.pb', as_text=False)

Evaluate the graph in 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::<f32>());
assert_eq!(&c[..], &[1.0 * 4.0, 2.0 * 5.0, 3.0 * 6.0]);

Structs

Buffer	A buffer.
Error	An error.
Input	An input.
Library	A library.
Options	Options.
Output	An output.
Session	A session.
Target	A target.
Tensor	A tensor.

Traits

Value

A value.

Type Definitions

Result	A result.
c32	A complex number with 32-bit parts.
c64	A complex number with 64-bit parts.