mnn 0.2.0

Rust bindings for MNN, a lightweight deep neural network inference engine.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44

mod common;
use common::*;

#[test]
pub fn test_resizing() -> Result<()> {
    let model = std::fs::read("tests/assets/resizing.mnn").expect("No resizing model");
    let mut net = Interpreter::from_bytes(&model).unwrap();
    net.set_cache_file("resizing.cache", 128)?;
    let config = ScheduleConfig::default();
    #[cfg(feature = "opencl")]
    config.set_type(ForwardType::OpenCL);
    let mut session = net.create_session(config).unwrap();
    net.update_cache_file(&mut session)?;

    let now = std::time::Instant::now();
    let mut mask = unsafe { net.input_unresized::<f32>(&session, "mask") }?;
    net.resize_tensor(&mut mask, [2048, 2048]);
    drop(mask);

    let mut og = unsafe { net.input_unresized::<f32>(&session, "original") }?;
    net.resize_tensor(&mut og, [2048, 2048, 3]);
    drop(og);

    let mut pain = unsafe { net.input_unresized::<f32>(&session, "inpainted") }?;
    net.resize_tensor(&mut pain, [2048, 2048, 3]);
    drop(pain);

    net.resize_session(&mut session);
    let inputs = net.inputs(&session);
    for tensor_info in inputs.iter() {
        let tensor = tensor_info.tensor::<f32>().unwrap();
        println!(
            "{:13}: {:>13}",
            tensor_info.name(),
            format!("{:?}", tensor.shape())
        );
        let mut host = tensor.create_host_tensor_from_device(false);
        host.host_mut().fill(1.0);
    }
    drop(inputs);
    net.run_session(&session).unwrap();
    println!("{:?}", now.elapsed());
    Ok(())
}