coaster 0.2.0

high-performance computation on any hardware
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

use coaster as co;
use coaster_nn as nn;
#[cfg(feature = "cuda")]
use rcublas;

#[cfg(feature = "cuda")]
use co::frameworks::cuda::get_cuda_backend;
use co::frameworks::native::flatbox::FlatBox;
#[cfg(not(feature = "cuda"))]
use co::frameworks::native::get_native_backend;
use co::prelude::*;
use nn::*;

fn write_to_memory<T: Copy>(mem: &mut FlatBox, data: &[T]) {
    let mem_buffer = mem.as_mut_slice::<T>();
    for (index, datum) in data.iter().enumerate() {
        mem_buffer[index] = *datum;
    }
}

fn main() {
    #[cfg(feature = "cuda")]
    let backend = get_cuda_backend();

    #[cfg(not(feature = "cuda"))]
    let backend = get_native_backend();

    // Initialize two SharedTensors.
    let mut x = SharedTensor::<f32>::new(&(1, 1, 3));
    // let mut result = SharedTensor::<f32>::new(&(1, 1, 3));
    // Fill `x` with some data.
    let payload: &[f32] = &::std::iter::repeat(1f32)
        .take(x.capacity())
        .collect::<Vec<f32>>();
    let native = Backend::<Native>::default().unwrap();
    write_to_memory(x.write_only(native.device()).unwrap(), payload); // Write to native host memory.
                                                                      // Run the sigmoid operation, provided by the NN Plugin, on your CUDA enabled GPU.
                                                                      // FIXME: Sigmoid cannot be included from coaster-nn without using cuda and native features
                                                                      // from coaster-nn. This causes the error https://github.com/rust-lang/cargo/issues/6915 ,
                                                                      // and so sigmoid has been disabled for now.
                                                                      // backend.sigmoid(&mut x, &mut result).unwrap();
                                                                      // See the result.
                                                                      // println!("{:?}", result.read(native.device()).unwrap().as_slice::<f32>());
}