1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798
use js_sys::{Array, Float32Array, Uint8Array};use ndarray::ArrayD;
use wasm_bindgen::{prelude::wasm_bindgen, JsValue};
use crate::{CPUBackend, Dataset, Logger, PredictOptions, TrainOptions, RESOURCES};
#[wasm_bindgen]extern "C" {    #[wasm_bindgen(js_namespace = console)]    fn log(s: &str);}
fn console_log(string: String) {    log(string.as_str())}
#[wasm_bindgen]pub fn wasm_backend_create(config: String, shape: Array) -> usize {    let config = serde_json::from_str(&config).unwrap();    let mut len = 0;    let logger = Logger { log: console_log };    let net_backend = CPUBackend::new(config, logger, None);    shape.set_length(net_backend.size.len() as u32);    for (i, s) in net_backend.size.iter().enumerate() {        shape.set(i as u32, JsValue::from(*s))    }
    RESOURCES.with(|cell| {        let mut backend = cell.backend.borrow_mut();        len = backend.len();        backend.push(net_backend);    });    len}
#[wasm_bindgen]pub fn wasm_backend_train(id: usize, buffers: Vec<Float32Array>, options: String) {    let options: TrainOptions = serde_json::from_str(&options).unwrap();
    let mut datasets = Vec::new();    for i in 0..options.datasets {        let input = buffers[i * 2].to_vec();        let output = buffers[i * 2 + 1].to_vec();        datasets.push(Dataset {            inputs: ArrayD::from_shape_vec(options.input_shape.clone(), input).unwrap(),            outputs: ArrayD::from_shape_vec(options.output_shape.clone(), output).unwrap(),        });    }
    RESOURCES.with(|cell| {        let mut backend = cell.backend.borrow_mut();        backend[id].train(datasets, options.epochs, options.batches, options.rate)    });}
#[wasm_bindgen]pub fn wasm_backend_predict(id: usize, buffer: Float32Array, options: String) -> Float32Array {    let options: PredictOptions = serde_json::from_str(&options).unwrap();    let inputs = ArrayD::from_shape_vec(options.input_shape, buffer.to_vec()).unwrap();
    let mut res = ArrayD::zeros(options.output_shape);
    RESOURCES.with(|cell| {        let mut backend = cell.backend.borrow_mut();        res = backend[id].predict(inputs);    });    Float32Array::from(res.as_slice().unwrap())}
#[wasm_bindgen]pub fn wasm_backend_save(id: usize) -> Uint8Array {    let mut buffer = Vec::new();    RESOURCES.with(|cell| {        let backend = cell.backend.borrow_mut();        buffer = backend[id].save();    });    Uint8Array::from(buffer.as_slice())}
#[wasm_bindgen]pub fn wasm_backend_load(buffer: Uint8Array, shape: Array) -> usize {    let mut len = 0;    let logger = Logger { log: console_log };    let net_backend = CPUBackend::load(buffer.to_vec().as_slice(), logger);    shape.set_length(net_backend.size.len() as u32);    for (i, s) in net_backend.size.iter().enumerate() {        shape.set(i as u32, JsValue::from(*s))    }
    RESOURCES.with(|cell| {        let mut backend = cell.backend.borrow_mut();        len = backend.len();        backend.push(net_backend);    });    len}