@fugood/onnxruntime-react-native/dist/typescript/NativeOnnxruntime.d.ts

ONNX Runtime bridge for react native

import type { TurboModule } from 'react-native/Libraries/TurboModule/RCTExport';
type SessionOptions = {};
type RunOptions = {};
/**
 * model loading information
 */
export type ModelLoadInfo = {
    /**
     * Key for an instance of InferenceSession, which is passed to run() function as parameter.
     */
    readonly key: string;
    /**
     * Get input names of the loaded model.
     */
    readonly inputNames: string[];
    /**
     * Get output names of the loaded model.
     */
    readonly outputNames: string[];
};
/**
 * JSIBlob is a blob object that exchange ArrayBuffer by OnnxruntimeJSIHelper.
 */
export type JSIBlob = {
    blobId: string;
    offset: number;
    size: number;
};
/**
 * Tensor type for react native, which doesn't allow ArrayBuffer in native bridge, so data will be stored as JSIBlob.
 */
export type EncodedTensor = {
    /**
     * the dimensions of the tensor.
     */
    readonly dims: readonly number[];
    /**
     * the data type of the tensor.
     */
    readonly type: string;
    /**
     * the JSIBlob object of the buffer data of the tensor.
     * if data is string array, it won't be stored as JSIBlob.
     */
    readonly data: JSIBlob | string[];
};
export type Feeds = {
    [name: string]: EncodedTensor;
};
export type Fetches = string[];
export type Return = {
    [name: string]: EncodedTensor;
};
export interface Spec extends TurboModule {
    loadModel(modelPath: string, options: SessionOptions): Promise<ModelLoadInfo>;
    loadModelFromBlob?(blob: JSIBlob, options: SessionOptions): Promise<ModelLoadInfo>;
    dispose(key: string): Promise<void>;
    run(key: string, feeds: Feeds, fetches: Fetches, options: RunOptions): Promise<Return>;
}
declare const _default: Spec | null;
export default _default;