react-native-executorch
Version:
An easy way to run AI models in React Native with ExecuTorch
56 lines (53 loc) • 2.51 kB
JavaScript
;
import { ResourceFetcher } from '../../utils/ResourceFetcher';
import { RnExecutorchErrorCode } from '../../errors/ErrorCodes';
import { parseUnknownError, RnExecutorchError } from '../../errors/errorUtils';
import { Logger } from '../../common/Logger';
import { VisionModule } from './VisionModule';
/**
* Module for generating image embeddings from input images.
* @category Typescript API
*/
export class ImageEmbeddingsModule extends VisionModule {
constructor(nativeModule) {
super();
this.nativeModule = nativeModule;
}
/**
* Creates an image embeddings instance for a built-in model.
* @param namedSources - An object specifying which built-in model to load and where to fetch it from.
* @param onDownloadProgress - Optional callback to monitor download progress, receiving a value between 0 and 1.
* @returns A Promise resolving to an `ImageEmbeddingsModule` instance.
*/
static async fromModelName(namedSources, onDownloadProgress = () => {}) {
try {
const paths = await ResourceFetcher.fetch(onDownloadProgress, namedSources.modelSource);
if (!paths?.[0]) {
throw new RnExecutorchError(RnExecutorchErrorCode.DownloadInterrupted, 'The download has been interrupted. As a result, not every file was downloaded. Please retry the download.');
}
return new ImageEmbeddingsModule(await global.loadImageEmbeddings(paths[0]));
} catch (error) {
Logger.error('Load failed:', error);
throw parseUnknownError(error);
}
}
/**
* Creates an image embeddings instance with a user-provided model binary.
* Use this when working with a custom-exported model that is not one of the built-in presets.
* @remarks The native model contract for this method is not formally defined and may change
* between releases. Refer to the native source code for the current expected tensor interface.
* @param modelSource - A fetchable resource pointing to the model binary.
* @param onDownloadProgress - Optional callback to monitor download progress, receiving a value between 0 and 1.
* @returns A Promise resolving to an `ImageEmbeddingsModule` instance.
*/
static fromCustomModel(modelSource, onDownloadProgress = () => {}) {
return ImageEmbeddingsModule.fromModelName({
modelName: 'custom',
modelSource
}, onDownloadProgress);
}
async forward(input) {
return new Float32Array(await super.forward(input));
}
}
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