import { isTensor3D, isTensor4D } from '../utils';
import { awaitMediaLoaded } from './awaitMediaLoaded';
import { isMediaElement } from './isMediaElement';
import { NetInput } from './NetInput';
import { resolveInput } from './resolveInput';
/**
 * Validates the input to make sure, they are valid net inputs and awaits all media elements
 * to be finished loading.
 *
 * @param input The input, which can be a media element or an array of different media elements.
 * @returns A NetInput instance, which can be passed into one of the neural networks.
 */
export async function toNetInput(inputs) {
    if (inputs instanceof NetInput) {
        return inputs;
    }
    let inputArgArray = Array.isArray(inputs)
        ? inputs
        : [inputs];
    if (!inputArgArray.length) {
        throw new Error('toNetInput - empty array passed as input');
    }
    const getIdxHint = (idx) => Array.isArray(inputs) ? ` at input index ${idx}:` : '';
    const inputArray = inputArgArray.map(resolveInput);
    inputArray.forEach((input, i) => {
        if (!isMediaElement(input) && !isTensor3D(input) && !isTensor4D(input)) {
            if (typeof inputArgArray[i] === 'string') {
                throw new Error(`toNetInput -${getIdxHint(i)} string passed, but could not resolve HTMLElement for element id ${inputArgArray[i]}`);
            }
            throw new Error(`toNetInput -${getIdxHint(i)} expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id`);
        }
        if (isTensor4D(input)) {
            // if tf.Tensor4D is passed in the input array, the batch size has to be 1
            const batchSize = input.shape[0];
            if (batchSize !== 1) {
                throw new Error(`toNetInput -${getIdxHint(i)} tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`);
            }
        }
    });
    // wait for all media elements being loaded
    await Promise.all(inputArray.map(input => isMediaElement(input) && awaitMediaLoaded(input)));
    return new NetInput(inputArray, Array.isArray(inputs));
}
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