transformers-fork/src/models/qwen2_vl/processing_qwen2_vl.js

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import { Processor } from "../../base/processing_utils.js";
import { AutoImageProcessor } from "../auto/image_processing_auto.js";
import { AutoTokenizer } from "../../tokenizers.js";
import { RawImage } from "../../utils/image.js";

export class Qwen2VLProcessor extends Processor {
    static image_processor_class = AutoImageProcessor
    static tokenizer_class = AutoTokenizer

    /**
     * 
     * @param {string|string[]} text 
     * @param {RawImage|RawImage[]} images 
     * @param  {...any} args 
     * @returns {Promise<any>}
     */
    async _call(text, images = null, ...args) {

        if (!Array.isArray(text)) {
            text = [text];
        }

        let image_inputs, image_grid_thw;

        if (images) {
            image_inputs = await this.image_processor(images);
            image_grid_thw = image_inputs.image_grid_thw;
        }

        if (image_grid_thw) {
            let merge_length = this.image_processor.config.merge_size ** 2;
            let index = 0;

            const image_grid_thw_list = image_grid_thw.tolist();
            text = text.map(t => {
                while (t.includes("<|image_pad|>")) {
                    const prod = Number(image_grid_thw_list[index++].reduce((a, b) => a * b, 1n));
                    t = t.replace("<|image_pad|>", "<|placeholder|>".repeat(Math.floor(prod / merge_length)));
                }
                return t.replaceAll("<|placeholder|>", "<|image_pad|>");
            });
        }

        const text_inputs = this.tokenizer(text);

        return {
            ...text_inputs,
            ...image_inputs,
            // TODO: ...videos_inputs,
        }
    }
}