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[WIP] Add support for deepseek-ai/Janus-1.3B (any-to-any) #1001

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54 changes: 54 additions & 0 deletions src/base/feature_extraction_utils.js
Original file line number Diff line number Diff line change
@@ -0,0 +1,54 @@
import { FEATURE_EXTRACTOR_NAME } from "../utils/constants.js";
import { Callable } from "../utils/generic.js";
import { getModelJSON } from "../utils/hub.js";

/**
* Base class for feature extractors.
*/
export class FeatureExtractor extends Callable {
/**
* Constructs a new FeatureExtractor instance.
*
* @param {Object} config The configuration for the feature extractor.
*/
constructor(config) {
super();
this.config = config
}

/**
* Instantiate one of the processor classes of the library from a pretrained model.
*
* The processor class to instantiate is selected based on the `image_processor_type` (or `feature_extractor_type`; legacy)
* property of the config object (either passed as an argument or loaded from `pretrained_model_name_or_path` if possible)
*
* @param {string} pretrained_model_name_or_path The name or path of the pretrained model. Can be either:
* - A string, the *model id* of a pretrained processor hosted inside a model repo on huggingface.co.
* Valid model ids can be located at the root-level, like `bert-base-uncased`, or namespaced under a
* user or organization name, like `dbmdz/bert-base-german-cased`.
* - A path to a *directory* containing processor files, e.g., `./my_model_directory/`.
* @param {import('../utils/hub.js').PretrainedOptions} options Additional options for loading the processor.
*
* @returns {Promise<FeatureExtractor>} A new instance of the Processor class.
*/
static async from_pretrained(pretrained_model_name_or_path, options) {
const preprocessorConfig = await getModelJSON(pretrained_model_name_or_path, FEATURE_EXTRACTOR_NAME, true, options);
return new this(preprocessorConfig);
}
}


/**
* Helper function to validate audio inputs.
* @param {any} audio The audio data.
* @param {string} feature_extractor The name of the feature extractor.
* @private
*/
export function validate_audio_inputs(audio, feature_extractor) {
if (!(audio instanceof Float32Array || audio instanceof Float64Array)) {
throw new Error(
`${feature_extractor} expects input to be a Float32Array or a Float64Array, but got ${audio?.constructor?.name ?? typeof audio} instead. ` +
`If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`
)
}
}
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