wehub-resource-sync
121 lines
4.2 KiB
JavaScript
121 lines
4.2 KiB
JavaScript
import { AutoProcessor } from "../../src/transformers.js";
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import { hamming, hanning, mel_filter_bank } from "../../src/utils/audio.js";
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import { getFile } from "../../src/utils/hub.js";
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import { RawImage } from "../../src/utils/image.js";
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import { MAX_TEST_EXECUTION_TIME } from "../init.js";
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describe("Utilities", () => {
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describe("Audio utilities", () => {
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it(
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"should calculate MEL filters",
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async () => {
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// NOTE: Uses official HF implementation as reference:
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const processor = await AutoProcessor.from_pretrained("openai/whisper-tiny.en");
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const config = processor.feature_extractor.config;
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// True MEL filters
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const original_mel_filters = config.mel_filters;
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// Calculated MEL filters
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const calculated_mel_filters = mel_filter_bank(
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Math.floor(1 + config.n_fft / 2), // num_frequency_bins
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config.feature_size, // num_mel_filters
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0.0, // min_frequency
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8000.0, // max_frequency
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config.sampling_rate, // sampling_rate
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"slaney", // norm
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"slaney", // mel_scale
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);
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const original = original_mel_filters.flat();
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const calculated = calculated_mel_filters.flat();
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// Compute max difference
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const maxdiff = original.reduce((maxdiff, _, i) => {
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const diff = Math.abs(original[i] - calculated[i]);
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return Math.max(maxdiff, diff);
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}, -Infinity);
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expect(maxdiff).toBeGreaterThanOrEqual(0);
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expect(maxdiff).toBeLessThan(1e-6);
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},
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MAX_TEST_EXECUTION_TIME,
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);
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it(
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"should calculate window",
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async () => {
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expect(hanning(10)).toBeCloseToNested(new Float64Array([0.0, 0.11697777844051105, 0.41317591116653485, 0.75, 0.9698463103929542, 0.9698463103929542, 0.75, 0.41317591116653485, 0.11697777844051105, 0.0]));
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expect(hamming(10)).toBeCloseToNested(new Float64Array([0.08000000000000002, 0.1876195561652702, 0.46012183827321207, 0.7700000000000001, 0.9722586055615179, 0.9722586055615179, 0.7700000000000001, 0.46012183827321207, 0.1876195561652702, 0.08000000000000002]));
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},
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MAX_TEST_EXECUTION_TIME,
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);
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});
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describe("Hub utilities", () => {
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it("Read data from blob", async () => {
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const blob = new Blob(["Hello, world!"], { type: "text/plain" });
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const blobUrl = URL.createObjectURL(blob);
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const data = await getFile(blobUrl);
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expect(await data.text()).toBe("Hello, world!");
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});
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});
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describe("Image utilities", () => {
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const [width, height, channels] = [2, 2, 3];
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const data = Uint8Array.from({ length: width * height * channels }, (_, i) => i % 5);
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const tiny_image = new RawImage(data, width, height, channels);
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let image;
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beforeAll(async () => {
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image = await RawImage.fromURL("https://picsum.photos/300/200");
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});
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it("Can split image into separate channels", async () => {
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const image_data = tiny_image.split().map((x) => x.data);
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const target = [
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new Uint8Array([0, 3, 1, 4]), // Reds
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new Uint8Array([1, 4, 2, 0]), // Greens
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new Uint8Array([2, 0, 3, 1]), // Blues
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];
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expect(image_data).toEqual(target);
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});
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it("Can splits channels for grayscale", async () => {
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const image_data = tiny_image
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.grayscale()
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.split()
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.map((x) => x.data);
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const target = [new Uint8ClampedArray([1, 3, 2, 1])];
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expect(image_data).toEqual(target);
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});
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it("Read image from URL", async () => {
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expect(image.width).toBe(300);
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expect(image.height).toBe(200);
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expect(image.channels).toBe(3);
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});
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it("Can resize image", async () => {
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const resized = await image.resize(150, 100);
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expect(resized.width).toBe(150);
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expect(resized.height).toBe(100);
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});
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it("Can resize with aspect ratio", async () => {
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const resized = await image.resize(150, null);
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expect(resized.width).toBe(150);
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expect(resized.height).toBe(100);
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});
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it("Returns original image if width and height are null", async () => {
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const resized = await image.resize(null, null);
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expect(resized.width).toBe(300);
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expect(resized.height).toBe(200);
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});
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});
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});
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