Spaces:
Running
Running
File size: 2,621 Bytes
ca97aa9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
import { pipeline, AudioClassificationPipeline } from "../../src/transformers.js";
import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../init.js";
const PIPELINE_ID = "audio-classification";
export default () => {
describe("Audio Classification", () => {
const model_id = "hf-internal-testing/tiny-random-unispeech";
const audios = [new Float32Array(16000).fill(0), Float32Array.from({ length: 16000 }, (_, i) => i)];
/** @type {AudioClassificationPipeline} */
let pipe;
beforeAll(async () => {
pipe = await pipeline(PIPELINE_ID, model_id, DEFAULT_MODEL_OPTIONS);
}, MAX_MODEL_LOAD_TIME);
it("should be an instance of AudioClassificationPipeline", () => {
expect(pipe).toBeInstanceOf(AudioClassificationPipeline);
});
describe("batch_size=1", () => {
it(
"default (top_k=5)",
async () => {
const output = await pipe(audios[0]);
const target = [
{ score: 0.5043687224388123, label: "LABEL_0" },
{ score: 0.4956313371658325, label: "LABEL_1" },
];
expect(output).toBeCloseToNested(target, 5);
},
MAX_TEST_EXECUTION_TIME,
);
it(
"custom (top_k=1)",
async () => {
const output = await pipe(audios[0], { top_k: 1 });
const target = [{ score: 0.5043687224388123, label: "LABEL_0" }];
expect(output).toBeCloseToNested(target, 5);
},
MAX_TEST_EXECUTION_TIME,
);
});
describe("batch_size>1", () => {
it(
"default (top_k=5)",
async () => {
const output = await pipe(audios);
const target = [
[
{ score: 0.5043687224388123, label: "LABEL_0" },
{ score: 0.4956313371658325, label: "LABEL_1" },
],
[
{ score: 0.5187293887138367, label: "LABEL_0" },
{ score: 0.4812707006931305, label: "LABEL_1" },
],
];
expect(output).toBeCloseToNested(target, 5);
},
MAX_TEST_EXECUTION_TIME,
);
it(
"custom (top_k=1)",
async () => {
const output = await pipe(audios, { top_k: 1 });
const target = [[{ score: 0.5043687224388123, label: "LABEL_0" }], [{ score: 0.5187293887138367, label: "LABEL_0" }]];
expect(output).toBeCloseToNested(target, 5);
},
MAX_TEST_EXECUTION_TIME,
);
});
afterAll(async () => {
await pipe.dispose();
}, MAX_MODEL_DISPOSE_TIME);
});
};
|