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[Web] Implement linear congruential generator, make runtime seedable (a…
…pache#16722) This PR implements `LinearCongruentialGenerator` in TVMjs, following the C++ counterpart in apache#8642. The motivation is that we want to seed autoregressive generation to make results reproducible, supporting the OpenAI field `seed`. The main function is `nextInt()`, which generates a number `(0, 2^32 - 1)` non-inclusive. Subsequently, we change all `Math.random()` in `runtime.ts` to `this.rng.randomFloat()`, exposing API `Instance.setSeed()`. Unit tests are added for `LinearCongruentialGenerator` for testing seed and coverage.
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/* | ||
* Licensed to the Apache Software Foundation (ASF) under one | ||
* or more contributor license agreements. See the NOTICE file | ||
* distributed with this work for additional information | ||
* regarding copyright ownership. The ASF licenses this file | ||
* to you under the Apache License, Version 2.0 (the | ||
* "License"); you may not use this file except in compliance | ||
* with the License. You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, | ||
* software distributed under the License is distributed on an | ||
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
* KIND, either express or implied. See the License for the | ||
* specific language governing permissions and limitations | ||
* under the License. | ||
*/ | ||
/* eslint-disable no-undef */ | ||
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const tvmjs = require("../../dist"); | ||
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test("Test coverage of [0,100] inclusive", () => { | ||
const covered = Array(100); | ||
const rng = new tvmjs.LinearCongruentialGenerator(); | ||
for (let i = 0; i < 100000; i++) { | ||
covered[rng.nextInt() % 100] = true; | ||
} | ||
const notCovered = []; | ||
for (let i = 0; i < 100; i++) { | ||
if (!covered[i]) { | ||
notCovered.push(i); | ||
} | ||
} | ||
expect(notCovered).toEqual([]); | ||
}); | ||
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test("Test whether the same seed make two RNGs generate same results", () => { | ||
const rng1 = new tvmjs.LinearCongruentialGenerator(); | ||
const rng2 = new tvmjs.LinearCongruentialGenerator(); | ||
rng1.setSeed(42); | ||
rng2.setSeed(42); | ||
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for (let i = 0; i < 100; i++) { | ||
expect(rng1.randomFloat()).toBeCloseTo(rng2.randomFloat()); | ||
} | ||
}); | ||
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test("Test two RNGs with different seeds generate different results", () => { | ||
const rng1 = new tvmjs.LinearCongruentialGenerator(); | ||
const rng2 = new tvmjs.LinearCongruentialGenerator(); | ||
rng1.setSeed(41); | ||
rng2.setSeed(42); | ||
let numSame = 0; | ||
const numTest = 100; | ||
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// Generate `numTest` random numbers, make sure not all are the same. | ||
for (let i = 0; i < numTest; i++) { | ||
if (rng1.nextInt() === rng2.nextInt()) { | ||
numSame += 1; | ||
} | ||
} | ||
expect(numSame < numTest).toBe(true); | ||
}); | ||
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test('Illegal argument to `setSeed()`', () => { | ||
expect(() => { | ||
const rng1 = new tvmjs.LinearCongruentialGenerator(); | ||
rng1.setSeed(42.5); | ||
}).toThrow("Seed should be an integer."); | ||
}); |