scalar-autograd/dist/Optimizers.edge-cases.spec.js

Scalar-based reverse-mode automatic differentiation in TypeScript.

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const Value_1 = require("./Value");
const Optimizers_1 = require("./Optimizers");
describe('Optimizer edge cases', () => {
    it('handles empty parameter list', () => {
        const opt = new Optimizers_1.SGD([], { learningRate: 0.1 });
        expect(() => opt.step()).not.toThrow();
    });
    it('filters out non-trainable parameters', () => {
        const x = new Value_1.Value(1, 'x', true);
        const y = new Value_1.Value(2, 'y', false);
        const opt = new Optimizers_1.SGD([x, y], { learningRate: 0.1 });
        x.grad = 1;
        y.grad = 1;
        opt.step();
        expect(x.data).toBe(0.9);
        expect(y.data).toBe(2); // unchanged
    });
    it('Adam handles zero gradients correctly', () => {
        const x = new Value_1.Value(1, 'x', true);
        const opt = new Optimizers_1.Adam([x], { learningRate: 0.1 });
        x.grad = 0;
        for (let i = 0; i < 10; i++) {
            opt.step();
        }
        expect(x.data).toBe(1); // unchanged
    });
});