@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
52 lines • 2.25 kB
JavaScript
import * as tf from '../index';
import { describeWithFlags } from '../jasmine_util';
import { ALL_ENVS, expectArraysClose } from '../test_util';
describeWithFlags('MomentumOptimizer', ALL_ENVS, function () {
it('basic', function () {
var learningRate = .1;
var momentum = .5;
var optimizer = tf.train.momentum(learningRate, momentum);
var x = tf.tensor1d([1, 2]).variable();
var f = function () { return x.square().sum(); };
var numTensors = tf.memory().numTensors;
var cost = optimizer.minimize(f, true);
expect(tf.memory().numTensors).toBe(numTensors + 2);
expectArraysClose(x, [.8, 1.6]);
cost.dispose();
numTensors = tf.memory().numTensors;
cost = optimizer.minimize(f, false);
expectArraysClose(x, [0.54, 1.08]);
expect(tf.memory().numTensors).toBe(numTensors);
expect(cost).toBe(null);
x.dispose();
optimizer.dispose();
expect(tf.memory().numTensors).toBe(1);
});
it('basic - with Nesterov', function () {
var learningRate = .1;
var momentum = .5;
var useNesterov = true;
var optimizer = tf.train.momentum(learningRate, momentum, useNesterov);
var x = tf.tensor1d([1, 2]).variable();
var f = function () { return x.square().sum(); };
var numTensors = tf.memory().numTensors;
var cost = optimizer.minimize(f, true);
expect(tf.memory().numTensors).toBe(numTensors + 2);
expectArraysClose(x, [.7, 1.4]);
cost.dispose();
numTensors = tf.memory().numTensors;
cost = optimizer.minimize(f, false);
expectArraysClose(x, [0.44, 0.88]);
expect(tf.memory().numTensors).toBe(numTensors);
expect(cost).toBe(null);
x.dispose();
optimizer.dispose();
expect(tf.memory().numTensors).toBe(1);
});
it('serialization round-trip', function () {
var originalOpt = tf.train.momentum(0.1, 0.2, true);
var reserialized = tf.MomentumOptimizer.fromConfig(tf.MomentumOptimizer, originalOpt.getConfig());
expect(reserialized.getConfig()).toEqual(originalOpt.getConfig());
});
});
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