@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
247 lines • 10 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("./index");
var test_util_1 = require("./test_util");
var jasmine_util_1 = require("./jasmine_util");
var util = require("./util");
describe('Util', function () {
it('Flatten arrays', function () {
expect(util.flatten([[1, 2, 3], [4, 5, 6]])).toEqual([1, 2, 3, 4, 5, 6]);
expect(util.flatten([[[1, 2], [3, 4], [5, 6], [7, 8]]])).toEqual([
1, 2, 3, 4, 5, 6, 7, 8
]);
expect(util.flatten([1, 2, 3, 4, 5, 6])).toEqual([1, 2, 3, 4, 5, 6]);
});
it('Correctly gets size from shape', function () {
expect(util.sizeFromShape([1, 2, 3, 4])).toEqual(24);
});
it('Correctly identifies scalars', function () {
expect(util.isScalarShape([])).toBe(true);
expect(util.isScalarShape([1, 2])).toBe(false);
expect(util.isScalarShape([1])).toBe(false);
});
it('Number arrays equal', function () {
expect(util.arraysEqual([1, 2, 3, 6], [1, 2, 3, 6])).toBe(true);
expect(util.arraysEqual([1, 2], [1, 2, 3])).toBe(false);
expect(util.arraysEqual([1, 2, 5], [1, 2])).toBe(false);
});
it('Is integer', function () {
expect(util.isInt(0.5)).toBe(false);
expect(util.isInt(1)).toBe(true);
});
it('Size to squarish shape (perfect square)', function () {
expect(util.sizeToSquarishShape(9)).toEqual([3, 3]);
});
it('Size to squarish shape (prime number)', function () {
expect(util.sizeToSquarishShape(11)).toEqual([1, 11]);
});
it('Size to squarish shape (almost square)', function () {
expect(util.sizeToSquarishShape(35)).toEqual([5, 7]);
});
it('Size of 1 to squarish shape', function () {
expect(util.sizeToSquarishShape(1)).toEqual([1, 1]);
});
it('infer shape single number', function () {
expect(util.inferShape(4)).toEqual([]);
});
it('infer shape 1d array', function () {
expect(util.inferShape([1, 2, 5])).toEqual([3]);
});
it('infer shape 2d array', function () {
expect(util.inferShape([[1, 2, 5], [5, 4, 1]])).toEqual([2, 3]);
});
it('infer shape 3d array', function () {
var a = [[[1, 2], [2, 3], [5, 6]], [[5, 6], [4, 5], [1, 2]]];
expect(util.inferShape(a)).toEqual([2, 3, 2]);
});
it('infer shape 4d array', function () {
var a = [
[[[1], [2]], [[2], [3]], [[5], [6]]],
[[[5], [6]], [[4], [5]], [[1], [2]]]
];
expect(util.inferShape(a)).toEqual([2, 3, 2, 1]);
});
it('infer shape of typed array', function () {
var a = new Float32Array([1, 2, 3, 4, 5]);
expect(util.inferShape(a)).toEqual([5]);
});
});
describe('util.repeatedTry', function () {
it('resolves', function (doneFn) {
var counter = 0;
var checkFn = function () {
counter++;
if (counter === 2) {
return true;
}
return false;
};
util.repeatedTry(checkFn).then(doneFn).catch(function () {
throw new Error('Rejected backoff.');
});
});
it('rejects', function (doneFn) {
var checkFn = function () { return false; };
util.repeatedTry(checkFn, function () { return 0; }, 5)
.then(function () {
throw new Error('Backoff resolved');
})
.catch(doneFn);
});
});
describe('util.getQueryParams', function () {
it('basic', function () {
expect(util.getQueryParams('?a=1&b=hi&f=animal'))
.toEqual({ 'a': '1', 'b': 'hi', 'f': 'animal' });
});
});
describe('util.inferFromImplicitShape', function () {
it('empty shape', function () {
var result = util.inferFromImplicitShape([], 0);
expect(result).toEqual([]);
});
it('[2, 3, 4] -> [2, 3, 4]', function () {
var result = util.inferFromImplicitShape([2, 3, 4], 24);
expect(result).toEqual([2, 3, 4]);
});
it('[2, -1, 4] -> [2, 3, 4], size=24', function () {
var result = util.inferFromImplicitShape([2, -1, 4], 24);
expect(result).toEqual([2, 3, 4]);
});
it('[-1, 3, 4] -> [2, 3, 4], size=24', function () {
var result = util.inferFromImplicitShape([-1, 3, 4], 24);
expect(result).toEqual([2, 3, 4]);
});
it('[2, 3, -1] -> [2, 3, 4], size=24', function () {
var result = util.inferFromImplicitShape([2, 3, -1], 24);
expect(result).toEqual([2, 3, 4]);
});
it('[2, -1, -1] throws error', function () {
expect(function () { return util.inferFromImplicitShape([2, -1, -1], 24); }).toThrowError();
});
it('[2, 3, -1] size=13 throws error', function () {
expect(function () { return util.inferFromImplicitShape([2, 3, -1], 13); }).toThrowError();
});
it('[2, 3, 4] size=25 (should be 24) throws error', function () {
expect(function () { return util.inferFromImplicitShape([2, 3, 4], 25); }).toThrowError();
});
});
describe('util.squeezeShape', function () {
it('scalar', function () {
var _a = util.squeezeShape([]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([]);
expect(keptDims).toEqual([]);
});
it('1x1 reduced to scalar', function () {
var _a = util.squeezeShape([1, 1]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([]);
expect(keptDims).toEqual([]);
});
it('1x3x1 reduced to [3]', function () {
var _a = util.squeezeShape([1, 3, 1]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([3]);
expect(keptDims).toEqual([1]);
});
it('1x1x4 reduced to [4]', function () {
var _a = util.squeezeShape([1, 1, 4]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([4]);
expect(keptDims).toEqual([2]);
});
it('2x3x4 not reduction', function () {
var _a = util.squeezeShape([2, 3, 4]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([2, 3, 4]);
expect(keptDims).toEqual([0, 1, 2]);
});
describe('with axis', function () {
it('should only reduce dimensions specified by axis', function () {
var _a = util.squeezeShape([1, 1, 1, 1, 4], [1, 2]), newShape = _a.newShape, keptDims = _a.keptDims;
expect(newShape).toEqual([1, 1, 4]);
expect(keptDims).toEqual([0, 3, 4]);
});
it('throws error when specified axis is not squeezable', function () {
expect(function () { return util.squeezeShape([1, 1, 2, 1, 4], [1, 2]); }).toThrowError();
});
});
});
describe('util.isTensorInList', function () {
it('not in list', function () {
var a = tf.scalar(1);
var list = [tf.scalar(1), tf.tensor1d([1, 2, 3])];
expect(util.isTensorInList(a, list)).toBe(false);
});
it('in list', function () {
var a = tf.scalar(1);
var list = [tf.scalar(2), tf.tensor1d([1, 2, 3]), a];
expect(util.isTensorInList(a, list)).toBe(true);
});
});
describe('util.checkForNaN', function () {
it('Float32Array has NaN', function () {
expect(function () { return util.checkForNaN(new Float32Array([1, 2, 3, NaN, 4, 255]), 'float32', ''); })
.toThrowError();
});
it('Float32Array no NaN', function () {
expect(function () { return util.checkForNaN(new Float32Array([1, 2, 3, 4, -1, 255]), 'float32', ''); })
.not.toThrowError();
});
});
describe('util.flattenNameArrayMap', function () {
it('basic', function () {
var a = tf.scalar(1);
var b = tf.scalar(3);
var c = tf.tensor1d([1, 2, 3]);
var map = { a: a, b: b, c: c };
expect(util.flattenNameArrayMap(map, Object.keys(map))).toEqual([a, b, c]);
});
});
describe('util.unflattenToNameArrayMap', function () {
it('basic', function () {
var a = tf.scalar(1);
var b = tf.scalar(3);
var c = tf.tensor1d([1, 2, 3]);
expect(util.unflattenToNameArrayMap(['a', 'b', 'c'], [
a, b, c
])).toEqual({ a: a, b: b, c: c });
});
});
describe('util.hasEncodingLoss', function () {
it('any to float32', function () {
expect(util.hasEncodingLoss('bool', 'float32')).toBe(false);
expect(util.hasEncodingLoss('int32', 'float32')).toBe(false);
expect(util.hasEncodingLoss('float32', 'float32')).toBe(false);
});
it('float32 to any', function () {
expect(util.hasEncodingLoss('float32', 'float32')).toBe(false);
expect(util.hasEncodingLoss('float32', 'int32')).toBe(true);
expect(util.hasEncodingLoss('float32', 'bool')).toBe(true);
});
it('int32 to lower', function () {
expect(util.hasEncodingLoss('int32', 'int32')).toBe(false);
expect(util.hasEncodingLoss('int32', 'bool')).toBe(true);
});
it('lower to int32', function () {
expect(util.hasEncodingLoss('bool', 'int32')).toBe(false);
});
it('bool to bool', function () {
expect(util.hasEncodingLoss('bool', 'bool')).toBe(false);
});
});
jasmine_util_1.describeWithFlags('extractTensorsFromAny', test_util_1.CPU_ENVS, function () {
it('null input returns empty tensor', function () {
var results = util.extractTensorsFromAny(null);
expect(results).toEqual([]);
});
it('tensor input returns one element tensor', function () {
var x = tf.scalar(1);
var results = util.extractTensorsFromAny(x);
expect(results).toEqual([x]);
});
it('name tensor map returns flattened tensor', function () {
var x1 = tf.scalar(1);
var x2 = tf.scalar(3);
var x3 = tf.scalar(4);
var results = util.extractTensorsFromAny({ x1: x1, x2: x2, x3: x3 });
expect(results).toEqual([x1, x2, x3]);
});
});
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