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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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"use strict"; 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]); }); }); //# sourceMappingURL=util_test.js.map