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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 tensor_1 = require("./tensor"); function assertArgumentIsTensor(x, argName, functionName) { assert(x instanceof tensor_1.Tensor, "Argument '" + argName + "' passed to '" + functionName + "' must be a Tensor, " + ("but got " + typeof x + ".")); } function assertArgumentsAreTensors(args, functionName) { var _loop_1 = function (argName) { var arg = args[argName]; if (Array.isArray(arg)) { arg.forEach(function (t, i) { assertArgumentIsTensor(t, argName + "[" + i + "]", functionName); }); } else { assertArgumentIsTensor(arg, argName, functionName); } }; for (var argName in args) { _loop_1(argName); } } exports.assertArgumentsAreTensors = assertArgumentsAreTensors; function shuffle(array) { var counter = array.length; var temp = 0; var index = 0; while (counter > 0) { index = (Math.random() * counter) | 0; counter--; temp = array[counter]; array[counter] = array[index]; array[index] = temp; } } exports.shuffle = shuffle; function clamp(min, x, max) { return Math.max(min, Math.min(x, max)); } exports.clamp = clamp; function randUniform(a, b) { return Math.random() * (b - a) + a; } exports.randUniform = randUniform; function distSquared(a, b) { var result = 0; for (var i = 0; i < a.length; i++) { var diff = Number(a[i]) - Number(b[i]); result += diff * diff; } return result; } exports.distSquared = distSquared; function assert(expr, msg) { if (!expr) { throw new Error(msg); } } exports.assert = assert; function assertShapesMatch(shapeA, shapeB, errorMessagePrefix) { if (errorMessagePrefix === void 0) { errorMessagePrefix = ''; } assert(arraysEqual(shapeA, shapeB), errorMessagePrefix + (" Shapes " + shapeA + " and " + shapeB + " must match")); } exports.assertShapesMatch = assertShapesMatch; function assertTypesMatch(a, b) { assert(a.dtype === b.dtype, " The dtypes of the first(" + a.dtype + ") and" + (" second(" + b.dtype + ") input must match")); } exports.assertTypesMatch = assertTypesMatch; function flatten(arr, ret) { if (ret === void 0) { ret = []; } if (Array.isArray(arr)) { for (var i = 0; i < arr.length; ++i) { flatten(arr[i], ret); } } else { ret.push(arr); } return ret; } exports.flatten = flatten; function inferShape(val) { if (isTypedArray(val)) { return [val.length]; } if (!Array.isArray(val)) { return []; } var shape = []; while (val instanceof Array) { shape.push(val.length); val = val[0]; } return shape; } exports.inferShape = inferShape; function sizeFromShape(shape) { if (shape.length === 0) { return 1; } var size = shape[0]; for (var i = 1; i < shape.length; i++) { size *= shape[i]; } return size; } exports.sizeFromShape = sizeFromShape; function isScalarShape(shape) { return shape.length === 0; } exports.isScalarShape = isScalarShape; function arraysEqual(n1, n2) { if (n1.length !== n2.length) { return false; } for (var i = 0; i < n1.length; i++) { if (n1[i] !== n2[i]) { return false; } } return true; } exports.arraysEqual = arraysEqual; function isInt(a) { return a % 1 === 0; } exports.isInt = isInt; function tanh(x) { if (Math.tanh != null) { return Math.tanh(x); } if (x === Infinity) { return 1; } else if (x === -Infinity) { return -1; } else { var e2x = Math.exp(2 * x); return (e2x - 1) / (e2x + 1); } } exports.tanh = tanh; function sizeToSquarishShape(size) { for (var a = Math.floor(Math.sqrt(size)); a > 1; --a) { if (size % a === 0) { return [a, size / a]; } } return [1, size]; } exports.sizeToSquarishShape = sizeToSquarishShape; function createShuffledIndices(n) { var shuffledIndices = new Uint32Array(n); for (var i = 0; i < n; ++i) { shuffledIndices[i] = i; } shuffle(shuffledIndices); return shuffledIndices; } exports.createShuffledIndices = createShuffledIndices; function rightPad(a, size) { if (size <= a.length) { return a; } return a + ' '.repeat(size - a.length); } exports.rightPad = rightPad; function repeatedTry(checkFn, delayFn, maxCounter) { if (delayFn === void 0) { delayFn = function (counter) { return 0; }; } return new Promise(function (resolve, reject) { var tryCount = 0; var tryFn = function () { if (checkFn()) { resolve(); return; } tryCount++; var nextBackoff = delayFn(tryCount); if (maxCounter != null && tryCount >= maxCounter) { reject(); return; } setTimeout(tryFn, nextBackoff); }; setTimeout(tryFn, 0); }); } exports.repeatedTry = repeatedTry; function getQueryParams(queryString) { var params = {}; queryString.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, function (s) { var t = []; for (var _i = 1; _i < arguments.length; _i++) { t[_i - 1] = arguments[_i]; } decodeParam(params, t[0], t[1]); return t.join('='); }); return params; } exports.getQueryParams = getQueryParams; function decodeParam(params, name, value) { params[decodeURIComponent(name)] = decodeURIComponent(value || ''); } function inferFromImplicitShape(shape, size) { var shapeProd = 1; var implicitIdx = -1; for (var i = 0; i < shape.length; ++i) { if (shape[i] > 0) { shapeProd *= shape[i]; } else if (shape[i] === -1) { if (implicitIdx !== -1) { throw Error("Shapes can only have 1 implicit size. " + ("Found - 1 at dim " + implicitIdx + " and dim " + i)); } implicitIdx = i; } else if (shape[i] <= 0) { throw Error("Shapes can not be <= 0. Found " + shape[i] + " at dim " + i); } } if (implicitIdx === -1) { if (size > 0 && size !== shapeProd) { throw Error("Size(" + size + ") must match the product of shape " + shape); } return shape; } if (size % shapeProd !== 0) { throw Error("The implicit shape can't be a fractional number. " + ("Got " + size + " / " + shapeProd)); } var newShape = shape.slice(); newShape[implicitIdx] = size / shapeProd; return newShape; } exports.inferFromImplicitShape = inferFromImplicitShape; function squeezeShape(shape, axis) { var newShape = []; var keptDims = []; var j = 0; for (var i = 0; i < shape.length; ++i) { if (axis != null) { if (axis[j] === i && shape[i] > 1) { throw new Error("Can't squeeze axis " + i + " since its dim '" + shape[i] + "' is not 1"); } if ((axis[j] == null || axis[j] > i) && shape[i] === 1) { newShape.push(shape[i]); keptDims.push(i); } if (axis[j] <= i) { j++; } } if (shape[i] > 1) { newShape.push(shape[i]); keptDims.push(i); } } return { newShape: newShape, keptDims: keptDims }; } exports.squeezeShape = squeezeShape; function getTypedArrayFromDType(dtype, size) { var values = null; if (dtype == null || dtype === 'float32') { values = new Float32Array(size); } else if (dtype === 'int32') { values = new Int32Array(size); } else if (dtype === 'bool') { values = new Uint8Array(size); } else { throw new Error("Unknown data type " + dtype); } return values; } exports.getTypedArrayFromDType = getTypedArrayFromDType; function isTensorInList(tensor, tensorList) { for (var i = 0; i < tensorList.length; i++) { if (tensorList[i].id === tensor.id) { return true; } } return false; } exports.isTensorInList = isTensorInList; function checkForNaN(vals, dtype, name) { if (dtype !== 'float32') { return; } for (var i = 0; i < vals.length; i++) { if (isNaN(vals[i])) { throw Error("The result of the '" + name + "' has NaNs."); } } } exports.checkForNaN = checkForNaN; function flattenNameArrayMap(nameArrayMap, keys) { var xs = []; if (nameArrayMap instanceof tensor_1.Tensor) { xs.push(nameArrayMap); } else { var xMap = nameArrayMap; for (var i = 0; i < keys.length; i++) { xs.push(xMap[keys[i]]); } } return xs; } exports.flattenNameArrayMap = flattenNameArrayMap; function unflattenToNameArrayMap(keys, flatArrays) { if (keys.length !== flatArrays.length) { throw new Error("Cannot unflatten Tensor[], keys and arrays are not of same length."); } var result = {}; for (var i = 0; i < keys.length; i++) { result[keys[i]] = flatArrays[i]; } return result; } exports.unflattenToNameArrayMap = unflattenToNameArrayMap; function hasEncodingLoss(oldType, newType) { if (newType === 'float32') { return false; } if (newType === 'int32' && oldType !== 'float32') { return false; } if (newType === 'bool' && oldType === 'bool') { return false; } return true; } exports.hasEncodingLoss = hasEncodingLoss; function copyTypedArray(array, dtype) { if (dtype == null || dtype === 'float32') { return new Float32Array(array); } else if (dtype === 'int32') { return new Int32Array(array); } else if (dtype === 'bool') { var bool = new Uint8Array(array.length); for (var i = 0; i < bool.length; ++i) { if (Math.round(array[i]) !== 0) { bool[i] = 1; } } return bool; } else { throw new Error("Unknown data type " + dtype); } } exports.copyTypedArray = copyTypedArray; function isTypedArray(a) { return a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array; } exports.isTypedArray = isTypedArray; function bytesPerElement(dtype) { if (dtype === 'float32' || dtype === 'int32') { return 4; } else if (dtype === 'bool') { return 1; } else { throw new Error("Unknown dtype " + dtype); } } exports.bytesPerElement = bytesPerElement; function isFunction(f) { return !!(f && f.constructor && f.call && f.apply); } exports.isFunction = isFunction; function extractTensorsFromContainer(result) { return extractTensorsFromAny(result); } exports.extractTensorsFromContainer = extractTensorsFromContainer; function extractTensorsFromAny(result) { if (result == null) { return []; } if (result instanceof tensor_1.Tensor) { return [result]; } var list = []; var resultObj = result; if (!isIterable(resultObj)) { return []; } for (var k in resultObj) { var sublist = flatten(resultObj[k]).filter(function (x) { return x instanceof tensor_1.Tensor; }); list.push.apply(list, sublist); } return list; } exports.extractTensorsFromAny = extractTensorsFromAny; function isIterable(obj) { return Array.isArray(obj) || typeof obj === 'object'; } //# sourceMappingURL=util.js.map