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- const cntk = {};
- cntk.ModelFactory = class {
- async match(context) {
- const stream = context.stream;
- // CNTK v1
- const signature = [0x42, 0x00, 0x43, 0x00, 0x4e, 0x00, 0x00, 0x00];
- if (stream && signature.length <= stream.length && stream.peek(signature.length).every((value, index) => value === signature[index])) {
- return context.set('cntk.v1');
- }
- // CNTK v2
- const tags = await context.tags('pb');
- if (tags.get(1) === 0 && tags.get(2) === 2) {
- return context.set('cntk.v2');
- }
- return null;
- }
- async open(context) {
- const metadata = await context.metadata('cntk-metadata.json');
- switch (context.type) {
- case 'cntk.v1': {
- let obj = null;
- try {
- const reader = await context.read('binary');
- obj = new cntk.ComputationNetwork(reader);
- } catch (error) {
- const message = error && error.message ? error.message : error.toString();
- throw new cntk.Error(`File format is not CNTK v1 (${message.replace(/\.$/, '')}).`);
- }
- return new cntk.Model(metadata, 1, obj);
- }
- case 'cntk.v2': {
- cntk.proto = await context.require('./cntk-proto');
- cntk.proto = cntk.proto.CNTK.proto;
- cntk.proto.PoolingType = { 0: 'Max', 1: 'Average' };
- let obj = null;
- try {
- const reader = await context.read('protobuf.binary');
- const dictionary = cntk.proto.Dictionary.decode(reader);
- obj = cntk.ModelFactory._convertDictionary(dictionary);
- } catch (error) {
- const message = error && error.message ? error.message : error.toString();
- throw new cntk.Error(`File format is not cntk.Dictionary (${message.replace(/\.$/, '')}).`);
- }
- return new cntk.Model(metadata, 2, obj);
- }
- default: {
- throw new cntk.Error(`Unsupported CNTK format '${context.type}'.`);
- }
- }
- }
- static _convertDictionary(dictionary) {
- const target = {};
- for (const key of Object.keys(dictionary.data).filter((key) => key !== 'version')) {
- target[key] = cntk.ModelFactory._convertDictionaryValue(dictionary.data[key]);
- }
- return target;
- }
- static _convertDictionaryValue(dictionaryValue) {
- switch (dictionaryValue.value_type) {
- case cntk.proto.DictionaryValue.Type.Bool:
- return dictionaryValue.bool_value;
- case cntk.proto.DictionaryValue.Type.Int:
- return dictionaryValue.int_value;
- case cntk.proto.DictionaryValue.Type.SizeT:
- return dictionaryValue.size_t_value;
- case cntk.proto.DictionaryValue.Type.Float:
- return dictionaryValue.float_value;
- case cntk.proto.DictionaryValue.Type.Double:
- return dictionaryValue.double_value;
- case cntk.proto.DictionaryValue.Type.String:
- return dictionaryValue.string_value;
- case cntk.proto.DictionaryValue.Type.Vector:
- return cntk.ModelFactory._convertVectorValue(dictionaryValue.vector_value);
- case cntk.proto.DictionaryValue.Type.NDShape:
- return dictionaryValue.nd_shape_value;
- case cntk.proto.DictionaryValue.Type.Axis:
- return dictionaryValue.axis_value;
- case cntk.proto.DictionaryValue.Type.Dictionary:
- return cntk.ModelFactory._convertDictionary(dictionaryValue.dictionary_value);
- case cntk.proto.DictionaryValue.Type.NDArrayView:
- return dictionaryValue.nd_array_view_value;
- default:
- throw new cntk.Error(`Unsupported dictionary value type '${dictionaryValue.value_type}'.`);
- }
- }
- static _convertVectorValue(vectorValue) {
- return vectorValue.value.map((item) => {
- return cntk.ModelFactory._convertDictionaryValue(item);
- });
- }
- };
- cntk.Model = class {
- constructor(metadata, version, obj) {
- switch (version) {
- case 1:
- this.format = `CNTK v1${obj.version ? (`.${obj.version}`) : ''}`;
- break;
- case 2:
- this.format = 'CNTK v2';
- break;
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- this.modules = [new cntk.Graph(metadata, version, obj)];
- }
- };
- cntk.Graph = class {
- constructor(metadata, version, obj) {
- metadata = new cntk.GraphMetadata(metadata);
- this.inputs = [];
- this.outputs = [];
- this.nodes = [];
- const values = new Map();
- values.map = (name, version, obj) => {
- if (obj && values.has(name)) {
- throw new cntk.Error(`Duplicate value '${name}'.`);
- }
- if (!values.has(name)) {
- switch (version) {
- case 1:
- values.set(name, new cntk.Value(version, obj ? obj : { name }));
- break;
- case 2:
- values.set(name, new cntk.Value(version, obj ? obj : { uid: name }));
- break;
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- return values.get(name);
- };
- switch (version) {
- case 1: {
- for (const name of Object.keys(obj.nodes)) {
- const node = obj.nodes[name];
- switch (node.__type__) {
- case 'InputValue': {
- const argument = new cntk.Argument(node.name, [values.map(node.name, version, node)]);
- this.inputs.push(argument);
- break;
- }
- case 'LearnableParameter': {
- values.map(node.name, version, node);
- break;
- }
- default:
- break;
- }
- }
- for (const name of Object.keys(obj.nodes)) {
- const node = obj.nodes[name];
- if (node.__type__ !== 'InputValue' && node.__type__ !== 'LearnableParameter') {
- this.nodes.push(new cntk.Node(metadata, version, node, values));
- }
- }
- if (obj.output) {
- for (const output of obj.output) {
- const argument = new cntk.Argument(output, [values.map(output, version)]);
- this.outputs.push(argument);
- }
- }
- break;
- }
- case 2: {
- const map = new Map(obj.primitive_functions.map((node) => [node.uid, node]));
- for (const input of obj.inputs) {
- const value = values.map(input.uid, version, input);
- // VariableKind { 0: 'input', 1: 'output', 2: 'parameter', 3: 'constant', 4: 'placeholder' }
- if (input.kind === 0n) {
- const inputName = input.name || input.uid;
- this.inputs.push(new cntk.Argument(inputName, [value]));
- }
- }
- for (const block of obj.primitive_functions) {
- if (block.op === 57n && block.block_function_composite) {
- const list = [block.block_function_composite.root];
- const output = map.get(block.block_function_composite.root);
- const keys = block.block_function_composite_arguments_map_keys;
- const args = block.block_function_composite_arguments_map_values;
- block.inputs = args;
- if (!Array.isArray(keys) || !Array.isArray(args) || keys.length !== args.length) {
- throw new cntk.Error('Invalid block function composite arguments.');
- }
- const inputs = keys.map((key) => new cntk.Argument(key, [values.map(key, version)]));
- const outputs = [new cntk.Argument('output', [values.map(`${output.uid}_Output_0`, version)])];
- const nodes = [];
- while (list.length > 0) {
- const name = list.shift();
- if (map.has(name)) {
- const node = map.get(name);
- nodes.push(new cntk.Node(metadata, version, node, values));
- map.delete(name);
- for (let i = 0; i < node.inputs.length; i++) {
- const parts = node.inputs[i].split('_');
- if (parts.length >= 3) {
- parts.pop();
- if (parts.pop() === 'Output') {
- list.push(parts.join('_'));
- }
- }
- }
- }
- }
- const func = new cntk.Function(block.block_function_op_name, nodes, inputs, outputs);
- metadata.add(block.uid, func);
- }
- }
- for (const node of map.values()) {
- this.nodes.push(new cntk.Node(metadata, version, node, values));
- }
- break;
- }
- default: {
- throw new cntk.Error(`Unsupported graph version '${version}'.`);
- }
- }
- }
- };
- cntk.Argument = class {
- constructor(name, value, type = null, visible = true) {
- this.name = name;
- this.value = value;
- this.type = type;
- this.visible = visible;
- }
- };
- cntk.Value = class {
- constructor(version, obj) {
- switch (version) {
- case 1:
- switch (obj.__type__) {
- case 'InputValue':
- this.name = obj.name;
- this.type = new cntk.TensorType(version, obj.precision, obj.sampleLayout);
- this.initializer = null;
- break;
- case 'LearnableParameter':
- this.name = obj.name;
- this.initializer = new cntk.Tensor(version, obj);
- this.type = this.initializer.type;
- break;
- default:
- this.name = obj.name;
- this.type = null;
- this.initializer = null;
- break;
- }
- break;
- case 2:
- if (obj.value) {
- this.name = obj.name || obj.uid;
- this.initializer = new cntk.Tensor(version, obj);
- this.type = this.initializer.type;
- } else {
- this.name = obj.uid;
- if (obj.data_type && obj.shape) {
- this.type = new cntk.TensorType(version, obj.data_type, obj.shape);
- }
- this.initializer = null;
- }
- break;
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- };
- cntk.Node = class {
- constructor(metadata, version, obj, values) {
- this.attributes = [];
- this.inputs = [];
- this.outputs = [];
- let inputs = [];
- let outputs = [];
- const attributes = [];
- switch (version) {
- case 1: {
- const type = obj.__type__;
- this.type = { name: type, ...metadata.type(type) };
- delete this.type.identifier;
- this.name = obj.name;
- for (const [name, value] of Object.entries(obj)) {
- if (name !== '__type__' && name !== 'name' && name !== 'inputs' && name !== 'precision') {
- const schema = metadata.attribute(type, name);
- attributes.push([schema, name, value]);
- }
- }
- inputs = obj.inputs.map((input) => values.map(input, version));
- outputs = [values.map(this.name, version)];
- break;
- }
- case 2: {
- this.name = obj.name || obj.uid || null;
- const output = obj.uid;
- if (obj.op === 57n) {
- this.type = { name: obj.uid, ...metadata.type(obj.uid) };
- delete this.type.identifier;
- } else if (Object.prototype.hasOwnProperty.call(obj, 'op')) {
- // cntk/Source/CNTKv2LibraryDll/API/Internals/PrimitiveOpType.h
- const op = obj.op.toNumber();
- this.type = { ...metadata.type(op) };
- delete this.type.identifier;
- } else {
- const type = obj.type;
- this.type = { name: type, ...metadata.type(type) };
- delete this.type.identifier;
- if (obj.user_defined_state) {
- for (const [name, value] of Object.entries(obj.user_defined_state)) {
- const schema = metadata.attribute(type, name);
- attributes.push([schema, name, value]);
- }
- }
- }
- if (obj.attributes) {
- for (const [name, value] of Object.entries(obj.attributes)) {
- const schema = metadata.attribute(this.type, name);
- attributes.push([schema, name, value]);
- }
- }
- inputs = obj.inputs.map((input) => values.map(input, version));
- outputs.push(values.map(`${output}_Output_0`, version));
- break;
- }
- default: {
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- let inputIndex = 0;
- if (this.type && this.type.inputs) {
- for (const schema of this.type.inputs) {
- if (inputIndex < inputs.length || schema.option !== 'optional') {
- const count = schema.type === 'Tensor[]' ? (inputs.length - inputIndex) : 1;
- const values = [];
- for (const value of inputs.slice(inputIndex, inputIndex + count)) {
- if (value.name !== '' || schema.option !== 'optional') {
- values.push(value);
- }
- }
- const argument = new cntk.Argument(schema.name, values);
- this.inputs.push(argument);
- inputIndex += count;
- }
- }
- }
- this.inputs.push(...inputs.slice(inputIndex).map((argument, index) => {
- return new cntk.Argument((inputIndex + index).toString(), [argument]);
- }));
- let outputIndex = 0;
- if (this.type && this.type.outputs) {
- for (const schema of this.type.outputs) {
- if (outputIndex < outputs.length || !schema.optional) {
- const count = schema.type === 'Tensor[]' ? (outputs.length - outputIndex) : 1;
- const values = outputs.slice(outputIndex, outputIndex + count);
- const argument = new cntk.Argument(schema.name, values);
- this.outputs.push(argument);
- outputIndex += count;
- }
- }
- }
- this.outputs.push(...outputs.slice(outputIndex).map((argument) => {
- return new cntk.Argument(outputIndex.toString(), [argument]);
- }));
- this.attributes = attributes.map(([metadata, name, value]) => {
- let type = null;
- let visible = true;
- if (value && value.__type__ === 'shape') {
- value = new cntk.TensorShape(1, value);
- type = 'shape';
- }
- if (cntk.proto && value instanceof cntk.proto.NDShape) {
- value = new cntk.TensorShape(2, value);
- type = 'shape';
- }
- if (cntk.proto && value instanceof cntk.proto.Axis) {
- const axis = { __type__: 'Axis' };
- for (const key of Object.keys(value).filter((key) => key !== 'name')) {
- axis[key] = value[key];
- }
- value = axis;
- }
- if (metadata) {
- if (metadata.type) {
- type = metadata.type;
- const table = cntk[type] || cntk.proto[type];
- if (table && table[value]) {
- value = table[value];
- }
- }
- if (metadata.visible === false) {
- visible = false;
- } else if (metadata.default !== undefined) {
- let defaultValue = metadata.default;
- if (typeof value === 'function') {
- value = value();
- }
- if (type === 'shape') {
- value = value.dimensions;
- }
- if (value === defaultValue) {
- visible = false;
- } else if (Array.isArray(value) && Array.isArray(defaultValue)) {
- defaultValue = defaultValue.slice(0, defaultValue.length);
- if (defaultValue.length > 1 && defaultValue[defaultValue.length - 1] === null) {
- defaultValue.pop();
- while (defaultValue.length < value.length) {
- defaultValue.push(defaultValue[defaultValue.length - 1]);
- }
- }
- if (value.every((item, index) => item === defaultValue[index])) {
- visible = false;
- }
- }
- }
- }
- return new cntk.Argument(name, value, type, visible);
- });
- }
- };
- cntk.Tensor = class {
- constructor(version, tensor) {
- this.encoding = '|';
- this.values = null;
- switch (version) {
- case 1: {
- if (tensor.__type__ === 'LearnableParameter') {
- this.name = tensor.name || null;
- this.type = new cntk.TensorType(version, tensor.precision, tensor.sampleLayout);
- }
- break;
- }
- case 2: {
- this.name = tensor.name || tensor.uid || null;
- this.type = new cntk.TensorType(version, tensor.data_type, tensor.shape);
- const value = tensor.value;
- if (this.type.dataType === 'float32' && value && value.float_values && value.float_values.value && value.float_values.value.length > 0) {
- this.values = value.float_values.value;
- }
- break;
- }
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- };
- cntk.TensorType = class {
- constructor(version, dataType, shape) {
- this.dataType = '?';
- switch (version) {
- case 1:
- switch (dataType) {
- case 'float': this.dataType = 'float32'; break;
- case 'double': this.dataType = 'float64'; break;
- case 'half': this.dataType = 'float16'; break;
- case '': this.dataType = 'float32'; break;
- default: throw new cntk.Error(`Unsupported tensor data type '${dataType}'.`);
- }
- this.shape = new cntk.TensorShape(version, shape);
- break;
- case 2:
- switch (dataType) {
- case 1n: this.dataType = 'float32'; break;
- default: throw new cntk.Error(`Unsupported tensor data type '${dataType}'.`);
- }
- this.shape = new cntk.TensorShape(version, shape);
- break;
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- toString() {
- return this.dataType + this.shape.toString();
- }
- };
- cntk.TensorShape = class {
- constructor(version, shape) {
- switch (version) {
- case 1:
- this.dimensions = shape.dims;
- break;
- case 2:
- this.dimensions = shape.shape_dim.map((dimension) => dimension.toNumber());
- break;
- default:
- throw new cntk.Error(`Unsupported CNTK version '${version}'.`);
- }
- }
- toString() {
- return (this.dimensions && this.dimensions.length) ? (`[${this.dimensions.join(',')}]`) : '';
- }
- };
- cntk.Function = class {
- constructor(name, nodes, inputs, outputs) {
- this.type = 'function';
- this.name = name;
- this.inputs = inputs;
- this.outputs = outputs;
- this.nodes = nodes;
- switch (this.name) {
- case 'PReLU':
- case 'Softmax':
- this.category = 'Activation';
- break;
- case 'Dropout':
- this.category = 'Dropout';
- break;
- case 'Convolution':
- case 'ConvolutionTranspose':
- case 'Dense':
- case 'linear':
- case 'LSTM':
- this.category = 'Layer';
- break;
- case 'BatchNormalization':
- case 'lrn':
- this.category = 'Normalization';
- break;
- case 'AveragePooling':
- case 'MaxPooling':
- this.category = 'Pool';
- break;
- default:
- this.category = null;
- break;
- }
- }
- };
- cntk.GraphMetadata = class {
- constructor(metadata) {
- this._metadata = metadata;
- this._functions = new Map();
- this._attributes = new Map();
- }
- add(name, func) {
- if (this._functions.has(name)) {
- throw new cntk.Error(`Duplicate function identifier '${func.name}'.`);
- }
- this._functions.set(name, func);
- }
- name(code) {
- // cntk/Source/CNTKv2LibraryDll/API/Internals/PrimitiveOpType.h
- return this._metadata.name(code);
- }
- type(name) {
- if (this._functions.has(name)) {
- return this._functions.get(name);
- }
- return this._metadata.type(name);
- }
- attribute(type, name) {
- const key = `${type}:${name}`;
- if (!this._attributes.has(key)) {
- const metadata = this.type(type);
- if (metadata && metadata.attributes && metadata.attributes.length > 0) {
- for (const attribute of metadata.attributes) {
- this._attributes.set(`${type}:${attribute.name}`, attribute);
- }
- }
- if (!this._attributes.has(key)) {
- this._attributes.set(key, null);
- }
- }
- return this._attributes.get(key);
- }
- };
- cntk.ComputationNetwork = class {
- constructor(reader) {
- reader = new cntk.BinaryReader(reader);
- const shape = (dims) => {
- return { __type__: 'shape', dims };
- };
- reader.assert('BCN');
- reader.assert('BVersion');
- this.version = reader.uint64().toNumber();
- reader.assert('EVersion');
- const numNodes = reader.uint64().toNumber();
- reader.assert('BNodeList');
- const op = {};
- op.Minus = function() {};
- op.Plus = function() {};
- op.GreaterEqual = function() {};
- op.Equal = function() {};
- op.NotEqual = function() {};
- op.GreaterEqual = function() {};
- op.Exp = function() {};
- op.Log = function() {};
- op.Reciprocal = function() {};
- op.ElementTimes = function() {};
- op.ClassificationError = function() {};
- op.RectifiedLinear = function() {};
- op.InputValue = function(reader, version) {
- this.rows = reader.uint64().toNumber();
- this.cols = reader.uint64().toNumber();
- this.sampleLayout = reader.shape(true);
- this.dynamicAxisNodeName = '';
- if (version >= 8) {
- const nrAxes = reader.uint32();
- if (nrAxes === 1) {
- this.dynamicAxisNodeName = reader.string();
- }
- }
- this.learningRateMultiplier = 0;
- if (version >= 10) {
- this.learningRateMultiplier = reader.float32();
- }
- };
- op.LearnableParameter = function(reader, version) {
- if (version >= 3) {
- this.learningRateMultiplier = reader.float32();
- this.sampleLayout = reader.shape(false);
- } else {
- throw new cntk.Error('LeanableParameter reader implemented.');
- }
- this.value = reader.matrix();
- };
- op.CrossEntropyWithSoftmax = function(reader) {
- this.evalMode = reader.uint32();
- if (this.evalMode > 2) {
- this.evalMode = 0;
- reader.skip(-4);
- }
- };
- op.Times = function(reader, version) {
- this.outputRank = (version >= 3) ? reader.uint64().toNumber() : 1;
- this.inferInputRankToMap = (version >= 12) ? reader.int32() : -1;
- };
- op.Dropout = function(reader, version) {
- if (version >= 16) {
- this.rngSeed = (version === 16) ? reader.uint32() : reader.uint64().toNumber();
- this.rngOffset = reader.uint64().toNumber();
- }
- };
- op.ConvolutionBase = function(reader, version) {
- if (version >= 5) {
- this.kernelShape = reader.shape(false);
- this.mapCount = reader.shape(false);
- this.strides = reader.shape(false);
- this.sharing = reader.booleans();
- this.autoPadding = reader.booleans();
- this.lowerPad = reader.shape(false);
- this.upperPad = reader.shape(false);
- this.poolKind = reader.int32();
- this.imageLayoutKind = reader.int32();
- this.maxTempMemSizeInSamples = reader.uint64().toNumber();
- }
- if (version >= 9) {
- this.transpose = reader.boolean();
- }
- if (version >= 20) {
- this.outputShape = reader.shape(false);
- }
- if (version >= 21) {
- this.ceilOutDim = reader.boolean();
- }
- if (version >= 23) {
- this.includePad = reader.boolean();
- }
- };
- op.Convolution = function(reader, version) {
- op.ConvolutionBase.apply(this, [reader, version]);
- if (version < 5) {
- this.kernelShape = shape([reader.uint64().toNumber(), reader.uint64().toNumber(), 1]);
- this.strides = shape([reader.uint64().toNumber(), reader.uint64().toNumber(), 1]);
- this.mapCount = shape([reader.uint32()]);
- this.imageLayoutKind = reader.int32();
- this.autoPadding = [reader.boolean()];
- this.maxTempMemSizeInSamples = reader.uint64().toNumber();
- this.poolKind = 'None';
- this.convolution2D = true;
- this.sharing = [true];
- this.lowerPad = shape([0]);
- this.upperPad = shape([0]);
- } else {
- this.convolution2D = reader.boolean();
- if (version >= 18) {
- this.dilation = reader.shape();
- } else {
- this.dilation = shape([1]);
- }
- }
- };
- op.Pooling = function(reader, version) {
- op.ConvolutionBase.apply(this, [reader, version]);
- };
- op.PoolingBase = function(reader) {
- this.imageLayoutKind = reader.int32();
- this.windowWidth = reader.uint32();
- this.windowHeight = reader.uint64().toNumber();
- this.horizontalSubsample = reader.uint64().toNumber();
- this.verticalSubsample = reader.uint64().toNumber();
- };
- op.MaxPooling = function(reader, version) {
- op.PoolingBase.apply(this, [reader, version]);
- };
- op.ROIPooling = function(reader, version) {
- this.roiOutputShape = reader.shape(false);
- this.poolKind = (version < 26) ? 'Max' : reader.int32();
- this.spatialScale = (version < 26) ? 0.0625 : reader.float64();
- };
- op.Reshape = function(reader) {
- this.beginDimParameter = reader.uint32();
- this.endDimParameter = reader.uint32();
- this.replacementSampleLayout = reader.shape(false);
- };
- op.ReduceElements = function(reader, version) {
- let num_axes = 1;
- if (version >= 27) {
- num_axes = reader.uint32();
- }
- this.axes = [];
- for (let i = 0; i < num_axes; i++) {
- this.axes.push(reader.uint32());
- }
- this.operation = reader.string();
- if (version >= 24) {
- this.keepDimensions = reader.boolean();
- }
- };
- op.BatchNormalization = function(reader, version) {
- let mbCount = 0;
- if (version >= 6) {
- this.spatial = reader.boolean();
- this.normalizationTimeConstant = reader.float64();
- this.blendTimeConstant = reader.float64();
- this.imageLayoutKind = reader.int32();
- if (version >= 13) {
- if (version === 19) {
- this.runCountUntied = reader.boolean() ? 0 : 'SIZE_MAX';
- } else {
- this.runCountUntied = reader.uint64().toNumber();
- }
- } else {
- mbCount = reader.uint64().toNumber();
- }
- this.epsilon = reader.float64();
- this.useCntkEngine = reader.boolean();
- } else {
- const verWritten = reader.int32();
- const verReadable = reader.int32();
- if (verReadable > verWritten || verWritten < 0x00010001 || verReadable > 0x00010004) {
- throw new cntk.Error('BatchNormalization version not supported.');
- }
- this.eval = reader.boolean();
- this.spatial = reader.boolean();
- if (verWritten >= 0x00010004) {
- this.normalizationTimeConstant = reader.float64();
- } else {
- reader.float64(); // expAvgFactor
- }
- if (verWritten >= 0x00010002) {
- this.imageLayoutKind = reader.int32();
- mbCount = reader.uint64().toNumber();
- }
- if (verWritten >= 0x00010003) {
- this.epsilon = reader.float64();
- this.useCntkEngine = reader.boolean();
- }
- }
- if (version < 13) {
- this.runCountUntied = 16 * mbCount;
- this.convertRunningVariancePending = true;
- }
- };
- op.Tanh = function() {};
- op.Sigmoid = function() {};
- op.Logistic = function() {};
- op.SquareError = function() {};
- op.ErrorPrediction = function() {};
- op.RowStack = function(reader, version) {
- this.spliceDim = (version >= 3) ? reader.int32() : 1;
- };
- op.Slice = function(reader, version) {
- let num = 1;
- if (version >= 22) {
- num = reader.int32();
- }
- this.index = [];
- this.axis = [];
- this.strideMultiplier = [];
- for (let i = 0; i < num; i++) {
- this.index.push([[reader.uint64().toNumber(), reader.uint64().toNumber()]]);
- if (version >= 3) {
- this.axis.push(reader.int32());
- }
- if (version >= 27) {
- this.strideMultiplier.push(reader.int32());
- }
- }
- };
- op.PastValue = function(reader, version) {
- this.timeStep = reader.int32();
- if (version > 3) {
- this.sampleLayout = reader.shape(false);
- } else {
- const rows = reader.uint64().toNumber();
- reader.uint64();
- this.sampleLayout = shape([rows], true);
- }
- if (version >= 2) {
- this.initialStateValue = reader.int32();
- }
- };
- op.FutureValue = function(reader, version) {
- this.timeStep = reader.int32();
- if (version > 3) {
- this.sampleLayout = reader.shape(false);
- } else {
- const rows = reader.uint64().toNumber();
- reader.uint64();
- this.sampleLayout = shape([rows], true);
- }
- if (version >= 2) {
- this.initialStateValue = reader.int32();
- }
- };
- op.TransposeDimensions = function(reader, version) {
- if (version >= 3) {
- this.axis1 = reader.int32();
- this.axis2 = reader.int32();
- if (version >= 25 && this.axis1 === 0 && this.axis2 === 0) {
- const size = reader.uint64().toNumber();
- this.perm = [];
- for (let i = 0; i < size; i++) {
- this.perm.push(reader.uint64().toNumber());
- }
- }
- } else {
- this.axis1 = 1;
- this.axis2 = 2;
- }
- };
- op.AveragePooling = function(reader, version) {
- op.PoolingBase.apply(this, [reader, version]);
- };
- op.InvStdDev = function(reader) {
- this.hasComputed = reader.boolean();
- this.value = reader.matrix();
- };
- op.Mean = function(reader) {
- this.hasComputed = reader.boolean();
- this.value = reader.matrix();
- };
- op.PerDimMeanVarNormalization = function() {};
- op.Softmax = function() {};
- op.DynamicAxis = function() {};
- const nodes = [];
- this.nodes = {};
- for (let i = 0; i < numNodes; i++) {
- const precision = this.version >= 7 ? reader.string() : '';
- if (precision !== 'float' && precision !== 'double' && precision !== 'half' && precision !== '') {
- throw new cntk.Error(`Invalid precision format '${precision}'.`);
- }
- const obj = { __type__: reader.string() };
- obj.name = reader.string();
- obj.precision = precision;
- const constructor = op[obj.__type__];
- if (!constructor) {
- throw new cntk.Error(`Unsupported node type '${obj.__type__}'.`);
- }
- constructor.apply(obj, [reader, this.version]);
- nodes.push(obj);
- this.nodes[obj.name] = obj;
- }
- reader.assert('ENodeList');
- reader.assert('BRelation');
- for (let j = 0; j < numNodes; j++) {
- const nodeName = reader.string();
- const node = this.nodes[nodeName];
- const numChildren = reader.uint64().toNumber();
- const children = [];
- for (let k = 0; k < numChildren; k++) {
- children.push(reader.string());
- }
- if (this.version < 19 && node.__type__ === 'BatchNormalization') {
- const runSampleCount = {
- __type__: 'LearnableParameter',
- name: `${nodeName}.run_sample_count`,
- precision: node.precision,
- sampleLayout: shape([1]),
- learningRateMultiplier: 0
- };
- nodes.push(runSampleCount);
- this.nodes[runSampleCount.name] = runSampleCount;
- children.push(runSampleCount.name);
- }
- if (node.__type__ === 'Convolution' && children.length > 1) {
- children.splice(0, 0, children.pop());
- }
- node.inputs = children;
- }
- reader.assert('ERelation');
- reader.assert('BRootNodes');
- if (reader.match('BFeatureNodes')) {
- this.feature = reader.strings();
- reader.assert('EFeatureNodes');
- }
- if (reader.match('BLabelNodes')) {
- this.label = reader.strings();
- reader.assert('ELabelNodes');
- }
- if (reader.match('BCriterionNodes')) {
- this.criterion = reader.strings();
- reader.assert('ECriterionNodes');
- }
- if (this.criterion.length === 0) {
- if (reader.match('BCriteriaNodes')) {
- this.criterion = reader.strings();
- reader.assert('ECriteriaNodes');
- }
- }
- if (reader.match('BNodesReqMultiSeqHandling')) {
- reader.strings();
- reader.assert('ENodesReqMultiSeqHandling');
- }
- if (reader.match('BEvalNodes')) {
- this.eval = reader.strings();
- reader.assert('EEvalNodes');
- }
- if (reader.match('BOutputNodes')) {
- this.output = reader.strings();
- reader.assert('EOutputNodes');
- }
- if (reader.match('BPairNodes')) {
- this.pair = reader.strings();
- reader.assert('EPairNodes');
- }
- reader.assert('ERootNodes');
- reader.assert('ECN');
- }
- };
- cntk.BinaryReader = class {
- constructor(reader) {
- this._reader = reader;
- }
- get position() {
- return this._reader.position;
- }
- seek(offset) {
- this._reader.seek(offset);
- }
- skip(offset) {
- this._reader.skip(offset);
- }
- read(length) {
- return this._reader.read(length);
- }
- boolean() {
- return this._reader.boolean();
- }
- byte() {
- return this._reader.byte();
- }
- int32() {
- return this._reader.int32();
- }
- uint16() {
- return this._reader.uint16();
- }
- uint32() {
- return this._reader.uint32();
- }
- uint64() {
- return this._reader.uint64();
- }
- float32() {
- return this._reader.float32();
- }
- float64() {
- return this._reader.float64();
- }
- match(text) {
- const position = this.position;
- for (let i = 0; i < text.length; i++) {
- if (this.uint16() !== text.charCodeAt(i)) {
- this.seek(position);
- return false;
- }
- }
- if (this.uint16() !== 0) {
- this.seek(position);
- return false;
- }
- return true;
- }
- assert(text) {
- if (!this.match(text)) {
- throw new cntk.Error(`Invalid '${text}' signature.`);
- }
- }
- string() {
- const content = [];
- let c = this.uint16();
- while (c !== 0) {
- content.push(String.fromCharCode(c));
- c = this.uint16();
- }
- return content.join('');
- }
- strings() {
- const size = this.uint64().toNumber();
- const array = new Array(size);
- for (let i = 0; i < size; i++) {
- array[i] = this.string();
- }
- return array;
- }
- booleans() {
- const size = this.uint64().toNumber();
- const array = new Array(size);
- for (let i = 0; i < size; i++) {
- array[i] = this.boolean();
- }
- return array;
- }
- matrix() {
- const type = this.byte();
- switch (type) {
- case 100: {
- // dense
- this.assert('BMAT');
- const elsize = this.uint64().toNumber();
- const value = {};
- value.name = this.string();
- value.format = this.uint32();
- value.rows = this.uint64().toNumber();
- value.columns = this.uint64().toNumber();
- this.read(elsize * value.rows * value.columns);
- this.assert('EMAT');
- return value;
- }
- case 115: // sparse
- throw new cntk.Error('Matrix sparse type not implemented.');
- default:
- throw new cntk.Error(`Matrix type '${type}' not implemented.`);
- }
- }
- shape(acceptLegacyFormat) {
- const dims = [];
- const rank = this.uint32();
- let dim0 = 0;
- if (rank > 0) {
- dim0 = this.uint32();
- }
- if (!acceptLegacyFormat || dim0 !== 0) {
- if (rank > 0) {
- dims.push(dim0);
- }
- for (let i = 1; i < rank; i++) {
- dims.push(this.uint32());
- }
- } else {
- const dim = this.uint32();
- dims.push(this.uint32());
- dims.push(rank);
- dims.push(dim);
- }
- return { __type__: 'shape', dims };
- }
- };
- cntk.ImageLayoutKind = {
- 0: 'CHW',
- 1: 'HWC'
- };
- cntk.PoolKind = {
- 0: 'None',
- 1: 'Max',
- 2: 'Average'
- };
- cntk.Error = class extends Error {
- constructor(message) {
- super(message);
- this.name = 'Error loading CNTK model.';
- }
- };
- export const ModelFactory = cntk.ModelFactory;
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