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- import * as flatbuffers from './flatbuffers.js';
- import * as flexbuffers from './flexbuffers.js';
- import * as zip from './zip.js';
- const circle = {};
- circle.ModelFactory = class {
- async match(context) {
- const reader = await context.peek('flatbuffers.binary');
- if (reader && reader.identifier === 'CIR0') {
- return context.set('circle.flatbuffers', reader);
- }
- const obj = await context.peek('json');
- if (obj && obj.subgraphs && obj.operator_codes) {
- return context.set('circle.flatbuffers.json', obj);
- }
- return null;
- }
- async open(context) {
- circle.schema = await context.require('./circle-schema');
- circle.schema = circle.schema.circle;
- let model = null;
- const attachments = new Map();
- switch (context.type) {
- case 'circle.flatbuffers.json': {
- try {
- const reader = await context.read('flatbuffers.text');
- model = circle.schema.Model.createText(reader);
- } catch (error) {
- const message = error && error.message ? error.message : error.toString();
- throw new circle.Error(`File text format is not circle.Model (${message.replace(/\.$/, '')}).`);
- }
- break;
- }
- case 'circle.flatbuffers': {
- try {
- const reader = context.value;
- model = circle.schema.Model.create(reader);
- } catch (error) {
- const message = error && error.message ? error.message : error.toString();
- throw new circle.Error(`File format is not circle.Model (${message.replace(/\.$/, '')}).`);
- }
- try {
- const stream = context.stream;
- const archive = zip.Archive.open(stream);
- if (archive) {
- for (const [name, value] of archive.entries) {
- attachments.set(name, value);
- }
- }
- } catch {
- // continue regardless of error
- }
- break;
- }
- default: {
- throw new circle.Error(`Unsupported Circle format '${context.type}'.`);
- }
- }
- const stream = context.stream;
- const metadata = await context.metadata('circle-metadata.json');
- return new circle.Model(metadata, model, stream);
- }
- };
- circle.Model = class {
- constructor(metadata, model, stream) {
- this.format = 'Circle';
- this.format = `${this.format} v${model.version}`;
- this.description = model.description || '';
- this.modules = [];
- this.metadata = [];
- const builtinOperators = new Map();
- const upperCase = new Set(['2D', 'LSH', 'SVDF', 'RNN', 'L2', 'LSTM']);
- for (const key of Object.keys(circle.schema.BuiltinOperator)) {
- const value = key === 'BATCH_MATMUL' ? 'BATCH_MAT_MUL' : key;
- const name = value.split('_').map((s) => (s.length < 1 || upperCase.has(s)) ? s : s[0] + s.substring(1).toLowerCase()).join('');
- const index = circle.schema.BuiltinOperator[key];
- builtinOperators.set(index, name);
- }
- const operators = model.operator_codes.map((operator) => {
- const code = Math.max(operator.deprecated_builtin_code, operator.builtin_code || 0);
- const value = {};
- if (code === circle.schema.BuiltinOperator.CUSTOM) {
- value.name = operator.custom_code ? operator.custom_code : 'Custom';
- value.version = operator.version;
- value.custom = true;
- } else {
- value.name = builtinOperators.has(code) ? builtinOperators.get(code) : code.toString();
- value.version = operator.version;
- value.custom = false;
- }
- return value;
- });
- let modelMetadata = null;
- for (const metadata of model.metadata) {
- const buffer = model.buffers[metadata.buffer];
- let data = null;
- const position = stream.position;
- if (buffer && buffer.data && buffer.data.length > 0) {
- data = buffer.data;
- } else if (buffer && buffer.offset !== 0n && buffer.size !== 0n) {
- const offset = buffer.offset.toNumber();
- const size = buffer.size.toNumber();
- stream.seek(offset);
- data = stream.read(size);
- }
- stream.seek(position);
- if (data) {
- switch (metadata.name) {
- case 'min_runtime_version': {
- const decoder = new TextDecoder('utf-8');
- this.runtime = decoder.decode(data);
- break;
- }
- case 'TFLITE_METADATA': {
- const reader = flatbuffers.BinaryReader.open(data);
- if (!reader || !circle.schema.ModelMetadata.identifier(reader)) {
- throw new circle.Error('Invalid TensorFlow Lite metadata.');
- }
- modelMetadata = circle.schema.ModelMetadata.create(reader);
- if (modelMetadata.name) {
- this.name = modelMetadata.name;
- }
- if (modelMetadata.version) {
- this.version = modelMetadata.version;
- }
- if (modelMetadata.description) {
- this.description = this.description ? [this.description, modelMetadata.description].join(' ') : modelMetadata.description;
- }
- if (modelMetadata.author) {
- this.metadata.push(new circle.Argument('author', modelMetadata.author));
- }
- if (modelMetadata.license) {
- this.metadata.push(new circle.Argument('license', modelMetadata.license));
- }
- break;
- }
- default: {
- const value = data.length < 256 && data.every((c) => c >= 32 && c < 128) ? String.fromCharCode.apply(null, data) : '?';
- const argument = new circle.Argument(metadata.name, value);
- this.metadata.push(argument);
- break;
- }
- }
- }
- }
- const subgraphs = model.subgraphs;
- const subgraphsMetadata = modelMetadata ? modelMetadata.subgraph_metadata : null;
- for (let i = 0; i < subgraphs.length; i++) {
- const subgraph = subgraphs[i];
- const name = subgraphs.length > 1 ? i.toString() : '';
- const subgraphMetadata = subgraphsMetadata && i < subgraphsMetadata.length ? subgraphsMetadata[i] : null;
- const signatures = model.signature_defs.filter((signature) => signature.subgraph_index === i);
- const graph = new circle.Graph(metadata, subgraph, signatures, subgraphMetadata, name, operators, model, stream);
- this.modules.push(graph);
- }
- }
- };
- circle.Graph = class {
- constructor(metadata, subgraph, signatures, subgraphMetadata, name, operators, model, stream) {
- this.name = subgraph.name || name;
- if (subgraph.operators.length === 0 && subgraph.tensors.length > 0 && operators.length === 0) {
- operators.push({ name: 'Weights', custom: true });
- const layers = new Map();
- for (let i = 0; i < subgraph.tensors.length; i++) {
- const tensor = subgraph.tensors[i];
- const parts = tensor.name.split('.');
- parts.pop();
- const key = parts.join('.');
- if (!layers.has(key)) {
- const operator = { opcode_index: 0, inputs: [], outputs: [] };
- layers.set(key, operator);
- subgraph.operators.push(operator);
- }
- const operator = layers.get(key);
- operator.inputs.push(i);
- }
- }
- const tensors = new Map();
- tensors.map = (index, metadata) => {
- if (index === -1) {
- return null;
- }
- if (!tensors.has(index)) {
- let tensor = { name: '' };
- let initializer = null;
- let description = '';
- let denotation = '';
- if (index < subgraph.tensors.length) {
- tensor = subgraph.tensors[index];
- const buffer = model.buffers[tensor.buffer];
- const is_variable = tensor.is_variable;
- const variable = is_variable || (buffer && buffer.data && buffer.data.length > 0) || (buffer && buffer.offset !== 0n && buffer.size !== 0n);
- initializer = variable ? new circle.Tensor(index, tensor, buffer, stream, is_variable) : null;
- }
- if (metadata) {
- description = metadata.description;
- const content = metadata.content;
- if (content) {
- const contentProperties = content.content_properties;
- if (contentProperties instanceof circle.schema.FeatureProperties) {
- denotation = 'Feature';
- } else if (contentProperties instanceof circle.schema.ImageProperties) {
- denotation = 'Image';
- switch (contentProperties.color_space) {
- case 0: denotation += '(Unknown)'; break;
- case 1: denotation += '(RGB)'; break;
- case 2: denotation += '(Grayscale)'; break;
- default: throw circle.Error(`Unsupported image color space '${contentProperties.color_space}'.`);
- }
- } else if (contentProperties instanceof circle.schema.BoundingBoxProperties) {
- denotation = 'BoundingBox';
- } else if (contentProperties instanceof circle.schema.AudioProperties) {
- denotation = `Audio(${contentProperties.sample_rate},${contentProperties.channels})`;
- }
- }
- }
- const value = new circle.Value(index, tensor, initializer, description, denotation);
- tensors.set(index, value);
- }
- return tensors.get(index);
- };
- this.inputs = Array.from(subgraph.inputs).map((tensor_index, index) => {
- const metadata = subgraphMetadata && index < subgraphMetadata.input_tensor_metadata.length ? subgraphMetadata.input_tensor_metadata[index] : null;
- const value = tensors.map(tensor_index, metadata);
- const values = value ? [value] : [];
- const name = value ? value.name.split('\n')[0] : '?';
- return new circle.Argument(name, values);
- });
- this.outputs = Array.from(subgraph.outputs).map((tensor_index, index) => {
- const metadata = subgraphMetadata && index < subgraphMetadata.output_tensor_metadata.length ? subgraphMetadata.output_tensor_metadata[index] : null;
- const value = tensors.map(tensor_index, metadata);
- const values = value ? [value] : [];
- const name = value ? value.name.split('\n')[0] : '?';
- return new circle.Argument(name, values);
- });
- this.signatures = signatures.map((signature) => {
- return new circle.Signature(signature, tensors);
- });
- this.nodes = Array.from(subgraph.operators).map((operator, index) => {
- const opcode_index = operator.opcode_index;
- const opcode = opcode_index < operators.length ? operators[opcode_index] : { name: `(${opcode_index})` };
- return new circle.Node(metadata, operator, opcode, index.toString(), tensors);
- });
- }
- };
- circle.Signature = class {
- constructor(signature, tensors) {
- this.name = signature.signature_key;
- this.inputs = signature.inputs.map((input) => {
- const value = tensors.map(input.tensor_index);
- const values = value ? [value] : [];
- return new circle.Argument(input.name, values);
- });
- this.outputs = signature.outputs.map((output) => {
- const value = tensors.map(output.tensor_index);
- const values = value ? [value] : [];
- return new circle.Argument(output.name, values);
- });
- }
- };
- circle.Node = class {
- constructor(metadata, node, type, identifier, tensors) {
- this.name = '';
- this.identifier = identifier;
- this.type = type.custom ? { name: type.name } : metadata.type(type.name);
- this.inputs = [];
- this.outputs = [];
- this.attributes = [];
- if (node) {
- const attributes = [];
- const inputs = Array.from(node.inputs || new Int32Array(0));
- for (let i = 0; i < inputs.length;) {
- let count = 1;
- let name = null;
- let visible = true;
- const values = [];
- if (this.type && this.type.inputs && i < this.type.inputs.length) {
- const input = this.type.inputs[i];
- name = input.name;
- if (input.list) {
- count = inputs.length - i;
- }
- if (input.visible === false) {
- visible = false;
- }
- }
- for (const index of inputs.slice(i, i + count)) {
- const value = tensors.map(index);
- if (value) {
- values.push(value);
- }
- }
- name = name ? name : (i + 1).toString();
- i += count;
- const argument = new circle.Argument(name, values, null, visible);
- this.inputs.push(argument);
- }
- const outputs = Array.from(node.outputs || new Int32Array(0));
- for (let i = 0; i < outputs.length; i++) {
- const index = outputs[i];
- const value = tensors.map(index);
- const values = value ? [value] : [];
- let name = (i + 1).toString();
- if (this.type && this.type.outputs && i < this.type.outputs.length) {
- const output = this.type.outputs[i];
- if (output && output.name) {
- name = output.name;
- }
- }
- const argument = new circle.Argument(name, values);
- this.outputs.push(argument);
- }
- if (type.custom && node.custom_options && node.custom_options.length > 0) {
- let decoded = false;
- if (node.custom_options_format === circle.schema.CustomOptionsFormat.FLEXBUFFERS) {
- try {
- const reader = flexbuffers.BinaryReader.open(node.custom_options);
- if (reader) {
- const custom_options = reader.read();
- if (Array.isArray(custom_options)) {
- attributes.push([null, 'custom_options', custom_options]);
- decoded = true;
- } else if (custom_options) {
- for (const [key, value] of Object.entries(custom_options)) {
- const schema = metadata.attribute(type.name, key);
- attributes.push([schema, key, value]);
- }
- decoded = true;
- }
- }
- } catch {
- // continue regardless of error
- }
- }
- if (!decoded) {
- const schema = metadata.attribute(type.name, 'custom');
- attributes.push([schema, 'custom', Array.from(node.custom_options)]);
- }
- }
- const options = node.builtin_options;
- if (options) {
- for (const [name, value] of Object.entries(options)) {
- if (name === 'fused_activation_function' && value) {
- if (value < 1 || value > 5) {
- throw new circle.Error(`Unsupported activation function index '${value}'.`);
- }
- const list = ['Unknown', 'Relu', 'ReluN1To1', 'Relu6', 'Tanh', 'SignBit'];
- const type = list[value];
- const node = new circle.Node(metadata, null, { name: type }, null, []);
- this.chain = [node];
- }
- const schema = metadata.attribute(type.name, name);
- attributes.push([schema, name, value]);
- }
- }
- this.attributes = attributes.map(([metadata, name, value]) => {
- const type = metadata && metadata.type ? metadata.type : null;
- value = ArrayBuffer.isView(value) ? Array.from(value) : value;
- let visible = true;
- if (name === 'fused_activation_function') {
- visible = false;
- }
- if (type) {
- value = circle.Utility.enum(type, value);
- }
- if (metadata) {
- if (metadata.visible === false) {
- visible = false;
- } else if (metadata.default !== undefined) {
- if (typeof value === 'function') {
- value = value();
- }
- if (value === metadata.default) {
- visible = false;
- }
- }
- }
- return new circle.Argument(name, value, type, visible);
- });
- }
- }
- };
- circle.Argument = class {
- constructor(name, value, type = null, visible = true) {
- this.name = name;
- this.value = value;
- this.type = type;
- this.visible = visible;
- }
- };
- circle.Value = class {
- constructor(index, tensor, initializer, description, denotation) {
- const name = tensor.name || '';
- this.name = `${name}\n${index}`;
- this.identifier = index.toString();
- this.type = tensor.type !== undefined && tensor.shape !== undefined ? new circle.TensorType(tensor, denotation) : null;
- this.initializer = initializer;
- this.description = description;
- const quantization = tensor.quantization;
- if (quantization && (quantization.scale.length > 0 || quantization.zero_point.length > 0 || quantization.min.length > 0 || quantization.max.length)) {
- this.quantization = {
- type: 'linear',
- dimension: quantization.quantized_dimension,
- scale: quantization.scale,
- offset: quantization.zero_point,
- min: quantization.min,
- max: quantization.max
- };
- }
- }
- };
- circle.Tensor = class {
- constructor(index, tensor, buffer, stream, is_variable) {
- this.identifier = index.toString();
- this.name = tensor.name;
- this.type = new circle.TensorType(tensor);
- this.category = is_variable ? 'Variable' : '';
- this.encoding = this.type.dataType === 'string' ? '|' : '<';
- if (buffer && buffer.data && buffer.data.length > 0) {
- this._data = buffer.data.slice(0);
- } else if (buffer && buffer.offset !== 0n && buffer.size !== 0n) {
- const offset = buffer.offset.toNumber();
- const size = buffer.size.toNumber();
- stream.seek(offset);
- this._data = stream.stream(size);
- } else {
- this._data = null;
- }
- }
- get values() {
- switch (this.type.dataType) {
- case 'string': {
- let offset = 0;
- const data = new DataView(this._data.buffer, this._data.byteOffset, this._data.byteLength);
- const count = data.getInt32(0, true);
- offset += 4;
- const offsetTable = [];
- for (let j = 0; j < count; j++) {
- offsetTable.push(data.getInt32(offset, true));
- offset += 4;
- }
- offsetTable.push(this._data.length);
- const stringTable = [];
- const utf8Decoder = new TextDecoder('utf-8');
- for (let k = 0; k < count; k++) {
- const textArray = this._data.subarray(offsetTable[k], offsetTable[k + 1]);
- stringTable.push(utf8Decoder.decode(textArray));
- }
- return stringTable;
- }
- default: {
- if (this._data instanceof Uint8Array) {
- return this._data;
- }
- if (this._data && this._data.peek) {
- return this._data.peek();
- }
- return null;
- }
- }
- }
- };
- circle.TensorType = class {
- constructor(tensor, denotation) {
- const shape = tensor.shape_signature && tensor.shape_signature.length > 0 ? tensor.shape_signature : tensor.shape;
- this.dataType = circle.Utility.dataType(tensor.type);
- this.shape = new circle.TensorShape(Array.from(shape || []));
- this.denotation = denotation;
- }
- toString() {
- return this.dataType + this.shape.toString();
- }
- };
- circle.TensorShape = class {
- constructor(dimensions) {
- this.dimensions = dimensions;
- }
- toString() {
- if (!this.dimensions || this.dimensions.length === 0) {
- return '';
- }
- return `[${this.dimensions.map((dimension) => dimension.toString()).join(',')}]`;
- }
- };
- circle.Utility = class {
- static dataType(type) {
- if (!circle.Utility._tensorTypes) {
- circle.Utility._tensorTypes = new Map(Object.entries(circle.schema.TensorType).map(([key, value]) => [value, key.toLowerCase()]));
- circle.Utility._tensorTypes.set(6, 'boolean');
- }
- return circle.Utility._tensorTypes.has(type) ? circle.Utility._tensorTypes.get(type) : '?';
- }
- static enum(name, value) {
- const type = name && circle.schema ? circle.schema[name] : undefined;
- if (type) {
- circle.Utility._enums = circle.Utility._enums || new Map();
- if (!circle.Utility._enums.has(name)) {
- const entries = new Map(Object.entries(type).map(([key, value]) => [value, key]));
- circle.Utility._enums.set(name, entries);
- }
- const map = circle.Utility._enums.get(name);
- if (map.has(value)) {
- return map.get(value);
- }
- }
- return value;
- }
- };
- circle.Error = class extends Error {
- constructor(message) {
- super(message);
- this.name = 'Error loading Circle model.';
- }
- };
- export const ModelFactory = circle.ModelFactory;
|