chore: update node_modules with new binary files and dependencies
- Add new binary files for nodemon, onnxruntime-web, and xenova/transformers - Update various JavaScript and TypeScript files in node_modules - Remove unused files and dependencies - Add new test fixtures and documentation files
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node_modules/onnxruntime-web/lib/onnxjs/session.ts
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node_modules/onnxruntime-web/lib/onnxjs/session.ts
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import {readFile} from 'fs';
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import {promisify} from 'util';
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import {resolveBackend, SessionHandlerType} from './backend';
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import {ExecutionPlan} from './execution-plan';
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import {Graph} from './graph';
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import {Profiler} from './instrument';
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import {Model} from './model';
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import {Operator} from './operators';
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import {Tensor} from './tensor';
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export declare namespace Session {
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export interface Config {
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backendHint?: string;
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profiler?: Profiler.Config;
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}
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export interface Context {
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profiler: Readonly<Profiler>;
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graphInputTypes?: Tensor.DataType[];
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graphInputDims?: Array<readonly number[]>;
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}
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}
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export class Session {
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constructor(config: Session.Config = {}) {
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this._initialized = false;
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this.backendHint = config.backendHint;
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this.profiler = Profiler.create(config.profiler);
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this.context = {profiler: this.profiler, graphInputTypes: [], graphInputDims: []};
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}
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get inputNames(): readonly string[] {
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return this._model.graph.getInputNames();
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}
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get outputNames(): readonly string[] {
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return this._model.graph.getOutputNames();
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}
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startProfiling() {
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this.profiler.start();
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}
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endProfiling() {
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this.profiler.stop();
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}
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async loadModel(uri: string): Promise<void>;
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async loadModel(buffer: ArrayBuffer, byteOffset?: number, length?: number): Promise<void>;
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async loadModel(buffer: Uint8Array): Promise<void>;
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async loadModel(arg: string|ArrayBuffer|Uint8Array, byteOffset?: number, length?: number): Promise<void> {
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await this.profiler.event('session', 'Session.loadModel', async () => {
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// resolve backend and session handler
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const backend = await resolveBackend(this.backendHint);
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this.sessionHandler = backend.createSessionHandler(this.context);
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this._model = new Model();
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if (typeof arg === 'string') {
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const isOrtFormat = arg.endsWith('.ort');
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if (typeof fetch === 'undefined') {
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// node
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const buf = await promisify(readFile)(arg);
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this.initialize(buf, isOrtFormat);
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} else {
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// browser
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const response = await fetch(arg);
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const buf = await response.arrayBuffer();
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this.initialize(new Uint8Array(buf), isOrtFormat);
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}
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} else if (!ArrayBuffer.isView(arg)) {
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// load model from ArrayBuffer
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const arr = new Uint8Array(arg, byteOffset || 0, length || arg.byteLength);
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this.initialize(arr);
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} else {
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// load model from Uint8array
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this.initialize(arg);
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}
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});
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}
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private initialize(modelProtoBlob: Uint8Array, isOrtFormat?: boolean): void {
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if (this._initialized) {
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throw new Error('already initialized');
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}
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this.profiler.event('session', 'Session.initialize', () => {
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// load graph
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const graphInitializer =
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this.sessionHandler.transformGraph ? this.sessionHandler as Graph.Initializer : undefined;
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this._model.load(modelProtoBlob, graphInitializer, isOrtFormat);
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// graph is completely initialzied at this stage , let the interested handlers know
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if (this.sessionHandler.onGraphInitialized) {
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this.sessionHandler.onGraphInitialized(this._model.graph);
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}
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// initialize each operator in the graph
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this.initializeOps(this._model.graph);
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// instantiate an ExecutionPlan object to be used by the Session object
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this._executionPlan = new ExecutionPlan(this._model.graph, this._ops, this.profiler);
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});
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this._initialized = true;
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}
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async run(inputs: Map<string, Tensor>|Tensor[]): Promise<Map<string, Tensor>> {
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if (!this._initialized) {
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throw new Error('session not initialized yet');
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}
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return this.profiler.event('session', 'Session.run', async () => {
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const inputTensors = this.normalizeAndValidateInputs(inputs);
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const outputTensors = await this._executionPlan.execute(this.sessionHandler, inputTensors);
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return this.createOutput(outputTensors);
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});
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}
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private normalizeAndValidateInputs(inputs: Map<string, Tensor>|Tensor[]): Tensor[] {
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const modelInputNames = this._model.graph.getInputNames();
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// normalize inputs
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// inputs: Tensor[]
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if (Array.isArray(inputs)) {
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if (inputs.length !== modelInputNames.length) {
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throw new Error(`incorrect input array length: expected ${modelInputNames.length} but got ${inputs.length}`);
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}
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}
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// convert map to array
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// inputs: Map<string, Tensor>
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else {
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if (inputs.size !== modelInputNames.length) {
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throw new Error(`incorrect input map size: expected ${modelInputNames.length} but got ${inputs.size}`);
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}
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const sortedInputs = new Array<Tensor>(inputs.size);
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let sortedInputsIndex = 0;
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for (let i = 0; i < modelInputNames.length; ++i) {
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const tensor = inputs.get(modelInputNames[i]);
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if (!tensor) {
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throw new Error(`missing input tensor for: '${name}'`);
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}
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sortedInputs[sortedInputsIndex++] = tensor;
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}
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inputs = sortedInputs;
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}
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// validate dims requirements
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// First session run - graph input data is not cached for the session
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if (!this.context.graphInputTypes || this.context.graphInputTypes.length === 0 || !this.context.graphInputDims ||
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this.context.graphInputDims.length === 0) {
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const modelInputIndices = this._model.graph.getInputIndices();
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const modelValues = this._model.graph.getValues();
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const graphInputDims = new Array<readonly number[]>(modelInputIndices.length);
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for (let i = 0; i < modelInputIndices.length; ++i) {
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const graphInput = modelValues[modelInputIndices[i]];
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graphInputDims[i] = graphInput.type!.shape.dims;
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// cached for second and subsequent runs.
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// Some parts of the framework works on the assumption that the graph and types and shapes are static
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this.context.graphInputTypes!.push(graphInput.type!.tensorType);
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this.context.graphInputDims!.push(inputs[i].dims);
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}
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this.validateInputTensorDims(graphInputDims, inputs, true);
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}
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// Second and subsequent session runs - graph input data is cached for the session
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else {
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this.validateInputTensorDims(this.context.graphInputDims, inputs, false);
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}
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// validate types requirement
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this.validateInputTensorTypes(this.context.graphInputTypes!, inputs);
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return inputs;
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}
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private validateInputTensorTypes(graphInputTypes: Tensor.DataType[], givenInputs: Tensor[]) {
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for (let i = 0; i < givenInputs.length; i++) {
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const expectedType = graphInputTypes[i];
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const actualType = givenInputs[i].type;
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if (expectedType !== actualType) {
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throw new Error(`input tensor[${i}] check failed: expected type '${expectedType}' but got ${actualType}`);
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}
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}
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}
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private validateInputTensorDims(
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graphInputDims: Array<readonly number[]>, givenInputs: Tensor[], noneDimSupported: boolean) {
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for (let i = 0; i < givenInputs.length; i++) {
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const expectedDims = graphInputDims[i];
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const actualDims = givenInputs[i].dims;
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if (!this.compareTensorDims(expectedDims, actualDims, noneDimSupported)) {
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throw new Error(`input tensor[${i}] check failed: expected shape '[${expectedDims.join(',')}]' but got [${
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actualDims.join(',')}]`);
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}
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}
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}
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private compareTensorDims(expectedDims: readonly number[], actualDims: readonly number[], noneDimSupported: boolean):
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boolean {
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if (expectedDims.length !== actualDims.length) {
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return false;
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}
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for (let i = 0; i < expectedDims.length; ++i) {
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if (expectedDims[i] !== actualDims[i] && (!noneDimSupported || expectedDims[i] !== 0)) {
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// data shape mis-match AND not a 'None' dimension.
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return false;
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}
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}
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return true;
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}
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private createOutput(outputTensors: Tensor[]): Map<string, Tensor> {
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const modelOutputNames = this._model.graph.getOutputNames();
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if (outputTensors.length !== modelOutputNames.length) {
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throw new Error('expected number of outputs do not match number of generated outputs');
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}
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const output = new Map<string, Tensor>();
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for (let i = 0; i < modelOutputNames.length; ++i) {
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output.set(modelOutputNames[i], outputTensors[i]);
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}
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return output;
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}
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private initializeOps(graph: Graph): void {
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const nodes = graph.getNodes();
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this._ops = new Array(nodes.length);
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for (let i = 0; i < nodes.length; i++) {
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this._ops[i] = this.sessionHandler.resolve(nodes[i], this._model.opsets, graph);
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}
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}
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private _model: Model;
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private _initialized: boolean;
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private _ops: Operator[];
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private _executionPlan: ExecutionPlan;
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private backendHint?: string;
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private sessionHandler: SessionHandlerType;
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private context: Session.Context;
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private profiler: Readonly<Profiler>;
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}
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