[js/web/training] added parameters methods implementations

js/common/lib/backend.ts

@@ -49,8 +49,9 @@ export interface TrainingSessionHandler extends SessionHandler {
       feeds: SessionHandler.FeedsType, fetches: SessionHandler.FetchesType,
       options: InferenceSession.RunOptions): Promise<SessionHandler.ReturnType>;
 
-  loadParametersBuffer(array: Uint8Array, trainableOnly: boolean): Promise<void>;
-  getContiguousParameters(trainableOnly: boolean): Promise<Uint8Array>;
+  getParametersSize(trainableOnly: boolean): Promise<number>;
+  loadParametersBuffer(array: Float32Array, trainableOnly: boolean): Promise<void>;
+  getContiguousParameters(trainableOnly: boolean): Promise<OnnxValue>;
 }
 
 /**

js/common/lib/training-session-impl.ts

@@ -1,11 +1,21 @@
 // Copyright (c) Microsoft Corporation. All rights reserved.
 // Licensed under the MIT License.
 
+import {resolveBackend} from './backend-impl.js';
 import {TrainingSessionHandler} from './backend.js';
 import {InferenceSession as InferenceSession} from './inference-session.js';
+import {OnnxValue} from './onnx-value.js';
+import {Tensor} from './tensor.js';
 import {TrainingSession as TrainingSessionInterface, TrainingSessionCreateOptions} from './training-session.js';
 
 type SessionOptions = InferenceSession.SessionOptions;
+type FeedsType = InferenceSession.FeedsType;
+type FetchesType = InferenceSession.FetchesType;
+type ReturnType = InferenceSession.ReturnType;
+type RunOptions = InferenceSession.RunOptions;
+
+const noBackendErrMsg: string = 'Training backend could not be resolved. ' +
+    'Make sure you\'re using the correct configuration & WebAssembly files.';
 
 export class TrainingSession implements TrainingSessionInterface {
   private constructor(handler: TrainingSessionHandler) {
@@ -20,27 +30,141 @@ export class TrainingSession implements TrainingSessionInterface {
     return this.handler.outputNames;
   }
 
-  static async create(_trainingOptions: TrainingSessionCreateOptions, _sessionOptions?: SessionOptions):
+  static async create(trainingOptions: TrainingSessionCreateOptions, sessionOptions?: SessionOptions):
       Promise<TrainingSession> {
-    throw new Error('Method not implemented');
+    const evalModel: string|Uint8Array = trainingOptions.evalModel || '';
+    const optimizerModel: string|Uint8Array = trainingOptions.optimizerModel || '';
+    const options: SessionOptions = sessionOptions || {};
+
+    // get backend hints
+    const eps = options.executionProviders || [];
+    const backendHints = eps.map(i => typeof i === 'string' ? i : i.name);
+    const backend = await resolveBackend(backendHints);
+    if (backend.createTrainingSessionHandler) {
+      const handler = await backend.createTrainingSessionHandler(
+          trainingOptions.checkpointState, trainingOptions.trainModel, evalModel, optimizerModel, options);
+      return new TrainingSession(handler);
+    } else {
+      throw new Error(noBackendErrMsg);
+    }
+  }
+
+  runTrainStep(feeds: FeedsType, options?: RunOptions): Promise<ReturnType>;
+  runTrainStep(feeds: FeedsType, fetches: FetchesType, options?: RunOptions): Promise<ReturnType>;
+  async runTrainStep(feeds: FeedsType, arg1?: FetchesType|RunOptions, arg2?: RunOptions): Promise<ReturnType> {
+    const fetches: {[name: string]: OnnxValue|null} = {};
+    let options: RunOptions = {};
+    // check inputs
+    if (typeof feeds !== 'object' || feeds === null || feeds instanceof Tensor || Array.isArray(feeds)) {
+      throw new TypeError(
+          '\'feeds\' must be an object that use input names as keys and OnnxValue as corresponding values.');
+    }
+
+    let isFetchesEmpty = true;
+    // determine which override is being used
+    if (typeof arg1 === 'object') {
+      if (arg1 === null) {
+        throw new TypeError('Unexpected argument[1]: cannot be null.');
+      }
+      if (arg1 instanceof Tensor) {
+        throw new TypeError('\'fetches\' cannot be a Tensor');
+      }
+
+      if (Array.isArray(arg1)) {
+        if (arg1.length === 0) {
+          throw new TypeError('\'fetches\' cannot be an empty array.');
+        }
+        isFetchesEmpty = false;
+        // output names
+        for (const name of arg1) {
+          if (typeof name !== 'string') {
+            throw new TypeError('\'fetches\' must be a string array or an object.');
+          }
+          if (this.outputNames.indexOf(name) === -1) {
+            throw new RangeError(`'fetches' contains invalid output name: ${name}.`);
+          }
+          fetches[name] = null;
+        }
+
+        if (typeof arg2 === 'object' && arg2 !== null) {
+          options = arg2;
+        } else if (typeof arg2 !== 'undefined') {
+          throw new TypeError('\'options\' must be an object.');
+        }
+      } else {
+        // decide whether arg1 is fetches or options
+        // if any output name is present and its value is valid OnnxValue, we consider it fetches
+        let isFetches = false;
+        const arg1Keys = Object.getOwnPropertyNames(arg1);
+        for (const name of this.outputNames) {
+          if (arg1Keys.indexOf(name) !== -1) {
+            const v = (arg1 as InferenceSession.NullableOnnxValueMapType)[name];
+            if (v === null || v instanceof Tensor) {
+              isFetches = true;
+              isFetchesEmpty = false;
+              fetches[name] = v;
+            }
+          }
+        }
+
+        if (isFetches) {
+          if (typeof arg2 === 'object' && arg2 !== null) {
+            options = arg2;
+          } else if (typeof arg2 !== 'undefined') {
+            throw new TypeError('\'options\' must be an object.');
+          }
+        } else {
+          options = arg1 as RunOptions;
+        }
+      }
+    } else if (typeof arg1 !== 'undefined') {
+      throw new TypeError('Unexpected argument[1]: must be \'fetches\' or \'options\'.');
+    }
+
+    // check if all inputs are in feed
+    for (const name of this.inputNames) {
+      if (typeof feeds[name] === 'undefined') {
+        throw new Error(`input '${name}' is missing in 'feeds'.`);
+      }
+    }
+
+    // if no fetches is specified, we use the full output names list
+    if (isFetchesEmpty) {
+      for (const name of this.outputNames) {
+        fetches[name] = null;
+      }
+    }
+
+    const results = await this.handler.runTrainStep(feeds, fetches, options);
+    const returnValue: {[name: string]: OnnxValue} = {};
+    for (const key in results) {
+      if (Object.hasOwnProperty.call(results, key)) {
+        const result = results[key];
+        if (result instanceof Tensor) {
+          returnValue[key] = result;
+        } else {
+          returnValue[key] = new Tensor(result.type, result.data, result.dims);
+        }
+      }
+    }
+    return returnValue;
   }
 
-  async loadParametersBuffer(_array: Uint8Array, _trainableOnly: boolean): Promise<void> {
-    throw new Error('Method not implemented.');
+  async getParametersSize(trainableOnly: boolean): Promise<number> {
+    return this.handler.getParametersSize(trainableOnly);
   }
 
-  async getContiguousParameters(_trainableOnly: boolean): Promise<Uint8Array> {
-    throw new Error('Method not implemented.');
+  async loadParametersBuffer(array: Float32Array, trainableOnly: boolean): Promise<void> {
+    const paramsSize = await this.getParametersSize(trainableOnly);
+    if (array.length !== paramsSize) {
+      throw new Error('Size of the buffer passed into loadParametersBuffer must match the number of parameters in ' +
+        'the model. Please use getParametersSize method to check.');
+    }
+    return this.handler.loadParametersBuffer(array, trainableOnly);
   }
 
-  runTrainStep(feeds: InferenceSession.OnnxValueMapType, options?: InferenceSession.RunOptions|undefined):
-      Promise<InferenceSession.OnnxValueMapType>;
-  runTrainStep(
-      feeds: InferenceSession.OnnxValueMapType, fetches: InferenceSession.FetchesType,
-      options?: InferenceSession.RunOptions|undefined): Promise<InferenceSession.OnnxValueMapType>;
-  async runTrainStep(_feeds: unknown, _fetches?: unknown, _options?: unknown):
-      Promise<InferenceSession.OnnxValueMapType> {
-    throw new Error('Method not implemented.');
+  async getContiguousParameters(trainableOnly: boolean): Promise<OnnxValue> {
+    return this.handler.getContiguousParameters(trainableOnly);
   }
 
   async release(): Promise<void> {

js/common/lib/training-session.ts

@@ -2,6 +2,7 @@
 // Licensed under the MIT License.
 
 import {InferenceSession} from './inference-session.js';
+import {OnnxValue} from './onnx-value.js';
 import {TrainingSession as TrainingSessionImpl} from './training-session-impl.js';
 
 /* eslint-disable @typescript-eslint/no-redeclare */
@@ -49,21 +50,29 @@ export interface TrainingSession {
   // #endregion
 
   // #region copy parameters
+
+  /**
+   * Retrieves the size of all parameters for the training state.
+   *
+   * @param trainableOnly skips non-trainable parameters when true.
+   */
+  getParametersSize(trainableOnly: boolean): Promise<number>;
+
   /**
    * Copies from a buffer containing parameters to the TrainingSession parameters.
    *
    * @param buffer - buffer containing parameters
    * @param trainableOnly - True if trainable parameters only to be modified, false otherwise.
    */
-  loadParametersBuffer(array: Uint8Array, trainableOnly: boolean): Promise<void>;
+  loadParametersBuffer(array: Float32Array, trainableOnly: boolean): Promise<void>;
 
   /**
    * Copies from the TrainingSession parameters to a buffer.
    *
    * @param trainableOnly - True if trainable parameters only to be copied, false othrwise.
    * @returns A promise that resolves to a buffer of the requested parameters.
    */
-  getContiguousParameters(trainableOnly: boolean): Promise<Uint8Array>;
+  getContiguousParameters(trainableOnly: boolean): Promise<OnnxValue>;
   // #endregion
 
   // #region release()

js/web/lib/backend-onnxjs.ts

@@ -5,7 +5,7 @@
 import {Backend, InferenceSession, InferenceSessionHandler} from 'onnxruntime-common';
 
 import {Session} from './onnxjs/session';
-import {OnnxjsSessionHandler} from './onnxjs/session-handler';
+import {OnnxjsSessionHandler} from './onnxjs/session-handler-inference';
 
 class OnnxjsBackend implements Backend {
   // eslint-disable-next-line @typescript-eslint/no-empty-function

js/web/lib/backend-wasm-training.ts

@@ -4,13 +4,17 @@
 import {InferenceSession, TrainingSessionHandler} from 'onnxruntime-common';
 
 import {OnnxruntimeWebAssemblyBackend} from './backend-wasm';
+import {OnnxruntimeWebAssemblyTrainingSessionHandler} from './wasm/session-handler-training';
 
 class OnnxruntimeTrainingWebAssemblyBackend extends OnnxruntimeWebAssemblyBackend {
   async createTrainingSessionHandler(
-      _checkpointStateUriOrBuffer: string|Uint8Array, _trainModelUriOrBuffer: string|Uint8Array,
-      _evalModelUriOrBuffer: string|Uint8Array, _optimizerModelUriOrBuffer: string|Uint8Array,
-      _options: InferenceSession.SessionOptions): Promise<TrainingSessionHandler> {
-    throw new Error('Method not implemented yet.');
+      checkpointStateUriOrBuffer: string|Uint8Array, trainModelUriOrBuffer: string|Uint8Array,
+      evalModelUriOrBuffer: string|Uint8Array, optimizerModelUriOrBuffer: string|Uint8Array,
+      options: InferenceSession.SessionOptions): Promise<TrainingSessionHandler> {
+    const handler = new OnnxruntimeWebAssemblyTrainingSessionHandler();
+    await handler.createTrainingSession(
+        checkpointStateUriOrBuffer, trainModelUriOrBuffer, evalModelUriOrBuffer, optimizerModelUriOrBuffer, options);
+    return Promise.resolve(handler);
   }
 }
 

js/web/lib/backend-wasm.ts

@@ -5,7 +5,7 @@ import {cpus} from 'node:os';
 import {Backend, env, InferenceSession, InferenceSessionHandler} from 'onnxruntime-common';
 
 import {initializeWebAssemblyInstance} from './wasm/proxy-wrapper';
-import {OnnxruntimeWebAssemblySessionHandler} from './wasm/session-handler';
+import {OnnxruntimeWebAssemblySessionHandler} from './wasm/session-handler-inference';
 
 /**
  * This function initializes all flags for WebAssembly.

js/web/lib/wasm/binding/ort-wasm.d.ts

@@ -102,6 +102,11 @@ export interface OrtWasmModule extends EmscriptenModule {
   _OrtTrainingCopyParametersFromBuffer?
       (trainingHandle: number, parametersBuffer: number, parameterCount: number, trainableOnly: boolean): number;
 
+  _OrtTrainingGetInputOutputCount?
+      (trainingHandle: number, inputCount: number, outputCount: number, isEvalModel: boolean): number;
+  _OrtTrainingGetInputOutputName?
+      (trainingHandle: number, index: number, isInput: boolean, isEvalModel: boolean): number;
+
   _OrtTrainingReleaseSession?(trainingHandle: number): void;
   // #endregion
 

js/web/lib/wasm/proxy-messages.ts

@@ -73,5 +73,10 @@ interface MesssageEndProfiling extends MessageError {
   in ?: number;
 }
 
+interface MessageIsOrtEnvInitialized extends MessageError {
+  type: 'is-ort-env-initialized';
+  out?: boolean;
+}
+
 export type OrtWasmMessage = MessageInitWasm|MessageInitOrt|MessageCreateSessionAllocate|MessageCreateSessionFinalize|
-    MessageCreateSession|MessageReleaseSession|MessageRun|MesssageEndProfiling;
+    MessageCreateSession|MessageReleaseSession|MessageRun|MesssageEndProfiling|MessageIsOrtEnvInitialized;

js/web/lib/wasm/proxy-worker/main.ts

@@ -4,7 +4,7 @@
 /// <reference lib="webworker" />
 
 import {OrtWasmMessage} from '../proxy-messages';
-import {createSession, createSessionAllocate, createSessionFinalize, endProfiling, extractTransferableBuffers, initRuntime, releaseSession, run} from '../wasm-core-impl';
+import {createSession, createSessionAllocate, createSessionFinalize, endProfiling, extractTransferableBuffers, initRuntime, isOrtEnvInitialized, releaseSession, run} from '../wasm-core-impl';
 import {initializeWebAssembly} from '../wasm-factory';
 
 self.onmessage = (ev: MessageEvent<OrtWasmMessage>): void => {
@@ -89,6 +89,14 @@ self.onmessage = (ev: MessageEvent<OrtWasmMessage>): void => {
         postMessage({type: 'end-profiling', err} as OrtWasmMessage);
       }
       break;
+    case 'is-ort-env-initialized':
+      try {
+        const ortEnvInitialized = isOrtEnvInitialized();
+        postMessage({type: 'is-ort-env-initialized', out: ortEnvInitialized} as OrtWasmMessage);
+      } catch (err) {
+        postMessage({type: 'is-ort-env-initialized', err} as OrtWasmMessage);
+      }
+      break;
     default:
   }
 };

js/web/lib/wasm/proxy-wrapper.ts

@@ -24,6 +24,7 @@ const createSessionCallbacks: Array<PromiseCallbacks<SerializableSessionMetadata
 const releaseSessionCallbacks: Array<PromiseCallbacks<void>> = [];
 const runCallbacks: Array<PromiseCallbacks<SerializableTensorMetadata[]>> = [];
 const endProfilingCallbacks: Array<PromiseCallbacks<void>> = [];
+const isOrtEnvInitializedCallbacks: Array<PromiseCallbacks<boolean>> = [];
 
 const ensureWorker = (): void => {
   if (initializing || !initialized || aborted || !proxyWorker) {
@@ -92,6 +93,13 @@ const onProxyWorkerMessage = (ev: MessageEvent<OrtWasmMessage>): void => {
         endProfilingCallbacks.shift()![0]();
       }
       break;
+    case 'is-ort-env-initialized':
+      if (ev.data.err) {
+        isOrtEnvInitializedCallbacks.shift()![1](ev.data.err);
+      } else {
+        isOrtEnvInitializedCallbacks.shift()![0](ev.data.out!);
+      }
+      break;
     default:
   }
 };
@@ -251,3 +259,16 @@ export const endProfiling = async(sessionId: number): Promise<void> => {
     core.endProfiling(sessionId);
   }
 };
+
+export const isOrtEnvInitialized = async(): Promise<boolean> => {
+  if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
+    ensureWorker();
+    return new Promise<boolean>((resolve, reject) => {
+      isOrtEnvInitializedCallbacks.push([resolve, reject]);
+      const message: OrtWasmMessage = {type: 'is-ort-env-initialized'};
+      proxyWorker!.postMessage(message);
+    });
+  } else {
+    return core.isOrtEnvInitialized();
+  }
+};

js/web/lib/wasm/session-handler.ts → js/web/lib/wasm/session-handler-inference.ts

@@ -5,13 +5,12 @@ import {readFile} from 'node:fs/promises';
 import {env, InferenceSession, InferenceSessionHandler, SessionHandler, Tensor} from 'onnxruntime-common';
 
 import {SerializableModeldata, TensorMetadata} from './proxy-messages';
-import {createSession, createSessionAllocate, createSessionFinalize, endProfiling, initializeRuntime, releaseSession, run} from './proxy-wrapper';
+import {createSession, createSessionAllocate, createSessionFinalize, endProfiling, initializeRuntime, isOrtEnvInitialized, releaseSession, run} from './proxy-wrapper';
 import {isGpuBufferSupportedType} from './wasm-common';
 
-let runtimeInitialized: boolean;
 let runtimeInitializationPromise: Promise<void>|undefined;
 
-const encodeTensorMetadata = (tensor: Tensor, getName: () => string): TensorMetadata => {
+export const encodeTensorMetadata = (tensor: Tensor, getName: () => string): TensorMetadata => {
   switch (tensor.location) {
     case 'cpu':
       return [tensor.type, tensor.dims, tensor.data, 'cpu'];
@@ -22,7 +21,7 @@ const encodeTensorMetadata = (tensor: Tensor, getName: () => string): TensorMeta
   }
 };
 
-const decodeTensorMetadata = (tensor: TensorMetadata): Tensor => {
+export const decodeTensorMetadata = (tensor: TensorMetadata): Tensor => {
   switch (tensor[3]) {
     case 'cpu':
       return new Tensor(tensor[0], tensor[2], tensor[1]);
@@ -57,13 +56,12 @@ export class OnnxruntimeWebAssemblySessionHandler implements InferenceSessionHan
   }
 
   async loadModel(pathOrBuffer: string|Uint8Array, options?: InferenceSession.SessionOptions): Promise<void> {
-    if (!runtimeInitialized) {
+    if (!(await isOrtEnvInitialized())) {
       if (!runtimeInitializationPromise) {
         runtimeInitializationPromise = initializeRuntime(env);
       }
       await runtimeInitializationPromise;
       runtimeInitializationPromise = undefined;
-      runtimeInitialized = true;
     }
 
     if (typeof pathOrBuffer === 'string') {