[WebNN EP] Add cache for MLContexts in the WebNNBackend

### Description
This change adds a cache of `MLContext`s keyed by their options to the `WebNNBackend`. This makes is so that multiple `InferenceSession`s create with the same options will share the same context.

### Motivation and Context
Since `MLTensor`s are tied `MLContext`s, developer can't easily share tensors between `InferenceSession` (outside of manually an `MLContext` and specifying the `context` options). This leads strange behaviors such as,
```js
const sessionsA = ort.InferenceSession.create(urlA, {
  executionProviders: ["webnn"],
  preferredOutputLocation: "ml-buffer",
});
const sessionsB = ort.InferenceSession.create(urlB, {
  executionProviders: ["webnn"],
});
const temp = await sessionA.run({/* arguments */});
const result = await sessionB.run({"input":temp["output"]}); // ERROR: Failed to execute 'dispatch' on 'MLContext': Invalid inputs: The context of MLGraph doesn't match the context of the MLTensor with name "input".
```
We encountered this behavior when updating the transformers.js version in the developer preview demos. microsoft/webnn-developer-preview#46

js/web/lib/wasm/jsep/backend-webnn.ts

@@ -30,6 +30,33 @@ const onnxDataTypeToWebnnDataType = new Map<DataType, MLOperandDataType>([
   [DataType.bool, 'uint8'],
 ]);
 
+type MLContextEntry = {
+  gpuDevice?: GPUDevice;
+  options?: MLContextOptions;
+  mlContext: MLContext;
+};
+
+const compareMLContextOptions = (a?: MLContextOptions, b?: MLContextOptions): boolean => {
+  if (a === b) {
+    return true;
+  }
+  if (a === undefined || b === undefined) {
+    return false;
+  }
+  const aKeys = Object.keys(a).sort();
+  const bKeys = Object.keys(b).sort();
+  if (aKeys.length !== bKeys.length) {
+    return false;
+  }
+  type GeneticObject = { [key: string]: object };
+  for (const key of aKeys) {
+    if ((a as GeneticObject)[key] !== (b as GeneticObject)[key]) {
+      return false;
+    }
+  }
+  return true;
+};
+
 /**
  * WebNN backend implementation. This class is used to keep track of the MLTensors created by the backend and keep track
  * of the current MLContext being used by the sessions.
@@ -47,6 +74,10 @@ export class WebNNBackend {
    * Maps from MLContext to session ids.
    */
   private sessionIdsByMLContext = new Map<MLContext, Set<number>>();
+  /**
+   * Cache of MLContexts.
+   */
+  private mlContextCache: MLContextEntry[] = [];
   /**
    * Current session id.
    */
@@ -67,6 +98,41 @@ export class WebNNBackend {
     this.activeSessionId = sessionId;
   }
 
+  public async createMLContext(optionsOrDevice?: MLContextOptions | GPUDevice): Promise<MLContext> {
+    if (optionsOrDevice instanceof GPUDevice) {
+      const mlContextIndex = this.mlContextCache.findIndex((entry) => entry.gpuDevice === optionsOrDevice);
+      if (mlContextIndex !== -1) {
+        return this.mlContextCache[mlContextIndex].mlContext;
+      } else {
+        const mlContext = await navigator.ml.createContext(optionsOrDevice);
+        this.mlContextCache.push({ gpuDevice: optionsOrDevice, mlContext });
+        return mlContext;
+      }
+    } else if (optionsOrDevice === undefined) {
+      const mlContextIndex = this.mlContextCache.findIndex(
+        (entry) => entry.options === undefined && entry.gpuDevice === undefined,
+      );
+      if (mlContextIndex !== -1) {
+        return this.mlContextCache[mlContextIndex].mlContext;
+      } else {
+        const mlContext = await navigator.ml.createContext();
+        this.mlContextCache.push({ mlContext });
+        return mlContext;
+      }
+    }
+
+    const mlContextIndex = this.mlContextCache.findIndex((entry) =>
+      compareMLContextOptions(entry.options, optionsOrDevice),
+    );
+    if (mlContextIndex !== -1) {
+      return this.mlContextCache[mlContextIndex].mlContext;
+    } else {
+      const mlContext = await navigator.ml.createContext(optionsOrDevice);
+      this.mlContextCache.push({ options: optionsOrDevice, mlContext });
+      return mlContext;
+    }
+  }
+
   public get currentContext(): MLContext {
     const mlContext = this.getMLContext(this.currentSessionId);
     if (!mlContext) {
@@ -97,6 +163,10 @@ export class WebNNBackend {
     sessionIds.delete(sessionId);
     if (sessionIds.size === 0) {
       this.sessionIdsByMLContext.delete(mlContext);
+      const mlContextIndex = this.mlContextCache.findIndex((entry) => entry.mlContext === mlContext);
+      if (mlContextIndex !== -1) {
+        this.mlContextCache.splice(mlContextIndex, 1);
+      }
     }
   }
 

js/web/lib/wasm/wasm-core-impl.ts

@@ -301,12 +301,12 @@ export const createSession = async (
           if (context) {
             wasm.currentContext = context as MLContext;
           } else if (gpuDevice) {
-            wasm.currentContext = await navigator.ml.createContext(gpuDevice);
+            wasm.currentContext = await wasm.jsepCreateMLContext!(gpuDevice);
           } else {
-            wasm.currentContext = await navigator.ml.createContext({ deviceType, powerPreference });
+            wasm.currentContext = await wasm.jsepCreateMLContext!({ deviceType, powerPreference });
           }
         } else {
-          wasm.currentContext = await navigator.ml.createContext();
+          wasm.currentContext = await wasm.jsepCreateMLContext!();
         }
         break;
       }

js/web/lib/wasm/wasm-types.ts

@@ -219,6 +219,13 @@ export declare namespace JSEP {
      * @returns the MLTensor ID for the external MLTensor.
      */
     jsepRegisterMLTensor: (tensor: MLTensor, onnxDataType: DataType, dimensions: readonly number[]) => number;
+
+    /**
+     * [exported from pre-jsep.js] Create an MLContext from a GPUDevice or MLContextOptions.
+     * @param optionsOrGpuDevice - specify the options or GPUDevice.
+     * @returns
+     */
+    jsepCreateMLContext(optionsOrGpuDevice?: MLContextOptions | GPUDevice): Promise<MLContext>;
   }
 }
 

onnxruntime/wasm/pre-jsep.js

@@ -234,6 +234,9 @@ Module['jsepInit'] = (name, params) => {
     }
     Module['jsepRegisterMLTensor'] = (tensor, dataType, shape) => {
       return backend['registerMLTensor'](tensor, dataType, shape);
-    }
+    };
+    Module['jsepCreateMLContext'] = (optionsOrGpuDevice) => {
+      return backend['createMLContext'](optionsOrGpuDevice);
+    };
   }
 };