Remove Wasm and WebGL backends (WebNN-Polyfill)

README.md

@@ -95,8 +95,7 @@ We welcome contributions from the community to make webnn-samples even better! I
 ### WebNN Resources
 To learn more about Web Neural Network API (WebNN) and its capabilities, check out the following resources:
 * [Web Neural Network API Specification](https://webmachinelearning.github.io/webnn/)
-* [WebNN Polyfill](https://github.com/webmachinelearning/webnn-polyfill)
-* [WebNN Community Group](https://webmachinelearning.github.io/)
+* [W3C WebML Working Group and Community Group](https://webmachinelearning.github.io/)
 
 ### WebNN API Samples
 * [WebNN code editor](https://webmachinelearning.github.io/webnn-samples/code/)

code/index.html

@@ -70,7 +70,7 @@
     <script src="./libs/codemirror/codemirror.js"></script>
     <script src="./libs/codemirror/javascript.js"></script>
     <script src="./libs/codemirror/sublime.js"></script>
-    <script src="https://webmachinelearning.github.io/webnn-polyfill/dist/webnn-polyfill.js" crossorigin="anonymous"></script>
+    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs/dist/tf.min.js"></script>
     <script type="module">
       import {main} from './main.js';
       window.onload = async () => {

code/main.js

@@ -1,14 +1,14 @@
 import {samplesRepo} from './samples_repo.js';
 import * as utils from '../common/utils.js';
+import {addAlert} from '../common/ui.js';
 
 window.sizeOfShape = utils.sizeOfShape;
 
 export async function main() {
   // Set backend
-  if (await utils.isWebNN()) {
-    await utils.setBackend('webnn', 'cpu');
-  } else {
-    await utils.setBackend('polyfill', 'cpu');
+  if (!await utils.isWebNN()) {
+    console.log(utils.webNNNotSupportMessage());
+    addAlert(utils.webNNNotSupportMessageHTML());
   }
   const selectElement = document.getElementById('example-select');
   for (const name of samplesRepo.names()) {

common/component/component.js

@@ -599,13 +599,6 @@ $(document).ready(async () => {
   $("#footer").html(footer());
   if (await isWebNN()) {
     if ($("#backendBtns")) {
-      $('label[name="polyfill"]').addClass("disabled");
-      $('label[name="polyfill"]').addClass("btn-outline-secondary");
-      $('label[name="polyfill"]').removeClass("btn-outline-info");
-      $('label[name="polyfill"]').attr(
-        "title",
-        "WebNN is supported, disable WebNN Polyfill."
-      );
       // Disable WebNN NPU backend if failed to find a capable NPU adapter.
       try {
         await navigator.ml.createContext({deviceType: 'npu'});

common/utils.js

@@ -269,48 +269,6 @@ export function getMedianValue(array) {
       (array[array.length / 2 - 1] + array[array.length / 2]) / 2;
 }
 
-// Set tf.js backend based WebNN's 'MLDeviceType' option
-export async function setPolyfillBackend(device) {
-  // Simulate WebNN's device selection using various tf.js backends.
-  // MLDeviceType: ['default', 'gpu', 'cpu']
-  // 'default' or 'gpu': tfjs-backend-webgl, 'cpu': tfjs-backend-wasm
-  if (!device) device = 'gpu';
-  // Use 'webgl' by default for better performance.
-  // Note: 'wasm' backend may run failed on some samples since
-  // some ops aren't supported on 'wasm' backend at present
-  const backend = device === 'cpu' ? 'wasm' : 'webgl';
-  const context = await navigator.ml.createContext();
-  const tf = context.tf;
-  if (tf) {
-    if (backend == 'wasm') {
-      const wasm = context.wasm;
-      // Force to use Wasm SIMD only
-      wasm.setWasmPath(`https://unpkg.com/@tensorflow/tfjs-backend-wasm@${tf.version_core}/dist/tfjs-backend-wasm-simd.wasm`);
-    }
-    if (!(await tf.setBackend(backend))) {
-      throw new Error(`Failed to set tf.js backend ${backend}.`);
-    }
-    await tf.ready();
-    let backendInfo = backend == 'wasm' ? 'WASM' : 'WebGL';
-    if (backendInfo == 'WASM') {
-      const hasSimd = tf.env().features['WASM_HAS_SIMD_SUPPORT'];
-      const hasThreads = tf.env().features['WASM_HAS_MULTITHREAD_SUPPORT'];
-      if (hasThreads && hasSimd) {
-        backendInfo += ' (SIMD + threads)';
-      } else if (hasThreads && !hasSimd) {
-        backendInfo += ' (threads)';
-      } else if (!hasThreads && hasSimd) {
-        backendInfo += ' (SIMD)';
-      }
-    }
-    addAlert(
-        `This sample is running on ` +
-        `<a href='https://github.com/webmachinelearning/webnn-polyfill'>` +
-        `WebNN-polyfill</a> with tf.js ${tf.version_core} ` +
-        `<b>${backendInfo}</b> backend.`, 'info');
-  }
-}
-
 // Get url params
 export function getUrlParams() {
   const params = new URLSearchParams(location.search);
@@ -346,59 +304,6 @@ export function getUrlParams() {
   return [numRuns, powerPreference, numThreads];
 }
 
-// Set backend for using WebNN-polyfill or WebNN
-export async function setBackend(backend, device) {
-  const webnnPolyfillId = 'webnn_polyfill';
-  const webnnNodeId = 'webnn_node';
-  const webnnPolyfillElem = document.getElementById(webnnPolyfillId);
-  const webnnNodeElem = document.getElementById(webnnNodeId);
-
-  if (backend === 'polyfill') {
-    if (webnnNodeElem) {
-      document.body.removeChild(webnnNodeElem);
-      // Unset global objects defined in node_setup.js
-      global.navigator.ml = undefined;
-      global.MLContext = undefined;
-      global.MLGraphBuilder = undefined;
-      global.MLGraph = undefined;
-      global.MLOperand = undefined;
-    }
-    if (!webnnPolyfillElem) {
-      const webnnPolyfillUrl =
-          'https://webmachinelearning.github.io/webnn-polyfill/dist/webnn-polyfill.js';
-      if (typeof(tf) != 'undefined') {
-        // Reset tf.ENV to avoid environments from tf.min.js
-        // affect webnn-polyfill.js
-        tf.engine().reset();
-      }
-      // Create WebNN-polyfill script
-      await loadScript(webnnPolyfillUrl, webnnPolyfillId);
-    }
-    await setPolyfillBackend(device);
-  } else if (backend === 'webnn') {
-    if (!await isWebNN()) {
-      addAlert(`WebNN is not supported!`, 'warning');
-    }
-  } else {
-    addAlert(`Unknow backend: ${backend}`, 'warning');
-  }
-}
-
-// Promise to load script with url and id
-async function loadScript(url, id) {
-  return new Promise((resolve, reject) => {
-    const script = document.createElement('script');
-    script.onload = resolve;
-    script.onerror = reject;
-    script.src = url;
-    script.id = id;
-    if (url.startsWith('http')) {
-      script.crossOrigin = 'anonymous';
-    }
-    document.body.appendChild(script);
-  });
-}
-
 export async function isWebNN() {
   if (typeof MLGraphBuilder !== 'undefined') {
     const context = await navigator.ml.createContext();
@@ -408,6 +313,14 @@ export async function isWebNN() {
   }
 }
 
+export function webNNNotSupportMessage() {
+  return 'Your browser does not support WebNN.';
+}
+
+export function webNNNotSupportMessageHTML() {
+  return 'Your browser does not support WebNN. Please refer to <a href="https://github.com/webmachinelearning/webnn-samples/#webnn-installation-guides">WebNN Installation Guides</a> for more details.';
+}
+
 // Derive from
 // https://github.com/webmachinelearning/webnn-baseline/blob/main/src/lib/compute-padding.js
 /**

face_recognition/facenet_nchw.js

@@ -276,14 +276,6 @@ export class FaceNetNchw {
     this.graph_ = await this.builder_.build({'output': outputOperand});
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

face_recognition/facenet_nhwc.js

@@ -245,14 +245,6 @@ export class FaceNetNhwc {
     this.graph_ = await this.builder_.build({'output': outputOperand});
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

face_recognition/index.html

@@ -31,12 +31,6 @@
           </div>
           <div class="col-md-auto">
             <div class="btn-group-toggle" data-toggle="buttons" id="backendBtns">
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_cpu" autocomplete="off">Wasm (CPU)
-              </label>
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_gpu" autocomplete="off">WebGL (GPU)
-              </label>
               <label class="btn btn-outline-info custom" name="webnn">
                 <input type="radio" name="backend" id="webnn_cpu" autocomplete="off">WebNN (CPU)
               </label>

face_recognition/main.js

@@ -45,7 +45,8 @@ $(document).ready(async () => {
   if (await utils.isWebNN()) {
     $('#webnn_cpu').click();
   } else {
-    $('#polyfill_cpu').click();
+    console.log(utils.webNNNotSupportMessage());
+    ui.addAlert(utils.webNNNotSupportMessageHTML());
   }
 });
 
@@ -307,19 +308,10 @@ async function main() {
         lastdeviceType != deviceType || lastBackend != backend) {
       if (lastdeviceType != deviceType || lastBackend != backend) {
         // Set backend and device
-        await utils.setBackend(backend, deviceType);
         lastdeviceType = lastdeviceType != deviceType ?
                                deviceType : lastdeviceType;
         lastBackend = lastBackend != backend ? backend : lastBackend;
       }
-      if (frInstance !== null) {
-        // Call dispose() to and avoid memory leak
-        frInstance.dispose();
-      }
-      if (fdInstance !== null) {
-        // Call dispose() to and avoid memory leak
-        fdInstance.dispose();
-      }
       fdInstanceType = fdModelName + layout;
       frInstanceType = frModelName + layout;
       fdInstance = constructNetObject(fdInstanceType);

facial_landmark_detection/face_landmark_nchw.js

@@ -116,14 +116,6 @@ export class FaceLandmarkNchw {
     this.graph_ = await this.builder_.build({'output': outputOperand});
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

facial_landmark_detection/face_landmark_nhwc.js

@@ -119,14 +119,6 @@ export class FaceLandmarkNhwc {
     this.graph_ = await this.builder_.build({'output': outputOperand});
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

facial_landmark_detection/index.html

@@ -31,12 +31,6 @@
           </div>
           <div class="col-md-auto">
             <div class="btn-group-toggle" data-toggle="buttons" id="backendBtns">
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_cpu" autocomplete="off">Wasm (CPU)
-              </label>
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_gpu" autocomplete="off">WebGL (GPU)
-              </label>
               <label class="btn btn-outline-info custom" name="webnn">
                 <input type="radio" name="backend" id="webnn_cpu" autocomplete="off">WebNN (CPU)
               </label>

facial_landmark_detection/main.js

@@ -41,7 +41,8 @@ $(document).ready(async () => {
   if (await utils.isWebNN()) {
     $('#webnn_cpu').click();
   } else {
-    $('#polyfill_cpu').click();
+    console.log(utils.webNNNotSupportMessage());
+    ui.addAlert(utils.webNNNotSupportMessageHTML());
   }
 });
 
@@ -243,19 +244,10 @@ async function main() {
         lastdeviceType != deviceType || lastBackend != backend) {
       if (lastdeviceType != deviceType || lastBackend != backend) {
         // Set backend and device
-        await utils.setBackend(backend, deviceType);
         lastdeviceType = lastdeviceType != deviceType ?
                                deviceType : lastdeviceType;
         lastBackend = lastBackend != backend ? backend : lastBackend;
       }
-      if (fldInstance !== null) {
-        // Call dispose() to and avoid memory leak
-        fldInstance.dispose();
-      }
-      if (fdInstance !== null) {
-        // Call dispose() to and avoid memory leak
-        fdInstance.dispose();
-      }
       fdInstanceType = fdModelName + layout;
       fldInstanceType = fldModelName + layout;
       fdInstance = constructNetObject(fdInstanceType);

facial_landmark_detection/ssd_mobilenetv2_face_nchw.js

@@ -243,14 +243,6 @@ ${nameArray[1]}`;
     this.graph_ = await this.builder_.build(outputOperand);
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

facial_landmark_detection/ssd_mobilenetv2_face_nhwc.js

@@ -255,14 +255,6 @@ ${nameArray[1]}`;
     this.graph_ = await this.builder_.build(outputOperand);
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

image_classification/efficientnet_fp16_nchw.js

@@ -168,14 +168,6 @@ export class EfficientNetFP16Nchw {
     this.graph_ = await this.builder_.build({'output': outputOperand});
   }
 
-  // Release the constant tensors of a model
-  dispose() {
-    // dispose() is only available in webnn-polyfill
-    if (this.graph_ !== null && 'dispose' in this.graph_) {
-      this.graph_.dispose();
-    }
-  }
-
   async compute(inputBuffer) {
     this.context_.writeTensor(this.inputTensor_, inputBuffer);
     const inputs = {'input': this.inputTensor_};

image_classification/index.html

@@ -31,12 +31,6 @@
           </div>
           <div class="col-md-auto">
             <div class="btn-group-toggle" data-toggle="buttons" id="backendBtns">
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_cpu" autocomplete="off">Wasm (CPU)
-              </label>
-              <label class="btn btn-outline-info custom" name="polyfill">
-                <input type="radio" name="backend" id="polyfill_gpu" autocomplete="off">WebGL (GPU)
-              </label>
               <label class="btn btn-outline-info custom" name="webnn">
                 <input type="radio" name="backend" id="webnn_cpu" autocomplete="off">WebNN (CPU)
               </label>