Replace devicePreference as deviceType (#185)

As the implementation will soon support the MLDeviceType enum.
webmachinelearning · Nov 2, 2023 · b138e20 · b138e20
1 parent 0b4b3c3
commit b138e20
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Showing 17 changed files with 33 additions and 33 deletions.
diff --git a/face_recognition/main.js b/face_recognition/main.js
@@ -317,7 +317,7 @@ async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/facial_landmark_detection/main.js b/facial_landmark_detection/main.js
@@ -252,7 +252,7 @@ async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/facial_landmark_detection/ssd_mobilenetv2_face_nchw.js b/facial_landmark_detection/ssd_mobilenetv2_face_nchw.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class SsdMobilenetV2FaceNchw {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/ssd_mobilenetv2_face_nchw/weights/';
@@ -78,7 +78,7 @@ ${nameArray[1]}`;
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -119,7 +119,7 @@ ${nameArray[1]}`;
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const input = this.builder_.input('input',
         {type: 'float32', dimensions: this.inputOptions.inputDimensions});

diff --git a/facial_landmark_detection/ssd_mobilenetv2_face_nhwc.js b/facial_landmark_detection/ssd_mobilenetv2_face_nhwc.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class SsdMobilenetV2FaceNhwc {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/ssd_mobilenetv2_face_nhwc/weights/';
@@ -85,7 +85,7 @@ ${nameArray[1]}`;
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -126,7 +126,7 @@ ${nameArray[1]}`;
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const input = this.builder_.input('input',
         {type: 'float32', dimensions: this.inputOptions.inputDimensions});

diff --git a/image_classification/main.js b/image_classification/main.js
@@ -238,7 +238,7 @@ async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/image_classification/mobilenet_nchw.js b/image_classification/mobilenet_nchw.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class MobileNetV2Nchw {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/mobilenetv2_nchw/weights/';
@@ -34,7 +34,7 @@ export class MobileNetV2Nchw {
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -76,7 +76,7 @@ export class MobileNetV2Nchw {
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const data = this.builder_.input('input',
         {type: 'float32', dimensions: this.inputOptions.inputDimensions});

diff --git a/image_classification/mobilenet_nhwc.js b/image_classification/mobilenet_nhwc.js
@@ -8,7 +8,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class MobileNetV2Nhwc {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/mobilenetv2_nhwc/weights/';
@@ -33,7 +33,7 @@ export class MobileNetV2Nhwc {
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -66,7 +66,7 @@ export class MobileNetV2Nhwc {
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const strides = [2, 2];
     const autoPad = 'same-upper';

diff --git a/lenet/main.js b/lenet/main.js
@@ -68,7 +68,7 @@ async function main() {
   const lenet = new LeNet(weightUrl);
   const [numRuns, powerPreference, numThreads] = utils.getUrlParams();
   try {
-    const contextOptions = {'devicePreference': deviceType};
+    const contextOptions = {deviceType};
     if (powerPreference) {
       contextOptions['powerPreference'] = powerPreference;
     }

diff --git a/nsnet2/denoiser.js b/nsnet2/denoiser.js
@@ -31,7 +31,7 @@ export class Denoiser {
       const start = performance.now();
       const weightsUrl = '../test-data/models/nsnet2/weights/';
       const powerPreference = getUrlParams()[1];
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/object_detection/main.js b/object_detection/main.js
@@ -219,7 +219,7 @@ async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/object_detection/ssd_mobilenetv1_nchw.js b/object_detection/ssd_mobilenetv1_nchw.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class SsdMobilenetV1Nchw {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.model_ = null;
     this.builder_ = null;
     this.graph_ = null;
@@ -64,7 +64,7 @@ ${nameArray[1]}_BatchNorm_batchnorm`;
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -77,7 +77,7 @@ ${nameArray[1]}_BatchNorm_batchnorm`;
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const input = this.builder_.input('input',
         {type: 'float32', dimensions: this.inputOptions.inputDimensions});

diff --git a/object_detection/ssd_mobilenetv1_nhwc.js b/object_detection/ssd_mobilenetv1_nhwc.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class SsdMobilenetV1Nhwc {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.model_ = null;
     this.builder_ = null;
     this.graph_ = null;
@@ -75,7 +75,7 @@ ${nameArray[1]}_BatchNorm_batchnorm`;
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -88,7 +88,7 @@ ${nameArray[1]}_BatchNorm_batchnorm`;
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const input = this.builder_.input('input',
         {type: 'float32', dimensions: this.inputOptions.inputDimensions});

diff --git a/rnnoise/main.js b/rnnoise/main.js
@@ -220,7 +220,7 @@ export async function main() {
       `[${batchSize} (batch_size) x 100 (frames) x 42].`, true);
     await log(modelInfo, '- Loading model...');
     const powerPreference = utils.getUrlParams()[1];
-    const contextOptions = {'devicePreference': deviceType};
+    const contextOptions = {deviceType};
     if (powerPreference) {
       contextOptions['powerPreference'] = powerPreference;
     }

diff --git a/semantic_segmentation/deeplabv3_mnv2_nchw.js b/semantic_segmentation/deeplabv3_mnv2_nchw.js
@@ -8,7 +8,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class DeepLabV3MNV2Nchw {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/deeplabv3_mnv2_nchw/weights/';
@@ -47,7 +47,7 @@ export class DeepLabV3MNV2Nchw {
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -91,7 +91,7 @@ export class DeepLabV3MNV2Nchw {
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const strides = [2, 2];
 

diff --git a/semantic_segmentation/deeplabv3_mnv2_nhwc.js b/semantic_segmentation/deeplabv3_mnv2_nhwc.js
@@ -6,7 +6,7 @@ import {buildConstantByNpy} from '../common/utils.js';
 export class DeepLabV3MNV2Nhwc {
   constructor() {
     this.context_ = null;
-    this.devicePreference_ = null;
+    this.deviceType_ = null;
     this.builder_ = null;
     this.graph_ = null;
     this.weightsUrl_ = '../test-data/models/deeplabv3_mnv2_nhwc/weights/';
@@ -47,7 +47,7 @@ export class DeepLabV3MNV2Nhwc {
       // TODO: Set clamp activation to options once it's supported in
       // WebNN DML backend.
       // Implement `clip` by `clamp` of  WebNN API
-      if (this.devicePreference_ == 'gpu') {
+      if (this.deviceType_ == 'gpu') {
         return this.builder_.clamp(
             this.builder_.conv2d(input, weights, options),
             {minValue: 0, maxValue: 6});
@@ -80,7 +80,7 @@ export class DeepLabV3MNV2Nhwc {
 
   async load(contextOptions) {
     this.context_ = await navigator.ml.createContext(contextOptions);
-    this.devicePreference_ = contextOptions.devicePreference;
+    this.deviceType_ = contextOptions.deviceType;
     this.builder_ = new MLGraphBuilder(this.context_);
     const strides = [2, 2];
     const input = this.builder_.input('input',

diff --git a/semantic_segmentation/main.js b/semantic_segmentation/main.js
@@ -331,7 +331,7 @@ export async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }

diff --git a/style_transfer/main.js b/style_transfer/main.js
@@ -217,7 +217,7 @@ export async function main() {
       // UI shows model loading progress
       await ui.showProgressComponent('current', 'pending', 'pending');
       console.log('- Loading weights... ');
-      const contextOptions = {'devicePreference': deviceType};
+      const contextOptions = {deviceType};
       if (powerPreference) {
         contextOptions['powerPreference'] = powerPreference;
       }