[webgpu] Check if runtime support WebGPU before initial a WebGPU backend (#5218)

Author: haoyunfeix

tfjs-backend-webgpu/src/backend_webgpu.ts

@@ -73,9 +73,6 @@ export interface WebGPUTimingInfo extends TimingInfo {
 const CPU_HANDOFF_SIZE_THRESHOLD =
     env().getNumber('CPU_HANDOFF_SIZE_THRESHOLD');
 
-const DEFAULT_GPUBUFFER_USAGE =
-    GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC | GPUBufferUsage.COPY_DST;
-
 export class WebGPUBackend extends KernelBackend {
   device: GPUDevice;
   queue: GPUQueue;
@@ -109,6 +106,9 @@ export class WebGPUBackend extends KernelBackend {
 
   constructor(device: GPUDevice, glslang: Glslang, supportTimeQuery = false) {
     super();
+    if (!webgpu_util.isWebGPUSupported()) {
+      throw new Error('WebGPU is not supported on this device');
+    }
     this.layoutCache = {};
     this.pipelineCache = {};
     this.device = device;
@@ -133,6 +133,11 @@ export class WebGPUBackend extends KernelBackend {
     return 32;
   }
 
+  defaultGpuBufferUsage(): number {
+    return GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC |
+        GPUBufferUsage.COPY_DST;
+  }
+
   flushDisposalQueue() {
     this.tensorDisposalQueue.forEach(d => {
       this.maybeReleaseBuffer(d);
@@ -191,7 +196,8 @@ export class WebGPUBackend extends KernelBackend {
   }
 
   acquireBuffer(
-      byteSize: number, usage: GPUBufferUsageFlags = DEFAULT_GPUBUFFER_USAGE) {
+      byteSize: number,
+      usage: GPUBufferUsageFlags = this.defaultGpuBufferUsage()) {
     return this.bufferManager.acquireBuffer(byteSize, usage);
   }
 
@@ -248,7 +254,7 @@ export class WebGPUBackend extends KernelBackend {
     this.tensorMap.set(dataId, {
       dtype,
       values,
-      bufferInfo: {byteSize, usage: DEFAULT_GPUBUFFER_USAGE},
+      bufferInfo: {byteSize, usage: this.defaultGpuBufferUsage()},
       refCount: 1
     });
     return dataId;
@@ -268,7 +274,7 @@ export class WebGPUBackend extends KernelBackend {
     this.tensorMap.set(dataId, {
       dtype,
       values,
-      bufferInfo: {byteSize, usage: DEFAULT_GPUBUFFER_USAGE},
+      bufferInfo: {byteSize, usage: this.defaultGpuBufferUsage()},
       refCount
     });
   }

tfjs-backend-webgpu/src/index.ts

@@ -18,40 +18,42 @@
 import './flags_webgpu';
 import './register_all_kernels';
 
-import {env, registerBackend} from '@tensorflow/tfjs-core';
+import {device_util, env, registerBackend} from '@tensorflow/tfjs-core';
 import glslangInit from '@webgpu/glslang/dist/web-devel/glslang.onefile';
 
 import {WebGPUBackend} from './backend_webgpu';
 import * as webgpu from './webgpu';
-
-registerBackend('webgpu', async () => {
-  // Remove it once we figure out how to correctly read the tensor data before
-  // the tensor is disposed in profiling mode.
-  env().set('CHECK_COMPUTATION_FOR_ERRORS', false);
-
-  const glslang = await glslangInit();
-  const gpuDescriptor: GPURequestAdapterOptions = {
-    powerPreference: env().get('WEBGPU_USE_LOW_POWER_GPU') ? 'low-power' :
-                                                             'high-performance'
-  };
-
-  const adapter = await navigator.gpu.requestAdapter(gpuDescriptor);
-  let deviceDescriptor: GPUDeviceDescriptor = {};
-  const supportTimeQuery = adapter.features.has('timestamp-query');
-
-  if (supportTimeQuery) {
-    deviceDescriptor = {
-      nonGuaranteedFeatures: ['timestamp-query' as const]
+import {isWebGPUSupported} from './webgpu_util';
+
+if (device_util.isBrowser() && isWebGPUSupported()) {
+  registerBackend('webgpu', async () => {
+    // Remove it once we figure out how to correctly read the tensor data
+    // before the tensor is disposed in profiling mode.
+    env().set('CHECK_COMPUTATION_FOR_ERRORS', false);
+
+    const glslang = await glslangInit();
+    const gpuDescriptor: GPURequestAdapterOptions = {
+      powerPreference: env().get('WEBGPU_USE_LOW_POWER_GPU') ?
+          'low-power' :
+          'high-performance'
     };
-  } else {
-    console.warn(
-        `This device doesn't support timestamp-query extension. ` +
-        `Zero will shown for the kernel time when profiling mode is enabled. ` +
-        `Using performance.now is not workable for webgpu since it doesn't ` +
-        `support synchronously to read data from GPU.`);
-  }
-  const device: GPUDevice = await adapter.requestDevice(deviceDescriptor);
-  return new WebGPUBackend(device, glslang, supportTimeQuery);
-}, 3 /*priority*/);
+
+    const adapter = await navigator.gpu.requestAdapter(gpuDescriptor);
+    let deviceDescriptor: GPUDeviceDescriptor = {};
+    const supportTimeQuery = adapter.features.has('timestamp-query');
+
+    if (supportTimeQuery) {
+      deviceDescriptor = {nonGuaranteedFeatures: ['timestamp-query' as const ]};
+    } else {
+      console.warn(
+          `This device doesn't support timestamp-query extension. ` +
+          `Zero will shown for the kernel time when profiling mode is` +
+          `enabled. Using performance.now is not workable for webgpu since` +
+          `it doesn't support synchronously to read data from GPU.`);
+    }
+    const device: GPUDevice = await adapter.requestDevice(deviceDescriptor);
+    return new WebGPUBackend(device, glslang, supportTimeQuery);
+  }, 3 /*priority*/);
+}
 
 export {webgpu};

tfjs-backend-webgpu/src/webgpu_util.ts

@@ -152,3 +152,10 @@ export function ArrayBufferToTypedArray(data: ArrayBuffer, dtype: DataType) {
     throw new Error(`Unknown dtype ${dtype}`);
   }
 }
+
+export function isWebGPUSupported(): boolean {
+  if (!navigator.gpu) {
+    return false;
+  }
+  return true;
+}