2021-08-31 17:23:42 +00:00
|
|
|
// Copyright (c) Microsoft Corporation. All rights reserved.
|
|
|
|
|
// Licensed under the MIT License.
|
|
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
import {env, InferenceSession} from 'onnxruntime-common';
|
2022-05-04 06:41:36 +00:00
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
import {OrtWasmMessage, SerializableInternalBuffer, SerializableSessionMetadata, SerializableTensorMetadata, TensorMetadata} from './proxy-messages';
|
2021-08-31 17:23:42 +00:00
|
|
|
import * as core from './wasm-core-impl';
|
2023-05-15 23:23:13 +00:00
|
|
|
import {initializeWebAssembly} from './wasm-factory';
|
2021-08-31 17:23:42 +00:00
|
|
|
|
|
|
|
|
const isProxy = (): boolean => !!env.wasm.proxy && typeof document !== 'undefined';
|
|
|
|
|
let proxyWorker: Worker|undefined;
|
|
|
|
|
let initializing = false;
|
|
|
|
|
let initialized = false;
|
|
|
|
|
let aborted = false;
|
|
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
type PromiseCallbacks<T = void> = [resolve: (result: T) => void, reject: (reason: unknown) => void];
|
2021-08-31 17:23:42 +00:00
|
|
|
let initWasmCallbacks: PromiseCallbacks;
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
const queuedCallbacks: Map<OrtWasmMessage['type'], Array<PromiseCallbacks<unknown>>> = new Map();
|
|
|
|
|
|
|
|
|
|
const enqueueCallbacks = (type: OrtWasmMessage['type'], callbacks: PromiseCallbacks<unknown>): void => {
|
|
|
|
|
const queue = queuedCallbacks.get(type);
|
|
|
|
|
if (queue) {
|
|
|
|
|
queue.push(callbacks);
|
|
|
|
|
} else {
|
|
|
|
|
queuedCallbacks.set(type, [callbacks]);
|
|
|
|
|
}
|
|
|
|
|
};
|
2021-08-31 17:23:42 +00:00
|
|
|
|
|
|
|
|
const ensureWorker = (): void => {
|
|
|
|
|
if (initializing || !initialized || aborted || !proxyWorker) {
|
|
|
|
|
throw new Error('worker not ready');
|
|
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
const onProxyWorkerMessage = (ev: MessageEvent<OrtWasmMessage>): void => {
|
|
|
|
|
switch (ev.data.type) {
|
|
|
|
|
case 'init-wasm':
|
|
|
|
|
initializing = false;
|
|
|
|
|
if (ev.data.err) {
|
|
|
|
|
aborted = true;
|
|
|
|
|
initWasmCallbacks[1](ev.data.err);
|
|
|
|
|
} else {
|
|
|
|
|
initialized = true;
|
|
|
|
|
initWasmCallbacks[0]();
|
|
|
|
|
}
|
|
|
|
|
break;
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
case 'init-ep':
|
|
|
|
|
case 'copy-from':
|
2021-08-31 17:23:42 +00:00
|
|
|
case 'create':
|
|
|
|
|
case 'release':
|
|
|
|
|
case 'run':
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
case 'end-profiling': {
|
|
|
|
|
const callbacks = queuedCallbacks.get(ev.data.type)!;
|
2021-08-31 17:23:42 +00:00
|
|
|
if (ev.data.err) {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
callbacks.shift();
|
2023-10-26 16:22:10 +00:00
|
|
|
} else {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
callbacks.shift();
|
2023-10-26 16:22:10 +00:00
|
|
|
}
|
|
|
|
|
break;
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
}
|
2021-08-31 17:23:42 +00:00
|
|
|
default:
|
|
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
2021-09-14 17:38:58 +00:00
|
|
|
const scriptSrc = typeof document !== 'undefined' ? (document?.currentScript as HTMLScriptElement)?.src : undefined;
|
2021-08-31 17:23:42 +00:00
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
export const initializeWebAssemblyAndOrtRuntime = async(): Promise<void> => {
|
|
|
|
|
if (initialized) {
|
|
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
if (initializing) {
|
|
|
|
|
throw new Error('multiple calls to \'initWasm()\' detected.');
|
|
|
|
|
}
|
|
|
|
|
if (aborted) {
|
|
|
|
|
throw new Error('previous call to \'initWasm()\' failed.');
|
|
|
|
|
}
|
2021-08-31 17:23:42 +00:00
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
initializing = true;
|
2021-08-31 17:23:42 +00:00
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
2021-08-31 17:23:42 +00:00
|
|
|
// overwrite wasm filepaths
|
|
|
|
|
if (env.wasm.wasmPaths === undefined) {
|
|
|
|
|
if (scriptSrc && scriptSrc.indexOf('blob:') !== 0) {
|
2023-01-12 17:05:18 +00:00
|
|
|
env.wasm.wasmPaths = scriptSrc.substr(0, +(scriptSrc).lastIndexOf('/') + 1);
|
2021-08-31 17:23:42 +00:00
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
return new Promise<void>((resolve, reject) => {
|
|
|
|
|
proxyWorker?.terminate();
|
2023-10-06 20:37:37 +00:00
|
|
|
|
|
|
|
|
const workerUrl = URL.createObjectURL(new Blob(
|
|
|
|
|
[
|
|
|
|
|
// This require() function is handled by esbuild plugin to load file content as string.
|
|
|
|
|
// eslint-disable-next-line @typescript-eslint/no-require-imports
|
|
|
|
|
require('./proxy-worker/main')
|
|
|
|
|
],
|
|
|
|
|
{type: 'text/javascript'}));
|
|
|
|
|
proxyWorker = new Worker(workerUrl, {name: 'ort-wasm-proxy-worker'});
|
|
|
|
|
proxyWorker.onerror = (ev: ErrorEvent) => reject(ev);
|
2021-08-31 17:23:42 +00:00
|
|
|
proxyWorker.onmessage = onProxyWorkerMessage;
|
2023-10-06 20:37:37 +00:00
|
|
|
URL.revokeObjectURL(workerUrl);
|
2021-08-31 17:23:42 +00:00
|
|
|
initWasmCallbacks = [resolve, reject];
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
const message: OrtWasmMessage = {type: 'init-wasm', in : env};
|
2021-08-31 17:23:42 +00:00
|
|
|
proxyWorker.postMessage(message);
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
} else {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
try {
|
|
|
|
|
await initializeWebAssembly(env.wasm);
|
|
|
|
|
await core.initRuntime(env);
|
|
|
|
|
initialized = true;
|
|
|
|
|
} catch (e) {
|
|
|
|
|
aborted = true;
|
|
|
|
|
throw e;
|
|
|
|
|
} finally {
|
|
|
|
|
initializing = false;
|
|
|
|
|
}
|
2021-08-31 17:23:42 +00:00
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
export const initializeOrtEp = async(epName: string): Promise<void> => {
|
2021-11-22 21:56:55 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
2021-08-31 17:23:42 +00:00
|
|
|
ensureWorker();
|
|
|
|
|
return new Promise<void>((resolve, reject) => {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
enqueueCallbacks('init-ep', [resolve, reject]);
|
|
|
|
|
const message: OrtWasmMessage = {type: 'init-ep', in : {epName, env}};
|
2021-08-31 17:23:42 +00:00
|
|
|
proxyWorker!.postMessage(message);
|
|
|
|
|
});
|
|
|
|
|
} else {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
await core.initEp(env, epName);
|
2021-08-31 17:23:42 +00:00
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
export const copyFromExternalBuffer = async(buffer: Uint8Array): Promise<SerializableInternalBuffer> => {
|
2022-11-14 20:18:02 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
|
|
|
|
ensureWorker();
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
return new Promise<SerializableInternalBuffer>((resolve, reject) => {
|
|
|
|
|
enqueueCallbacks('copy-from', [resolve, reject]);
|
|
|
|
|
const message: OrtWasmMessage = {type: 'copy-from', in : {buffer}};
|
|
|
|
|
proxyWorker!.postMessage(message, [buffer.buffer]);
|
2022-11-14 20:18:02 +00:00
|
|
|
});
|
|
|
|
|
} else {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
return core.copyFromExternalBuffer(buffer);
|
2022-11-14 20:18:02 +00:00
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
2021-08-31 17:23:42 +00:00
|
|
|
export const createSession =
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
async(model: SerializableInternalBuffer|Uint8Array, options?: InferenceSession.SessionOptions):
|
|
|
|
|
Promise<SerializableSessionMetadata> => {
|
|
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
|
|
|
|
// check unsupported options
|
|
|
|
|
if (options?.preferredOutputLocation) {
|
|
|
|
|
throw new Error('session option "preferredOutputLocation" is not supported for proxy.');
|
|
|
|
|
}
|
|
|
|
|
ensureWorker();
|
|
|
|
|
return new Promise<SerializableSessionMetadata>((resolve, reject) => {
|
|
|
|
|
enqueueCallbacks('create', [resolve, reject]);
|
|
|
|
|
const message: OrtWasmMessage = {type: 'create', in : {model, options}};
|
|
|
|
|
const transferable: Transferable[] = [];
|
|
|
|
|
if (model instanceof Uint8Array) {
|
|
|
|
|
transferable.push(model.buffer);
|
|
|
|
|
}
|
|
|
|
|
proxyWorker!.postMessage(message, transferable);
|
|
|
|
|
});
|
|
|
|
|
} else {
|
|
|
|
|
return core.createSession(model, options);
|
|
|
|
|
}
|
|
|
|
|
};
|
2021-08-31 17:23:42 +00:00
|
|
|
|
|
|
|
|
export const releaseSession = async(sessionId: number): Promise<void> => {
|
2021-11-22 21:56:55 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
2021-08-31 17:23:42 +00:00
|
|
|
ensureWorker();
|
|
|
|
|
return new Promise<void>((resolve, reject) => {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
enqueueCallbacks('release', [resolve, reject]);
|
2021-08-31 17:23:42 +00:00
|
|
|
const message: OrtWasmMessage = {type: 'release', in : sessionId};
|
|
|
|
|
proxyWorker!.postMessage(message);
|
|
|
|
|
});
|
|
|
|
|
} else {
|
|
|
|
|
core.releaseSession(sessionId);
|
|
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
export const run = async(
|
[js/webgpu] support IO binding (#17480)
<del>
**This PR is based on a few prerequisites PRs. They are listed as
below:**
- #17465
- #17469
- #17470
- #17472
- #17473
- #17484
Please review the current change by only looking at commit
e2e6623e673ec6de55a5c1f8edcbd3a46b535a89 and later.
</del>
### Description
This PR introduces WebGPU IO binding. This new feature allows
onnxruntime-web users to use tensors created from GPU as model
input/output so that a model inferencing can be done without unnecessary
data copy between CPU and GPU for model input/output.
### Examples
An E2E demo/example is being worked on.
Following is some simple demo with code snippet.
Let's first check today how we do:
```js
// STEP.1 - create an inference session:
const mySession = await ort.InferenceSession.create('./my_model.onnx', { executionProviders: ['webgpu'] });
// STEP.2 - create model input: (supposing myImageCpuData is a Float32Array)
const feeds = {
'input_image:0': new ort.Tensor('float32', myImageCpuData, [1, 224, 224, 3])
};
// STEP.3 - run model
const myResults = await mySession.run(feeds);
// STEP.4 - get output data
const myData = myResults['output_image:0'].data; // Float32Array
```
#### for inputs (GPU tensor):
Now, with IO binding, you can create a tensor from a GPU buffer, and
feed it to the model:
```js
// new STEP.2.A - create model input from a GPU buffer: (supposing myInputGpuBuffer is a `GPUBuffer` object with input data)
const feeds = {
'input_image:0': ort.Tensor.fromGpuBuffer(myInputGpuBuffer, { dataType: 'float32', dims: [1, 224, 224, 3] })
};
```
### for outputs (pre-allocated GPU tensor)
you can also do that for output, **if you know the output shape**:
```js
// new STEP.2.B - create model output from a GPU buffer: (supposing myOutputGpuBuffer is a pre-allocated `GPUBuffer` object)
const fetches = {
'output_image:0': ort.Tensor.fromGpuBuffer(myOutputGpuBuffer, { dataType: 'float32', dims: [1, 512, 512, 3] })
};
// new STEP.3 - run model with pre-allocated output (fetches)
const myResults = await mySession.run(feeds, fetches);
```
### for outputs (specify location)
if you do not know the output shape, you can specify the output location
when creating the session:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: "gpu-buffer"
});
```
if the model has multiple outputs, you can specify them seperately:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: {
"output_image:0": "gpu-buffer"
}
});
```
now you don't need to prepare the `fetches` object and onnxruntime-web
will prepare output data on the location that specified.
#### read data
when you get the output tensor, you can:
```js
// get the gpu buffer object:
const gpuBuffer = myOutputTensor.gpuBuffer; // GPUBuffer
// get the CPU data asynchronizely
const cpuData = await myOutputTensor.getData();
// get the CPU data asynchronizely and release the underlying GPU resources
const cpuData = await myOutputTensor.getData(true);
// dispose the tensor (release the underlying GPU resources). This tensor object will be invalid after dispose() is called.
myOutputTensor.dispose();
```
#### resource management
JavaScript has GC so you don't need to worry about managing JavaScript
objects. But there are 2 types of resources that are not managed by GC:
- GPU buffer that used in tensors
- Underlying ORT native resources
To simplify, most of the unmanaged resources and handled inside ORT web.
But there are a few resources that need users to manage:
- All external GPU resources, including GPU buffers inside all tensors
created by `Tensor.fromGpuBuffer()`, will not be managed by ORT. User
should manage those GPU buffers themselves.
- When a session is created with `preferredOutputLocation` ==
"gpu-buffer" specified in session options, and the corresponding output
is not pre-allocated, user need to call the output tensor's `dispose()`
or `getData(true)` to manually release the underlying GPU buffers.
- ORT internal errors (including providing a pre-allocated output tensor
with wrong type/dims) will invalidate the whole wasm memory and is not
recoverable. An exception is thrown in this situation.
2023-09-29 18:24:42 +00:00
|
|
|
sessionId: number, inputIndices: number[], inputs: TensorMetadata[], outputIndices: number[],
|
|
|
|
|
outputs: Array<TensorMetadata|null>, options: InferenceSession.RunOptions): Promise<TensorMetadata[]> => {
|
2021-11-22 21:56:55 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
[js/webgpu] support IO binding (#17480)
<del>
**This PR is based on a few prerequisites PRs. They are listed as
below:**
- #17465
- #17469
- #17470
- #17472
- #17473
- #17484
Please review the current change by only looking at commit
e2e6623e673ec6de55a5c1f8edcbd3a46b535a89 and later.
</del>
### Description
This PR introduces WebGPU IO binding. This new feature allows
onnxruntime-web users to use tensors created from GPU as model
input/output so that a model inferencing can be done without unnecessary
data copy between CPU and GPU for model input/output.
### Examples
An E2E demo/example is being worked on.
Following is some simple demo with code snippet.
Let's first check today how we do:
```js
// STEP.1 - create an inference session:
const mySession = await ort.InferenceSession.create('./my_model.onnx', { executionProviders: ['webgpu'] });
// STEP.2 - create model input: (supposing myImageCpuData is a Float32Array)
const feeds = {
'input_image:0': new ort.Tensor('float32', myImageCpuData, [1, 224, 224, 3])
};
// STEP.3 - run model
const myResults = await mySession.run(feeds);
// STEP.4 - get output data
const myData = myResults['output_image:0'].data; // Float32Array
```
#### for inputs (GPU tensor):
Now, with IO binding, you can create a tensor from a GPU buffer, and
feed it to the model:
```js
// new STEP.2.A - create model input from a GPU buffer: (supposing myInputGpuBuffer is a `GPUBuffer` object with input data)
const feeds = {
'input_image:0': ort.Tensor.fromGpuBuffer(myInputGpuBuffer, { dataType: 'float32', dims: [1, 224, 224, 3] })
};
```
### for outputs (pre-allocated GPU tensor)
you can also do that for output, **if you know the output shape**:
```js
// new STEP.2.B - create model output from a GPU buffer: (supposing myOutputGpuBuffer is a pre-allocated `GPUBuffer` object)
const fetches = {
'output_image:0': ort.Tensor.fromGpuBuffer(myOutputGpuBuffer, { dataType: 'float32', dims: [1, 512, 512, 3] })
};
// new STEP.3 - run model with pre-allocated output (fetches)
const myResults = await mySession.run(feeds, fetches);
```
### for outputs (specify location)
if you do not know the output shape, you can specify the output location
when creating the session:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: "gpu-buffer"
});
```
if the model has multiple outputs, you can specify them seperately:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: {
"output_image:0": "gpu-buffer"
}
});
```
now you don't need to prepare the `fetches` object and onnxruntime-web
will prepare output data on the location that specified.
#### read data
when you get the output tensor, you can:
```js
// get the gpu buffer object:
const gpuBuffer = myOutputTensor.gpuBuffer; // GPUBuffer
// get the CPU data asynchronizely
const cpuData = await myOutputTensor.getData();
// get the CPU data asynchronizely and release the underlying GPU resources
const cpuData = await myOutputTensor.getData(true);
// dispose the tensor (release the underlying GPU resources). This tensor object will be invalid after dispose() is called.
myOutputTensor.dispose();
```
#### resource management
JavaScript has GC so you don't need to worry about managing JavaScript
objects. But there are 2 types of resources that are not managed by GC:
- GPU buffer that used in tensors
- Underlying ORT native resources
To simplify, most of the unmanaged resources and handled inside ORT web.
But there are a few resources that need users to manage:
- All external GPU resources, including GPU buffers inside all tensors
created by `Tensor.fromGpuBuffer()`, will not be managed by ORT. User
should manage those GPU buffers themselves.
- When a session is created with `preferredOutputLocation` ==
"gpu-buffer" specified in session options, and the corresponding output
is not pre-allocated, user need to call the output tensor's `dispose()`
or `getData(true)` to manually release the underlying GPU buffers.
- ORT internal errors (including providing a pre-allocated output tensor
with wrong type/dims) will invalidate the whole wasm memory and is not
recoverable. An exception is thrown in this situation.
2023-09-29 18:24:42 +00:00
|
|
|
// check inputs location
|
|
|
|
|
if (inputs.some(t => t[3] !== 'cpu')) {
|
|
|
|
|
throw new Error('input tensor on GPU is not supported for proxy.');
|
|
|
|
|
}
|
|
|
|
|
// check outputs location
|
|
|
|
|
if (outputs.some(t => t)) {
|
|
|
|
|
throw new Error('pre-allocated output tensor is not supported for proxy.');
|
|
|
|
|
}
|
2021-08-31 17:23:42 +00:00
|
|
|
ensureWorker();
|
[js/webgpu] support IO binding (#17480)
<del>
**This PR is based on a few prerequisites PRs. They are listed as
below:**
- #17465
- #17469
- #17470
- #17472
- #17473
- #17484
Please review the current change by only looking at commit
e2e6623e673ec6de55a5c1f8edcbd3a46b535a89 and later.
</del>
### Description
This PR introduces WebGPU IO binding. This new feature allows
onnxruntime-web users to use tensors created from GPU as model
input/output so that a model inferencing can be done without unnecessary
data copy between CPU and GPU for model input/output.
### Examples
An E2E demo/example is being worked on.
Following is some simple demo with code snippet.
Let's first check today how we do:
```js
// STEP.1 - create an inference session:
const mySession = await ort.InferenceSession.create('./my_model.onnx', { executionProviders: ['webgpu'] });
// STEP.2 - create model input: (supposing myImageCpuData is a Float32Array)
const feeds = {
'input_image:0': new ort.Tensor('float32', myImageCpuData, [1, 224, 224, 3])
};
// STEP.3 - run model
const myResults = await mySession.run(feeds);
// STEP.4 - get output data
const myData = myResults['output_image:0'].data; // Float32Array
```
#### for inputs (GPU tensor):
Now, with IO binding, you can create a tensor from a GPU buffer, and
feed it to the model:
```js
// new STEP.2.A - create model input from a GPU buffer: (supposing myInputGpuBuffer is a `GPUBuffer` object with input data)
const feeds = {
'input_image:0': ort.Tensor.fromGpuBuffer(myInputGpuBuffer, { dataType: 'float32', dims: [1, 224, 224, 3] })
};
```
### for outputs (pre-allocated GPU tensor)
you can also do that for output, **if you know the output shape**:
```js
// new STEP.2.B - create model output from a GPU buffer: (supposing myOutputGpuBuffer is a pre-allocated `GPUBuffer` object)
const fetches = {
'output_image:0': ort.Tensor.fromGpuBuffer(myOutputGpuBuffer, { dataType: 'float32', dims: [1, 512, 512, 3] })
};
// new STEP.3 - run model with pre-allocated output (fetches)
const myResults = await mySession.run(feeds, fetches);
```
### for outputs (specify location)
if you do not know the output shape, you can specify the output location
when creating the session:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: "gpu-buffer"
});
```
if the model has multiple outputs, you can specify them seperately:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: {
"output_image:0": "gpu-buffer"
}
});
```
now you don't need to prepare the `fetches` object and onnxruntime-web
will prepare output data on the location that specified.
#### read data
when you get the output tensor, you can:
```js
// get the gpu buffer object:
const gpuBuffer = myOutputTensor.gpuBuffer; // GPUBuffer
// get the CPU data asynchronizely
const cpuData = await myOutputTensor.getData();
// get the CPU data asynchronizely and release the underlying GPU resources
const cpuData = await myOutputTensor.getData(true);
// dispose the tensor (release the underlying GPU resources). This tensor object will be invalid after dispose() is called.
myOutputTensor.dispose();
```
#### resource management
JavaScript has GC so you don't need to worry about managing JavaScript
objects. But there are 2 types of resources that are not managed by GC:
- GPU buffer that used in tensors
- Underlying ORT native resources
To simplify, most of the unmanaged resources and handled inside ORT web.
But there are a few resources that need users to manage:
- All external GPU resources, including GPU buffers inside all tensors
created by `Tensor.fromGpuBuffer()`, will not be managed by ORT. User
should manage those GPU buffers themselves.
- When a session is created with `preferredOutputLocation` ==
"gpu-buffer" specified in session options, and the corresponding output
is not pre-allocated, user need to call the output tensor's `dispose()`
or `getData(true)` to manually release the underlying GPU buffers.
- ORT internal errors (including providing a pre-allocated output tensor
with wrong type/dims) will invalidate the whole wasm memory and is not
recoverable. An exception is thrown in this situation.
2023-09-29 18:24:42 +00:00
|
|
|
return new Promise<SerializableTensorMetadata[]>((resolve, reject) => {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
enqueueCallbacks('run', [resolve, reject]);
|
[js/webgpu] support IO binding (#17480)
<del>
**This PR is based on a few prerequisites PRs. They are listed as
below:**
- #17465
- #17469
- #17470
- #17472
- #17473
- #17484
Please review the current change by only looking at commit
e2e6623e673ec6de55a5c1f8edcbd3a46b535a89 and later.
</del>
### Description
This PR introduces WebGPU IO binding. This new feature allows
onnxruntime-web users to use tensors created from GPU as model
input/output so that a model inferencing can be done without unnecessary
data copy between CPU and GPU for model input/output.
### Examples
An E2E demo/example is being worked on.
Following is some simple demo with code snippet.
Let's first check today how we do:
```js
// STEP.1 - create an inference session:
const mySession = await ort.InferenceSession.create('./my_model.onnx', { executionProviders: ['webgpu'] });
// STEP.2 - create model input: (supposing myImageCpuData is a Float32Array)
const feeds = {
'input_image:0': new ort.Tensor('float32', myImageCpuData, [1, 224, 224, 3])
};
// STEP.3 - run model
const myResults = await mySession.run(feeds);
// STEP.4 - get output data
const myData = myResults['output_image:0'].data; // Float32Array
```
#### for inputs (GPU tensor):
Now, with IO binding, you can create a tensor from a GPU buffer, and
feed it to the model:
```js
// new STEP.2.A - create model input from a GPU buffer: (supposing myInputGpuBuffer is a `GPUBuffer` object with input data)
const feeds = {
'input_image:0': ort.Tensor.fromGpuBuffer(myInputGpuBuffer, { dataType: 'float32', dims: [1, 224, 224, 3] })
};
```
### for outputs (pre-allocated GPU tensor)
you can also do that for output, **if you know the output shape**:
```js
// new STEP.2.B - create model output from a GPU buffer: (supposing myOutputGpuBuffer is a pre-allocated `GPUBuffer` object)
const fetches = {
'output_image:0': ort.Tensor.fromGpuBuffer(myOutputGpuBuffer, { dataType: 'float32', dims: [1, 512, 512, 3] })
};
// new STEP.3 - run model with pre-allocated output (fetches)
const myResults = await mySession.run(feeds, fetches);
```
### for outputs (specify location)
if you do not know the output shape, you can specify the output location
when creating the session:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: "gpu-buffer"
});
```
if the model has multiple outputs, you can specify them seperately:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: {
"output_image:0": "gpu-buffer"
}
});
```
now you don't need to prepare the `fetches` object and onnxruntime-web
will prepare output data on the location that specified.
#### read data
when you get the output tensor, you can:
```js
// get the gpu buffer object:
const gpuBuffer = myOutputTensor.gpuBuffer; // GPUBuffer
// get the CPU data asynchronizely
const cpuData = await myOutputTensor.getData();
// get the CPU data asynchronizely and release the underlying GPU resources
const cpuData = await myOutputTensor.getData(true);
// dispose the tensor (release the underlying GPU resources). This tensor object will be invalid after dispose() is called.
myOutputTensor.dispose();
```
#### resource management
JavaScript has GC so you don't need to worry about managing JavaScript
objects. But there are 2 types of resources that are not managed by GC:
- GPU buffer that used in tensors
- Underlying ORT native resources
To simplify, most of the unmanaged resources and handled inside ORT web.
But there are a few resources that need users to manage:
- All external GPU resources, including GPU buffers inside all tensors
created by `Tensor.fromGpuBuffer()`, will not be managed by ORT. User
should manage those GPU buffers themselves.
- When a session is created with `preferredOutputLocation` ==
"gpu-buffer" specified in session options, and the corresponding output
is not pre-allocated, user need to call the output tensor's `dispose()`
or `getData(true)` to manually release the underlying GPU buffers.
- ORT internal errors (including providing a pre-allocated output tensor
with wrong type/dims) will invalidate the whole wasm memory and is not
recoverable. An exception is thrown in this situation.
2023-09-29 18:24:42 +00:00
|
|
|
const serializableInputs = inputs as SerializableTensorMetadata[]; // every input is on CPU.
|
|
|
|
|
const message: OrtWasmMessage =
|
|
|
|
|
{type: 'run', in : {sessionId, inputIndices, inputs: serializableInputs, outputIndices, options}};
|
|
|
|
|
proxyWorker!.postMessage(message, core.extractTransferableBuffers(serializableInputs));
|
2021-08-31 17:23:42 +00:00
|
|
|
});
|
|
|
|
|
} else {
|
[js/webgpu] support IO binding (#17480)
<del>
**This PR is based on a few prerequisites PRs. They are listed as
below:**
- #17465
- #17469
- #17470
- #17472
- #17473
- #17484
Please review the current change by only looking at commit
e2e6623e673ec6de55a5c1f8edcbd3a46b535a89 and later.
</del>
### Description
This PR introduces WebGPU IO binding. This new feature allows
onnxruntime-web users to use tensors created from GPU as model
input/output so that a model inferencing can be done without unnecessary
data copy between CPU and GPU for model input/output.
### Examples
An E2E demo/example is being worked on.
Following is some simple demo with code snippet.
Let's first check today how we do:
```js
// STEP.1 - create an inference session:
const mySession = await ort.InferenceSession.create('./my_model.onnx', { executionProviders: ['webgpu'] });
// STEP.2 - create model input: (supposing myImageCpuData is a Float32Array)
const feeds = {
'input_image:0': new ort.Tensor('float32', myImageCpuData, [1, 224, 224, 3])
};
// STEP.3 - run model
const myResults = await mySession.run(feeds);
// STEP.4 - get output data
const myData = myResults['output_image:0'].data; // Float32Array
```
#### for inputs (GPU tensor):
Now, with IO binding, you can create a tensor from a GPU buffer, and
feed it to the model:
```js
// new STEP.2.A - create model input from a GPU buffer: (supposing myInputGpuBuffer is a `GPUBuffer` object with input data)
const feeds = {
'input_image:0': ort.Tensor.fromGpuBuffer(myInputGpuBuffer, { dataType: 'float32', dims: [1, 224, 224, 3] })
};
```
### for outputs (pre-allocated GPU tensor)
you can also do that for output, **if you know the output shape**:
```js
// new STEP.2.B - create model output from a GPU buffer: (supposing myOutputGpuBuffer is a pre-allocated `GPUBuffer` object)
const fetches = {
'output_image:0': ort.Tensor.fromGpuBuffer(myOutputGpuBuffer, { dataType: 'float32', dims: [1, 512, 512, 3] })
};
// new STEP.3 - run model with pre-allocated output (fetches)
const myResults = await mySession.run(feeds, fetches);
```
### for outputs (specify location)
if you do not know the output shape, you can specify the output location
when creating the session:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: "gpu-buffer"
});
```
if the model has multiple outputs, you can specify them seperately:
```js
// new STEP.1 - create an inference session with an option "preferredOutputLocation":
const mySession = await ort.InferenceSession.create('./my_model.onnx', {
executionProviders: ['webgpu'],
preferredOutputLocation: {
"output_image:0": "gpu-buffer"
}
});
```
now you don't need to prepare the `fetches` object and onnxruntime-web
will prepare output data on the location that specified.
#### read data
when you get the output tensor, you can:
```js
// get the gpu buffer object:
const gpuBuffer = myOutputTensor.gpuBuffer; // GPUBuffer
// get the CPU data asynchronizely
const cpuData = await myOutputTensor.getData();
// get the CPU data asynchronizely and release the underlying GPU resources
const cpuData = await myOutputTensor.getData(true);
// dispose the tensor (release the underlying GPU resources). This tensor object will be invalid after dispose() is called.
myOutputTensor.dispose();
```
#### resource management
JavaScript has GC so you don't need to worry about managing JavaScript
objects. But there are 2 types of resources that are not managed by GC:
- GPU buffer that used in tensors
- Underlying ORT native resources
To simplify, most of the unmanaged resources and handled inside ORT web.
But there are a few resources that need users to manage:
- All external GPU resources, including GPU buffers inside all tensors
created by `Tensor.fromGpuBuffer()`, will not be managed by ORT. User
should manage those GPU buffers themselves.
- When a session is created with `preferredOutputLocation` ==
"gpu-buffer" specified in session options, and the corresponding output
is not pre-allocated, user need to call the output tensor's `dispose()`
or `getData(true)` to manually release the underlying GPU buffers.
- ORT internal errors (including providing a pre-allocated output tensor
with wrong type/dims) will invalidate the whole wasm memory and is not
recoverable. An exception is thrown in this situation.
2023-09-29 18:24:42 +00:00
|
|
|
return core.run(sessionId, inputIndices, inputs, outputIndices, outputs, options);
|
2021-08-31 17:23:42 +00:00
|
|
|
}
|
|
|
|
|
};
|
2021-09-08 00:18:08 +00:00
|
|
|
|
|
|
|
|
export const endProfiling = async(sessionId: number): Promise<void> => {
|
2021-11-22 21:56:55 +00:00
|
|
|
if (!BUILD_DEFS.DISABLE_WASM_PROXY && isProxy()) {
|
2021-09-08 00:18:08 +00:00
|
|
|
ensureWorker();
|
|
|
|
|
return new Promise<void>((resolve, reject) => {
|
[js/web] revise backend registration (#18715)
### Description
This PR revises the backend registration.
The following describes the expected behavior after this change:
(**bolded are changed behavior**)
- (ort.min.js - built without webgpu support)
- loading: do not register 'webgpu' backend
- creating session without EP list: use default EP list ['webnn', 'cpu',
'wasm']
- creating session with ['webgpu'] as EP list: should fail with backend
not available
- (ort.webgpu.min.js - built with webgpu support)
- loading: **always register 'webgpu' backend**
( previous behavior: only register 'webgpu' backend when `navigator.gpu`
is available)
- creating session without EP list: use default EP list ['webgpu',
'webnn', 'cpu', 'wasm']
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init,**
and try to use next backend in the list, 'webnn'
(previous behavior: does not fail backend init, but fail in JSEP init,
which was too late to switch to next backend)
- creating session with ['webgpu'] as EP list
- when WebGPU is available (win): use WebGPU backend
- when WebGPU is unavailable (android): **should fail backend init, and
because no more EP listed, fail.
related PRs: #18190 #18144
2023-12-20 22:45:55 +00:00
|
|
|
enqueueCallbacks('end-profiling', [resolve, reject]);
|
2021-09-08 00:18:08 +00:00
|
|
|
const message: OrtWasmMessage = {type: 'end-profiling', in : sessionId};
|
|
|
|
|
proxyWorker!.postMessage(message);
|
|
|
|
|
});
|
|
|
|
|
} else {
|
|
|
|
|
core.endProfiling(sessionId);
|
|
|
|
|
}
|
|
|
|
|
};
|