### Description
<!-- Describe your changes. -->
Switch to setImmediate to avoid starving the Node.js event loop
There should really be a true async version though, running
computationally intensive things on the event loop will stop everything
else from happening while it is running, e.g. a web server from
answering requests.
This can be done by wrapping `RunAsync` behind a
[`napi::Promise`](https://github.com/nodejs/node-addon-api/blob/main/doc/promises.md)
to run on the onnxruntime thread pool or [`AsyncWorker`](
https://github.com/nodejs/node-addon-api/blob/main/doc/async_worker.md)
for the Node.js/libuv thread pool.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Without this, if you run inference in a tight loop, without anything
else in between that is async/deferred, `process.nextTick` will lead to
starving the event loop and not letting anything else run,
`setImmediate` at least lets the event loop spin between calls to `run`.
See
https://dev.to/ynmanware/setimmediate-settimeout-and-process-nexttick-3mfd
Contributed on behalf of [Swimm](https://swimm.io/)
### Description
<!-- Describe your changes. -->
Bump up version to 1.18.0 since the release branch has been cut.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Co-authored-by: rachguo <rachguo@rachguos-Mini.attlocal.net>
### Description
Following the design document:
* Added CreateTrainingSessionHandler to the Backend interface
* All existing Backend implementations throw an error for the new method
createTrainingSessionHandler
* Created TrainingSession namespace, interface, and
TrainingSessionFactory interface
* Created TrainingSessionImpl class implementation
As methods are implemented, the TrainingSession interface will be added
to or modified.
### Motivation and Context
Adding the public-facing interfaces to the onnxruntime-common package is
one of the first steps to support ORT training for web bindings.
---------
Co-authored-by: Caroline Zhu <carolinezhu@microsoft.com>
[//]: # (## Work In Progress. Feedbacks are welcome!)
### Description
This PR adds a few properties, methods and factories to Tensor type to
support IO-binding feature. This will allow user to create tensor from
GPU/CPU bound data without a force transferring of data between CPU and
GPU.
This change is a way to resolve#15312
### Change Summary
1. Add properties to `Tensor` type:
a. `location`: indicating where the data is sitting. valid values are
`cpu`, `cpu-pinned`, `texture`, `gpu-buffer`.
b. `texture`: sit side to `data`, a readonly property of `WebGLTexture`
type. available only when `location === 'texture'`
c. `gpuBuffer`: sit side to `data`, a readonly property of `GPUBuffer`
type. available only when `location === 'gpu-buffer'`
2. Add methods to `Tensor` type (usually dealing with inference
outputs):
- async function `getData()` allows user to download data from GPU to
CPU manually.
- function `dispose()` allows user to release GPU resources manually.
3. Add factories for creating `Tensor` instances:
a. `fromTexture()` to create a WebGL texture bound tensor data
b. `fromGpuBuffer()` to create a WebGPUBuffer bound tensor data
c. `fromPinnedBuffer()` to create a tensor using a CPU pinned buffer
### Examples:
create tensors from texture and pass to inference session as inputs
```js
// when create session, specify we prefer 'image_output:0' to be stored on GPU as texture
const session = await InferenceSession.create('./my_model.onnx', {
executionProviders: [ 'webgl' ],
preferredOutputLocation: { 'image_output:0': 'texture' }
});
...
const myImageTexture = getTexture(); // user's function to get a texture
const myFeeds = { input0: Tensor.fromTexture(myImageTexture, { width: 224, height: 224 }) }; // shape [1, 224, 224, 4], RGBA format.
const results = await session.run(myFeeds);
const myOutputTexture = results['image_output:0'].texture;
```
### Description
Add an API for users to get version of current package. example usage:
```js
import { env } from 'onnxruntime-node';
console.log(env.versions.node); // output "1.16.0"
```
```js
import { env } from 'onnxruntime-web';
console.log(env.versions.web); // output "1.16.0"
console.log(env.versions.common); // output "1.16.0"
console.log(env.versions.node); // output "undefined"
```
#16156
**Description**: This PR adds support for "XNNPACK EP" in ORTWeb and
changes the behavior of how ORTWeb deals with "backends", or "EPs" in
API.
**Background**: Term "backend" is introduced in ONNX.js to representing
a TypeScript type which implements a "backend" interface, which is a
similar but different concept to ORT's EP (execution provider). There
was 3 backends in ONNX.js: "cpu", "wasm" and "webgl".
When ORT Web is launched, the concept is derived to help users to
integrate smoothly. Technically, when "wasm" backend is used, users need
to also specify "EP" in the session options. Considering it may get
complicated and confused for users to figure out the difference between
"backend" and "EP", the JS API hide the "backend" concept and made a
mapping between names, backends and EPs:
"webgl" (Name) <==> "onnxjsBackend" (Backend)
"wasm" (Name) <==> "wasmBackend" (Backend) <==> "CPU" (EP)
**Details**:
The following changes are applied in this PR:
1. allow multi-registration for backends using the same name. This is
for use scenarios where both "onnxruntime-node" and "onnxruntime-web"
are consumed in a Node.js App ( so "cpu" will be registered twice in
this scenario. )
2. re-assign priority values to backends. I give 100 as base to "cpu"
for node and react_native, and 10 as base to "cpu" in web.
3. add "cpu", "xnnpack" as new names of backends.
4. update onnxruntime wasm exported functions to support EP
registration.
5. update implementations in ort web to handle execution providers in
session options.
6. add '--use_xnnpack' as default build flag for ort-web
* working on re-organizing js code for ortweb
* remove dup files
* move folder
* fix common references
* fix common es5
* add webpack to common
* split interfact/impl
* use cjs for node
* add npmignore for common
* update sourcemap config for common
* update node
* adjust folder/path in CI and build
* update folder
* nit: readme
* add bundle for dev
* correct nodejs paths
* enable ORT_API_MANUAL_INIT
* set name for umd library
* correct name for commonjs export
* add priority into registerBackend()
* fix npm ci pwd
* update eslintrc
* revise code
* revert package-lock lockfileVersion 2->1
* update prebuild
* resolve comments
* update document
* revise eslint config
* update eslint for typescript rules
* revert changes by mistake in backend.ts
* add env
* resolve comments
