Bumps [cross-spawn](https://github.com/moxystudio/node-cross-spawn) from
7.0.3 to 7.0.6.
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/moxystudio/node-cross-spawn/blob/master/CHANGELOG.md">cross-spawn's
changelog</a>.</em></p>
<blockquote>
<h3><a
href="https://github.com/moxystudio/node-cross-spawn/compare/v7.0.5...v7.0.6">7.0.6</a>
(2024-11-18)</h3>
<h3>Bug Fixes</h3>
<ul>
<li>update cross-spawn version to 7.0.5 in package-lock.json (<a
href="f700743918">f700743</a>)</li>
</ul>
<h3><a
href="https://github.com/moxystudio/node-cross-spawn/compare/v7.0.4...v7.0.5">7.0.5</a>
(2024-11-07)</h3>
<h3>Bug Fixes</h3>
<ul>
<li>fix escaping bug introduced by backtracking (<a
href="640d391fde">640d391</a>)</li>
</ul>
<h3><a
href="https://github.com/moxystudio/node-cross-spawn/compare/v7.0.3...v7.0.4">7.0.4</a>
(2024-11-07)</h3>
<h3>Bug Fixes</h3>
<ul>
<li>disable regexp backtracking (<a
href="https://redirect.github.com/moxystudio/node-cross-spawn/issues/160">#160</a>)
(<a
href="5ff3a07d9a">5ff3a07</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="77cd97f3ca"><code>77cd97f</code></a>
chore(release): 7.0.6</li>
<li><a
href="6717de49ff"><code>6717de4</code></a>
chore: upgrade standard-version</li>
<li><a
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fix: update cross-spawn version to 7.0.5 in package-lock.json</li>
<li><a
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chore: fix build status badge</li>
<li><a
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chore(release): 7.0.5</li>
<li><a
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fix: fix escaping bug introduced by backtracking</li>
<li><a
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chore: remove codecov</li>
<li><a
href="a7c6abc6fe"><code>a7c6abc</code></a>
chore: replace travis with github workflows</li>
<li><a
href="9b9246e096"><code>9b9246e</code></a>
chore(release): 7.0.4</li>
<li><a
href="5ff3a07d9a"><code>5ff3a07</code></a>
fix: disable regexp backtracking (<a
href="https://redirect.github.com/moxystudio/node-cross-spawn/issues/160">#160</a>)</li>
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### Description
This PR updates installation script to fix it for CUDA v12. However, it
may be difficult for CUDA v11 since the steps are quite complicated to
automate. Added a few lines of instructions instead.
fixes#22877
### Description
This change enhances the Node.js binding with the following features:
- support WebGPU EP
- lazy initialization of `OrtEnv`
- being able to initialize ORT with default log level setting from
`ort.env.logLevel`.
- session options:
- `enableProfiling` and `profileFilePrefix`: support profiling.
- `externalData`: explicit external data (optional in Node.js binding)
- `optimizedModelFilePath`: allow dumping optimized model for diagnosis
purpose
- `preferredOutputLocation`: support IO binding.
======================================================
`Tensor.download()` is not implemented in this PR.
Build pipeline update is not included in this PR.
### Description
See
454996d496
for manual changes (excluded auto-generated formatting changes)
### Why
Because the toolsets for old clang-format is out-of-date. This reduces
the development efficiency.
- The NPM package `clang-format` is already in maintenance mode. not
updated since 2 years ago.
- The VSCode extension for clang-format is not maintained for a while,
and a recent Node.js security update made it not working at all in
Windows.
No one in community seems interested in fixing those.
Choose Prettier as it is the most popular TS/JS formatter.
### How to merge
It's easy to break the build:
- Be careful of any new commits on main not included in this PR.
- Be careful that after this PR is merged, other PRs that already passed
CI can merge.
So, make sure there is no new commits before merging this one, and
invalidate js PRs that already passed CI, force them to merge to latest.
This commit e5f18ba2c1 caused some nightly
pipelines to fail. This PR fixes it.
It is because recently I changed our Linux library's SONAME. At runtime
onnxruntime_binding depends on libonnxruntime.so.1 , instead of
libonnxruntime.so.1.19.0(with the full version number). Therefore we
need to keep the libonnxruntime.so.1 symlink.
The packaging tools/ci_build/github/js/pack-npm-packages.ps1 still needs
be updated. I will address it in another PR.
### Description
Add support for using Onnx Runtime with Node
### Motivation and Context
Onnx Runtime supports the QNN HTP, but does not support it for Node.js.
This adds baseline support for the Onnx Runtime to be used with Node.
Note it does not update the node packages that are distributed
officially. This simply patches the onnxruntime.dll to allow 'qnn' to be
used as an execution provider.
Testing was done using the existing onnxruntime-node package. The
`onnxruntime.dll` and `onnxruntime_binding.node` were swapped into
`node_modules\onnxruntime-node\bin\napi-v3\win32\arm64` with the newly
built version, then the various QNN dlls and .so files were placed next
to the onnxruntime.dll. Testing was performed on a variety of models and
applications, but the easiest test is to modify the [node quickstart
example](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/js/quick-start_onnxruntime-node).
Bump up version in main from 1.18.0 to 1.19.0 since the release branch
has been cut.
---------
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description
Currently we try to include all prebuilt binaries into the NPM packages.
This was working until we added libonnxruntime_providers_cuda.so
(>400MB) into the NPM package. The NPM registry refuses to accept new
package publishment because the file is too large.
To make the new NPM package working, we have to remove the large file
from the package, and add a new script on package installation. This
script will try to dynamically install onnxruntime CUDA dynamic library
for Linux/x64.
### How to run it locally
1. conda install ninja
2. "C:\Program Files\Microsoft Visual
Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
3. python.exe {ort_repo}\tools\ci_build\build.py --config RelWithDebInfo
--build_dir {ort_repo}\build_cuda --skip_submodule_sync --build_csharp
--update --parallel --cmake_generator "Ninja" --build_shared_lib
--enable_onnx_tests --enable_pybind --build_java --build_nodejs
--use_cuda "--cuda_home=C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v11.8" --enable_cuda_profiling --cmake_extra_defines
CMAKE_CUDA_ARCHITECTURES=60
4. cd build_cuda\RelWithDebInfo
5. cmake --build . j16
### Motivation and Context
In packaging pipelines, we often come across a random issue that the
building with CUDA on Windows takes too much time.
Although it has been reduced much by moving the building to the CPU
machine.
We're planning to build with Ninja instead of msbuild in Packaging
pipelines, thus, nvcc can run parallelly.
It's the first step to support it locally.
Bumps
[follow-redirects](https://github.com/follow-redirects/follow-redirects)
from 1.15.4 to 1.15.6.
<details>
<summary>Commits</summary>
<ul>
<li><a
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Release version 1.15.6 of the npm package.</li>
<li><a
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Drop Proxy-Authorization across hosts.</li>
<li><a
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Use GitHub for disclosure.</li>
<li><a
href="b1677ce001"><code>b1677ce</code></a>
Release version 1.15.5 of the npm package.</li>
<li><a
href="d8914f7982"><code>d8914f7</code></a>
Preserve fragment in responseUrl.</li>
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### 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>
Bumps
[follow-redirects](https://github.com/follow-redirects/follow-redirects)
from 1.15.2 to 1.15.4.
<details>
<summary>Commits</summary>
<ul>
<li><a
href="65858205e5"><code>6585820</code></a>
Release version 1.15.4 of the npm package.</li>
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Disallow bracketed hostnames.</li>
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### Description
[js] update a few packages
- update semver
- update reference of onnx_proto to local folder in order to upgrade
protobufjs@7.2.4
Resolve AB#18513
### Description
This PR fixes the TypeScript type check.
Previously, when I use esbuild to replace webpack (#17745), typescript
typecheck was disabled. This causes a few TypeScript type error checked
in into the code base. This PR fixes the followings:
- Use "Node16" as default "module" value in tsconfig.json, because in
TypeScript v5, `(module == "ES2015" && moduleResolution == "Node16")` is
an invalid combination.
- Set `noUnusedParameters` to true as default. in web override it to
false because multiple code need to be updated ( a following-up PR will
do this )
- set correct project file for 'web/lib/**/*.ts' for ESLint (otherwise
WebGPU types are not populated correctly)
- fix type error in file js/web/lib/wasm/jsep/webgpu/program-manager.ts
- upgrade "@webgpu/types" to latest to fix type error in file
js/web/lib/wasm/jsep/backend-webgpu.ts
- add package script "prebuild" for web to run tsc type check
- add type check in CI yml file
### Description
upgrade JS shared dev dependencies.
- webpack: removed
- eslint: upgrade to latest.
- eslint config upgraded to compatible with latest version
- typescript upgrade to v5
- update module "CommonJS" to "Node16" in tsconfig
- update deprecated config "importsNotUsedAsValues" to
"verbatimModuleSyntax"
- remove webpack bundles in onnxruntime-common
Two major modifications of this PR:
1. Refactor OrtTensorRTProviderOptions initialization and make it easy
to add new field.
2. Make Python API capable of using TensorRT plugins by adding new
Python binding api `register_tensorrt_plugins_as_custom_ops`. (It needs
to register ep's custom op domain before model load. For C++ API, it's
slightly different, when calling
SessionOptionsAppendExecutionProvider_TensorRT_XX, it appends cutom op
domain to session option. Later ORT can register custom op domain from
session option before model loading)
### 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>
### Description
update prepack script to use exact version.
the prepack script for onnxruntime-node, onnxruntime-web and
onnxruntime-react-native is used to update their referencing version of
dependency "onnxruntime-common".
Previously "~" (tilde symbol) is used. This may cause NPM choose an
older version (if the old version matches the version requirement and
was previously installed already so hit the cache). see also
https://semver.npmjs.com/. [This
build](https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1134671&view=results)
is caused by this issue.
[//]: # (## 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
Release OrtEnv before main function returns. Before this change, OrtEnv
is deleted when C/C++ runtime destructs all global variables in ONNX
Runtime's core framework.
The callstack is like this:
```
* frame #0: 0x00007fffee39f5a6 libonnxruntime.so.1.16.0`onnxruntime::Environment::~Environment(this=0x00007fffee39fbf2) at environment.h:20:7
frame #1: 0x00007fffee39f614 libonnxruntime.so.1.16.0`std::default_delete<onnxruntime::Environment>::operator()(this=0x00007ffff4c30e50, __ptr=0x0000000005404b00) const at unique_ptr.h:85:2
frame #2: 0x00007fffee39edca libonnxruntime.so.1.16.0`std::unique_ptr<onnxruntime::Environment, std::default_delete<onnxruntime::Environment>>::~unique_ptr(this=0x5404b00) at unique_ptr.h:361:17
frame #3: 0x00007fffee39e2ab libonnxruntime.so.1.16.0`OrtEnv::~OrtEnv(this=0x00007ffff4c30e50) at ort_env.cc:43:1
frame #4: 0x00007fffee39fa96 libonnxruntime.so.1.16.0`std::default_delete<OrtEnv>::operator()(this=0x00007fffefff8f78, __ptr=0x00007ffff4c30e50) const at unique_ptr.h:85:2
frame #5: 0x00007fffee39f394 libonnxruntime.so.1.16.0`std::unique_ptr<OrtEnv, std::default_delete<OrtEnv>>::~unique_ptr(this=0x7ffff4c30e50) at unique_ptr.h:361:17
frame #6: 0x00007ffff78574b5 libc.so.6`__run_exit_handlers + 261
frame #7: 0x00007ffff7857630 libc.so.6`exit + 32
frame #8: 0x00007ffff783feb7 libc.so.6`__libc_start_call_main + 135
frame #9: 0x00007ffff783ff60 libc.so.6`__libc_start_main@@GLIBC_2.34 + 128
frame #10: 0x0000000000abbdee node`_start + 46
```
After this change, OrtEnv will be deleted before the main function
returns and nodejs is still alive.
### Description
"onnxruntime-common" starts to get more and more complicated, so it's a
good idea to add unit tests for it.
Includes the following changes:
- move `mocha` from each subfolder (js/web/, js/node/) to root (js/), so
that it will be installed once and all subfolder can use.
- add folder `test` in js/common/ as root folder for ort-common tests.
- add sub folder `type-tests`. this folder contains a few typescript
source code, which are excluded from the tsconfig.json. they are not
compiled by default. instead, file `type-tests.ts` calls typescript
compiler (tsc) to check for the files under this folder whether the
compilation result is as expected. If tsc compiles a file successfully
when a failure is expected, this is considered an failed test.
- add sub folder `unit-tests`. files under this folder will be compiled
by default. we use default mode of mocha (using `describe()` and `it()`)
to setup test groups and cases.
- update eslint rules accordingly.
### 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
1. Update VERSION_NUMBER for preparing the upcoming release. This PR's
commit will not be included in the 1.15 release branch
2. Delete package/rpm/onnxruntime.spec since it was not used in past
years.
### Motivation and Context
Preparing the release.
Fixed
[AB#15311](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/15311)
### Description
This PR includes the following changes:
- upgrade js dependencies
- enable STRICT mode for web assembly build.
- corresponding fix for cmake-js upgrade
- corresponsing fix for linter upgrade
- upgrade default typescript compile option of:
- `moduleResolution`: from `node` to `node16`
- `target`: from `es2017` to `es2020`
- fix ESM module import in commonJS source file
## change explanation
### changes to onnxruntime_webassembly.cmake
`-s WASM=1` and `-s LLD_REPORT_UNDEFINED` in latest version is
by-default and deprecated.
### changes to onnxruntime_node.cmake
The npm package `cmake-js` updated its way to find file `node.lib`.
previously it downloads this file from Node.js public release channel,
and now it generates it from a definition file.
The node.js release channel does not contain a windows/arm64 version, so
previously cmake-js will fail to download `node.lib` for that platform.
this is why we made special handling to download the unofficial binary
to build. now this is no longer needed so we removed that from the cmake
file.
### changes to tsconfig.json
`node16` module resolution supports async import and `es2020` as target
supports top level await.
### Description
update versions of a few build dependencies for onnxruntime NPM
packages.
update nodejs version to v16.x in linux CI. v12 is too out-of-dated. see
[nodejs release
schedule](https://github.com/nodejs/release#release-schedule)
### Motivation and Context
- upgrade to latest webpack allows using of latest Node.js LTS version.
previous version of webpack does not work on Node.js v18 and it is fixed
in latest version
- upgrade to latest typescript, ts-loader and other dev deps to
accelerate the build and bundling.
- upgrade also helps to resolve security warnings that may be vulnerable
in out-of-dated version
### Description
Bumping up version number to 1.14.0
### 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. -->
### Description
Deprecate CustomOpApi and refactor dependencies for exception safety and
eliminate memory leaks.
Refactor API classes for clear ownership and semantics.
Introduce `InitProviderOrtApi()`
### Motivation and Context
Make public API better and safer.
Special note about `Ort::Unowned`. The class suffers from the following
problems:
1. It is not able to hold const pointers to the underlying C objects.
This forces users to `const_cast` and circumvent constness of the
returned object. The user is now able to call mutating interfaces on the
object which violates invariants and may be a thread-safety issue. It
also enables to take ownership of the pointer and destroy it
unintentionally (see examples below).
2. The objects that are unowned cannot be copied and that makes coding
inconvenient and at times unsafe.
3. It directly inherits from the type it `unowns`.
All of the above creates great conditions for inadvertent unowned object
mutations and destructions. Consider the following examples of object
slicing, one of them is from a real customer issue and the other one I
accidentally coded myself (and I am supposed to know how this works).
None of the below can be solved by aftermarket patches and can be hard
to diagnose.
#### Example 1 slicing of argument
```cpp
void SlicingOnArgument(Ort::Value& value) {
// This will take possession of the input and if the argument
// is Ort::Unowned<Ort::Value> it would again double free the ptr
// regardless if it was const or not since we cast it away.
Ort::Value output_values[] = {std::move(value)};
}
void main() {
const OrtValue* ptr = nullptr; // some value does not matter
Ort::Unowned<Ort::Value> unowned{const_cast<OrtValue*>(ptr)};
// onowned is destroyed when the call returns.
SlicingOnArgument(unowned);
}
```
#### Example 2 slicing of return value
```cpp
// The return will be sliced to Ort::Value that would own and relase (double free the ptr)
Ort::Value SlicingOnReturn() {
const OrtValue* ptr = nullptr; // some value does not matter
Ort::Unowned<Ort::Value> unowned{const_cast<OrtValue*>(ptr)};
return unowned;
}
```
**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
# Motivation
Currently, ORT minimal builds use kernel def hashes to map from nodes to
kernels to execute when loading the model. As the kernel def hashes must
be known ahead of time, this works for statically registered kernels.
This works well for the CPU EP.
For this approach to work, the kernel def hashes must also be known at
ORT format model conversion time, which means the EP with statically
registered kernels must also be enabled then. This is not an issue for
the always-available CPU EP. However, we do not want to require that any
EP which statically registers kernels is always available too.
Consequently, we explore another approach to match nodes to kernels that
does not rely on kernel def hashes. An added benefit of this is the
possibility of moving away from kernel def hashes completely, which
would eliminate the maintenance burden of keeping the hashes stable.
# Approach
In a full build, ORT uses some information from the ONNX op schema to
match a node to a kernel. We want to avoid including the ONNX op schema
in a minimal build to reduce binary size. Essentially, we take the
necessary information from the ONNX op schema and make it available in a
minimal build.
We decouple the ONNX op schema from the kernel matching logic. The
kernel matching logic instead relies on per-op information which can
either be obtained from the ONNX op schema or another source.
This per-op information must be available in a minimal build when there
are no ONNX op schemas. We put it in the ORT format model.
Existing uses of kernel def hashes to look up kernels are replaced
with the updated kernel matching logic. We no longer store
kernel def hashes in the ORT format model’s session state and runtime
optimization representations. We no longer keep the logic to
generate and ensure stability of kernel def hashes.
