argmax and argmin are similar to reduce. Eventually we need to add
optimized flavors of the shader.
softmax is optimized but only works on the last axis for now which
should be the common use case.
todo: enable more ut for argmax/argmin
### Description
Added Resize NHWC domain kernel registration.
### 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
There are currently multiple failures that blocking the CI pipelines so
this PR has all of the fixes in order to make sure it passes the CI.
Otherwise a single fix will still fail the CI.
includes:
#16960#16958
Please help to make sure this PR get merged once CI passed.
@snnn @carzh @guschmue
Fixed:
[AB#18118](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/18118)
---------
Co-authored-by: Caroline Zhu <carolinezhu@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
### Description
- enable unit test for js/common in CI
- add debug config in js/.vscode/launch.json
- enable source map for js/common/test for debugging purposes; add
source map files to ignore list
- ignore js/common/test folder for npm packaging
### Description
Set `canvas` dimensions to the `ImageBitmap` dimensions, thus fixing a
malformed Tensor creation.
### Motivation and Context
According to the [HTMLCanvasElement.drawImage()
spec](https://html.spec.whatwg.org/multipage/canvas.html#drawing-images):
> When the destination rectangle is outside the destination image (the
output bitmap), the pixels that land outside the output bitmap are
discarded, as if the destination was an infinite canvas whose rendering
was clipped to the dimensions of the output bitmap.
meaning that `ImageBitmap` pixels exceeding the canvas dimensions will
be discarded. Since no canvas dimensions are set for
`Tensor.fromImage(ImageBitmap)` if-case, the default 300x150px canvas
dimensions are used leading to the creation of malformed Tensors where
all the exceeding pixels are discarded and equal to `0, 0, 0, 0` during
the subsequent `pixels2DContext.getImageData()` call.
### Description
<!-- Describe your changes. -->
This PR moves checking profilingMode to each run instead of the
initialization stage. In this way, users can start/stop profiling at any
time. Otherwise, profiling only take effects at the very beginning and
can't be stopped.
### Description
Implemented Resize operator support in JSEP
### 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
Added Gelu operator to JSEP
### 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
Added Flatten operator support to JSEP.
### 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
"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
Added Slice operator support to JSEP.
### 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
<!-- Describe your changes. -->
Allocating new GPUBuffer in every session.run is not efficient. We
should make it only happen in the first run. In the following runs, we
should try to reuse those buffers.
### 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. -->
- This PR is for performance.
See mobilenetv2 becomes 9.58 ms from 12.9 ms.
### Description
This change upgrades a lot of dependencies. There are 2 motivations of
doing this change:
- fix the security issue reported by dependabot (protobufjs Prototype
Pollution vulnerability -
https://github.com/advisories/GHSA-h755-8qp9-cq85)
- resolve the requirement of using ONNX IR_VERSION 9 (#16638)
This requires:
- upgrade protobufjs to v7.2.4
- upgrade library 'onnx-proto' to consume latest ONNX release (v1.14.0).
Problems:
- protobufjs v7.2.4 depends on long.js v5, which does not work well with
typescript (commonjs).
- onnx-proto depends on this fix with a new release of long.js
- long.js is in maintenance and it takes longer than expected to put in
new changes
Solutions:
- use a patch script in `preprepare` to copy type declarations to make
long.js work with typescript (commonjs)
- generate onnx protobuf JS/TS files and put them under
js/web/lib/onnxjs/ort-schema/protobuf folder - remove 'onnx-proto' from
dependency.
- apply fixes to generated onnx.d.ts
### Description
fix file size trim for wasm only .min.js
minimal build `ort.wasm.min.js` and `ort.wasm-core.min.js` should
exclude JSEP related source code.
### Description
<!-- Describe your changes. -->
As title.
Validation at JS call level in E2E app is not included. Can cover
together in a separate pr.
### 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. -->
Test coverage.
---------
Co-authored-by: rachguo <rachguo@rachguos-Mini.attlocal.net>
Co-authored-by: rachguo <rachguo@rachguos-Mac-mini.local>
### Description
allow creating (u)int64 tensors from either a number array or a bigint
array.
before:
```js
// TypeScript think is good, but actually does not work
// runtime error: Uncaught TypeError: Cannot convert 1 to a BigInt
const myTensor1 = new Tensor('int64', [1, 2, 3, 4], [2, 2]);
// runtime good, but TypeScript thinks myTensor2 is a string tensor
const myTensor2 = new Tensor('int64', [1n, 2n, 3n, 4n], [2, 2]);
```
after:
```js
// both work at runtime and TypeScript populates the correct types
const myTensor1 = new Tensor('int64', [1, 2, 3, 4], [2, 2]);
const myTensor2 = new Tensor('int64', [1n, 2n, 3n, 4n], [2, 2]);
```
### Description
This change reduces the number of calls to globby functions so that it
accelerates the initialization for 'npm test' with suite0/1 tests from
~14sec to <2sec.
### Description
Added Expand operator support.
### 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
Add ConvTranspose support for WebGPU
### 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
Added WeGPU/JSEP Split operator support.
### 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
Add missing L1Reduce and L2Reduce operator kernels.
### 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
always use 'typescript' from /js/ folder. This allows all NPM packages
to use the same typescript version.
- remove 'typescript' from /js/react_native/package.json. use the one
from /js/package.json
- remove unused '@types/fs-extra'
### Description
Add Concat operator
### 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
Modified indexing into outputIndices in the shader code. When the output
is 1-dim the outputIndices is not a vector and indexing results in
error.
### Motivation and Context
Fix the problem in the Reduce Ops implementation in WebGPU.
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
As title.
### 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. -->
Works with local onnxruntime-c pod in js/rn/e2e test.
A couple of places in onnxruntime used `float_t` data type alias as an
alternative to `float`. However, this is not entirely correct, since
`float_t` is an implementation-defined type alias, which may be `float`,
`double`, `long double` or some other implementation-defined data type,
depending on the state of the internal `FLT_EVAL_METHOD` macro:
https://en.cppreference.com/w/c/numeric/math/float_t
On most major platforms and compilers (clang, GCC, MSVC) this is only a
cosmetic change and will not lead to any changes. However, icpx compiler
(and legacy icc) tends to substitute `float_t` with `long double`,
resulting in a linker error (unresolved reference) to the base onnx
library, that only contains the `ParseData` function for `float` and
`double` as in
[here](9264e09367/onnx/defs/tensor_proto_util.cc (L133-L134)).
Overall, this PR cleans up the implementation-defined behaviour and
enables building onnxruntime with icpx.
### Description
Modify the creating of webgl context.
Previous behavior:
STEP.1 - create canvas (document.createElement), if failed, goto step.2
else step.3
STEP.2 - create offscreenCanvas, if failed abort
STEP.3 - use the canvas created in step.1 or 2 to create webgl context.
if successful return context else abort
Now bahavior:
STEP.1 create offscreenCanvas, if failed goto step.3
STEP.2 use it to create webgl context. if successful, return context
STEP.3 create canvas (document.createElement). if failed, abort
STEP.4 use it to create webgl context. if successful, return context
else abort
Motivation:
we found in some environment, normalCanvas.getContext() returns null but
offscreenCanvas.getContext() returns the context object. and when
offscreenCanvas is available it is good idea to always prefer to use it.
### Description
We used to use `typeof fetch === 'undefined'` as condition to detect the
environment is Node.js or not. Before Node.js v18, this works. However,
in Node.js v18, it introduced `fetch` function, so this check does not
work any more.
This PR changes the condition to check whether `process`,
`process.versions` and `process.versions.node` exists.
Checking whether `process` exists is not enough. This is because in some
configuration, webpack may polyfill nodejs's process.
### Description
<!-- Describe your changes. -->
This PR adds support for `executionProviders` option for react-native
package, support:
- Android: cpu / xnnpack / nnapi
- iOS: cpu / xnnpack / coreml
### 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. -->
In my case I want to enable Core ML / NNAPI EP for react-native project.
### Description
<!-- Describe your changes. -->
- Create `OnnxruntimeJSIHelper` native module to provide two JSI
functions
- `jsiOnnxruntimeStoreArrayBuffer`: Store buffer in Blob Manager &
return blob object (iOS: RCTBlobManager, Android: BlobModule)
- `jsiOnnxruntimeResolveArrayBuffer`: Use blob object to get buffer
- The part of implementation is reference to
[react-native-blob-jsi-helper](https://github.com/mrousavy/react-native-blob-jsi-helper)
- Replace base64 encode/decode
- `loadModelFromBlob`: Rename from `loadModelFromBase64EncodedBuffer`
- `run`: Use blob object to replace input.data & results[].data
For [this
context](https://github.com/microsoft/onnxruntime/issues/16031#issuecomment-1556527812),
it saved a lot of time and avoid JS thread blocking in decode return
type, it is 3700ms -> 5~20ms for the case. (resolve function only takes
0.x ms)
### 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. -->
It’s related to #16031, but not a full implementation for migrate to
JSI.
It just uses JSI through BlobManager to replace the slow part (base64
encode / decode).
Rewriting it entirely in JSI could be complicated, like type convertion
and threading. This PR might be considered a minor change.
/cc @skottmckay
"default" should be last element for exports.
This fixes "Module not found: Error: Default condition should be last
one" when importing the onnxruntime-web package in some conditions.
### Description
Added support for ReduceL1, ReduceL2, ReduceMean, ReduceMin, ReduceMax,
ReduceSum, ReduceLogSum, ReduceLogSumExp, ReduceProd and
ReduceSquareSum.
### 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: Satya Jandhyala <sajandhy@microsoft.com>
Co-authored-by: guschmue <guschmue@microsoft.com>
