Avoid producing presentKey/presentValue outputs if pastKey/pastValue
don't exists.
### Description
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### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
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### Motivation and Context
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### Description
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This PR fixes the `AttentionProbsSoftmax` recompilation issue when
executing the phi3 model. With this fix, it will further improve the
phi3 performance.
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
Previously, MultiHeadAttention supports relative position bias of shape
[1, N, S, T] or [B, N, S, T], and DecoderMaskedMultiHeadAttention
supports [1, N, S, T]. This will extend the support to allow [1, N, S,
T], [B, N, S, T], [B, 1, S, T] and [1, 1, S, T] for CUDA and CPU EPs.
- [x] Rename the input of "relative position bias" to "attention bias"
because it can also be used for other types of bias, like ALiBi
(Attention with Linear Biases) or attention mask.
- [x] Update unfused kernel to support broadcasting 2nd dimension of
attention bias.
- [x] Update efficient attention to support broadcasting 2nd dimension
of attention bias.
- [x] Update operators (MultiHeadAttention,
DecoderMaskedMultiHeadAttention, Attention, PackedAttention,
PackedMultiHeadAttention) to support broadcast attention bias on CUDA
and CPU EPs.
- [x] Update ROCm, DML and WebGPU naming to be consistent. (Note that
those EPs do not support broadcasting attention_bias for now).
- [x] Add attention bias tests for MultiHeadAttention.
- [x] Update operator documents
- [x] Update benchmark script
Other changes:
* Fix some checks in multihead-attention.ts
* Add helper functions to dump tensors given dimensions.
Chrome Canary is helpful to test some new features. With this PR, we can
enable Chrome Canary in unit tests with command like "npm test -- op
abs.jsonc -b=webgpu -e=chromecanary".
### 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Because the toolsets for old clang-format is out-of-date.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.
Bug: https://github.com/microsoft/onnxruntime/issues/21386
### Description
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### Motivation and Context
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### Description
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Replace jcenter. It's deprecated and not responding.
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
Fix CIs
Fix two issues:
(1) scale shall be fp32 instead of f16
(2) Softmax program does not handle the normalized dispatch group values, so if the sequence length is over 65535, the result is not correct for this program.
### Description
Added DequantizeLinear operator for JSEP.
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
update the build script for webgpu to enable model dump by default
Now if using build_jsep.bat to build debug, the model dump is enabled.
Using
[`optimizedModelFilePath`](https://onnxruntime.ai/docs/api/js/interfaces/InferenceSession.SessionOptions.html#optimizedModelFilePath)
in session option can dump the optimized model in browser
### Motivation and Context
Helps to debug/rule out problems may related to model optimizer.
### Description
allow op test to use f16 type for inputs/outputs.
This PR introduces "@petamoriken/float16" as Float16Array polyfill but
restricts it to be only used for test runner.
### Description
WebNN only supports test mode, so we don't care about other inputs or
attributes about training mode, use WebNN's identity op to implement the
Dropout op directly.
### Description
This PR adds a new option `ort.env.wasm.wasmBinary`, which allows user
to set to a buffer containing preload .wasm file content.
This PR should resolve the problem from latest discussion in #20876.
Bug:https://github.com/microsoft/onnxruntime/issues/21467
### Description
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### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
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### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
WebNN spec recently changes the definition of argMax/argMin:
- Remove selectLastIndex option, let backends decide to select the last
index or not.
- Move axes option to axis input
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
```
# npm audit report
socket.io 3.0.0 - 4.6.2
Severity: high
socket.io has an unhandled 'error' event - https://github.com/advisories/GHSA-25hc-qcg6-38wj
Depends on vulnerable versions of engine.io
fix available via `npm audit fix`
node_modules/socket.io
ws 8.0.0 - 8.17.0
Severity: high
ws affected by a DoS when handling a request with many HTTP headers - https://github.com/advisories/GHSA-3h5v-q93c-6h6q
fix available via `npm audit fix`
node_modules/ws
engine.io 0.7.8 - 0.7.9 || 6.0.0 - 6.5.4
Depends on vulnerable versions of ws
node_modules/engine.io
socket.io-adapter 2.5.2 - 2.5.4
Depends on vulnerable versions of ws
node_modules/socket.io-adapter
4 high severity vulnerabilities
```
This var has been initialized to 0 in tint, so no need extra loop to do
it again:
```
float tint_symbol_52[1][4] = (float[1][4])0;
{
for(int tint_symbol_53 = 0; (tint_symbol_53 < 1); tint_symbol_53 = (tint_symbol_53 + 1)) {
{
for(int tint_symbol_54 = 0; (tint_symbol_54 < 4); tint_symbol_54 = (tint_symbol_54 + 1)) {
tint_symbol_52[min(uint(tint_symbol_53), 0u)][min(uint(tint_symbol_54), 3u)] = 0.0f;
}
}
}
}
```
### Description
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### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
There are so many typos reported by the review dog, [Optional Lint]
actions (example:
https://github.com/microsoft/onnxruntime/actions/runs/9864564489/job/27239732367),
this PR is to fix some of them.
### 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: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description
This PR resolves a bug related to setting the **interOpNumThreads**
session option when creating an **ORTSession**. Currently, when the
**interOpNumThreads** option is passed from React Native, the native
module incorrectly sets **intraOpNumThreads** instead of
**interOpNumThreads**.
### Motivation and Context
Since this is a bug, users of the Onnx React Native package may believe
that they are setting **interOpNumThreads** correctly, So this change is
required. Refer to the code snippet below for details
<img width="634" alt="Screenshot 2024-07-05 at 9 28 58 PM"
src="https://github.com/microsoft/onnxruntime/assets/88655321/70a8f216-553a-4f4c-9481-e6871f0e37e6">
### Description
This PR enables the API added in #20816 as well as moving context
creation to JS.
### Motivation and Context
In order to enable I/O Binding with the upcoming
[MLBuffer](https://github.com/webmachinelearning/webnn/issues/542) API
in the WebNN specification, we need to share the same `MLContext` across
multiple sessions. This is because `MLBuffer`s are restricted to the
`MLContext` where they were created. This PR enables developers to use
the same `MLContext` across multiple sessions.
Currently WebNN TFLite backend allows the filter of
conv2d/convTranspose2d be an input. Remove the constraint and operate
necessary transpose/reshape operations for the filter input.
### Description
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### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
WebNN CPU implementation has been migrated from XNNPack to TFLite which
supports more ops. Turn on partial `cpu` supported ops which just need
the change from `false` to `true` firstly.
### Description
skip default `locateFile()` when dynamic import is disabled. This allows
the file to work with bundlers to load WebAssembly file correctly if
`env.wasm.wasmPaths` is not set.
### Description
ESM: use the bundled target as default export
In this change, the default import of the following entries:
```
import from 'onnxruntime-web';
import from 'onnxruntime-web/all';
import from 'onnxruntime-web/webgpu';
```
will use the "bundled" version, which has no dynamic import.
This change should only apply to ESM on web.
# Description
This PR removes the building of the ORT "mobile" packages and much of the associated infrastructure which is no longer needed.
Not removed yet - tools/ci_build/github/android/mobile_package.required_operators.config and the helper scripts that depend on it.
# Motivation and Context
The mobile packages were deprecated in 1.18. Users should use the full packages (Android - onnxruntime-android, iOS - onnxruntime-c/onnxruntime-objc) instead or do a custom build.
Following constraints have been supported by WebNN TFLite backend:
- Concat: supports up to 4 inputs
- Matmul: supports broadcasting
- Resize: supports nearest mode
- Split: supports up to 4 outputs
