### Description
Those test cases start to fail for unknown reasons.
To unblock the CI, I disabled those tests temporarily to earn time to
investigate the root cause.
### Description
This PR is a replacement of #21671. It offers a new way for accessing
the following:
- `ort.env.webgpu.adapter`:
- **deprecating**. There is no point to get the value of it. Once
`GPUDevice.adapterInfo` is supported, there is no point to set the value
too.
- `ort.env.webgpu.device`:
- set value of `GPUDevice` if user created it. Use at user's own risk.
- get value of `Promise<GPUDevice>`. if not exist, create a new one. if
exist return it.
- `ort.env.webgpu.powerPreference`:
- **deprecating**. encouraging users to set `ort.env.webgpu.device` if
necessary.
- `ort.env.webgpu.forceFallbackAdapter`:
- **deprecating**. encouraging users to set `ort.env.webgpu.device` if
necessary.
### Description
<!-- Describe your changes. -->
### 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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### Motivation and Context
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This PR make MatMul shaders not depend on inputs broadcasting pattern,
but only depend on input ranks and their shape provided in uniform. This
change fix the issue that currently shaders code are different for
different broadcasting, but have identical cache key and results in
wrong cache hit.
### Description
<!-- Describe your changes. -->
BUG #22031
In the demucs model, there are lots of MatMul ops with shapes like
below:
`input[0]: [3448,1,512] | float32, input[1]: [512,1536] | float32,
output[0]: [3448,1,1536] | float32`
We can see that for this kind of shape, the batch size is a big value,
but M = 1. Our current algorithm is based on [M, N] to partition tiles,
which is not efficient for such kind of shapes. This PR reshapes the
inputs to improve the matmul performance.
Before: [3448,1,512] x [512,1536] = [3448,1,1536]
After: [1, 3448, 512] x [512, 1536] = [1, 3448, 1536] , then the output
can be reshaped to [3448, 1, 1536]
The overall MatMul time in demucs model becomes 1778.45 ms from 4418.17
ms on my iGPUs.
---------
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
### Description
<!-- Describe your changes. -->
Test case failing sometimes and passing other times.
### Motivation and Context
Prevent unnecessary CI build failures requiring manually rerunning tests
Currently in debug mode, unit test will always download models to local
file system, which is a bit annoying. This PR fixes this by adding a
specific option to enable model download.
In current implementation, axis in softmax has to be the last, which is
an obvious limitation. This PR removes this limitation and will fix
issues #20710 and #22176.
### Description
Enables using the MLTensor to pass data between models.
### Motivation and Context
Using MLTensor instead of ArrayBuffers reduces the number of copies
between the CPU and devices as well as the renderer and GPU process in
Chromium.
<!-- Describe your changes. -->
<!-- - 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. -->
#21618
This PR optimizes grouped conv by 1) more sequential memory access in
gpu 2) reusing input's data to reduce global memory access times.
See `Conv|GroupedConv` op in
[Wav2Vec2](https://huggingface.co/facebook/wav2vec2-base-960h) becomes
92 ms from 1058 ms on iGPUs with 32 EU.
For the whole model on my iGPUs with 32 EU,
wav2vec2 model becomes 982ms from 1942 ms.
squeezebert-uncased model becomes 71.86ms from 431.77ms.
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
Fix bugs in previous implementation and add more situations to go the
optimized path.
Below situations will go to the optimized path.
1. 2d inputs or squeezed 2d inputs
2. channels last or channels first transpose. For example, channel last
transpose: [1, 256, 512, 512] -> [1, 512, 512, 256]
For this case, the transpose becomes [256, 512x512] -> [512x512, 256]
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
For SD Turbo demo, the total transpose time becomes 39.98ms from
122.09ms. And the correspnding percents becomes 3.89% from 11.05% in
this demo.
This PR will also help #21618, the total transpose time in that demo
becomes 17.32 ms from 70.25 ms on my iGPUs.
### Description
<!-- Describe your changes. -->
### Motivation and Context
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### Description
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### Motivation and Context
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---------
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
Avoid producing presentKey/presentValue outputs if pastKey/pastValue
don't exists.
### Description
<!-- Describe your changes. -->
### Motivation and Context
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### 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.
### 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
<!-- Describe your changes. -->
### Motivation and Context
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### Description
Added DequantizeLinear operator for 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
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
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
<!-- Describe your changes. -->
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
### Motivation and Context
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### Description
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This PR allows to build ORT web to `ort{.all|.webgpu}.bundle.min.mjs`,
which does not have any dynamic import. This makes it possible to use
ort web via static import in service worker.
Fixes#20876
### Description
Remove explicitly concatinating pastKey with Key and pastValue with
Value.
### 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. -->
