### Description
A break down PR of #22651
Add fp16 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
A break-down PR of #22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx


### 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
A breakdown PR of #22651



### 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
A break down PR of #22651
Add fp16 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
A break-down PR of #22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx


### 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
A breakdown PR of #22651



### 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
A break down PR of microsoft#22651
Add fp16 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
A break-down PR of microsoft#22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx


### 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
A breakdown PR of microsoft#22651



### 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
A break down PR of microsoft#22651
Add fp16 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
A break-down PR of microsoft#22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx


### 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
A breakdown PR of microsoft#22651



### 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
A break down PR of microsoft#22651
Add fp16 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
A break-down PR of microsoft#22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx


### 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
A breakdown PR of microsoft#22651



### 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. -->

[ARM] MatMulNBits FP16 support - kernels only (microsoft#22806)

A break down PR of microsoft#22651
Add fp16 kernels.

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- If it fixes an open issue, please link to the issue here. -->

Revert Implement DML copy for Lora Adapters (microsoft#22814)

Revert microsoft#22396

Fix issue microsoft#22796 - a typo: (__GNUC__ > 9) -> (__GNUC__ > 10) (microsoft#22807)

fix microsoft#22796
Signed-off-by: liqunfu <[email protected]>

[js/webgpu] Add scatterND (microsoft#22755)

<!-- Describe your changes. -->

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- If it fixes an open issue, please link to the issue here. -->

[WebNN] Remove validation for coordinate_transformation_mode (microsoft#22811)

The performance cost of falling back to the CPU EP is high for several
resampling nodes and causes multiple partitions in SD Turbo and VAE
decoder. Since the asymmetric mode with nearest to floor and integer
scales is identical to half_pixel anyway, stick with the WebNN EP.

[TensorRT EP] Add new provider option to exclude nodes from running on TRT (microsoft#22681)

Add new provider option `trt_op_types_to_exclude`:
- User can provide op type list to be excluded from running on TRT
- e.g. `trt_op_types_to_exclude="MaxPool"`

There is a known performance issue with the DDS ops (NonMaxSuppression,
NonZero and RoiAlign) from TRT versions 10.0 to 10.7. TRT EP excludes
DDS ops from running on TRT by default, user can override default value
with empty string to include all ops.

Keep the model metadata on the generated EP context model (microsoft#22825)

Keep the model metadata on the generated EP context model

[WebNN EP] Fix issues of GRU operator (microsoft#22123)

This PR fixes the spelling of the key value of the GRU operator in the
map in the `GetSupportedNodes` function (Gru -> GRU) and removes the
data type check for the fifth input (sequence_lens) of the GRU operator.

PTAL, thanks!

Auto-generated baselines by 1ES Pipeline Templates (microsoft#22817)

Fix Linux python CUDA package pipeline (microsoft#22803)

Making ::p optional in the Linux python CUDA package pipeline

Linux stage from Python-CUDA-Packaging-Pipeline has failed since merge
of microsoft#22773

[WebNN] Fix MLTensorUsage is undefined issue (microsoft#22831)

`MLTensorUsage` has been removed from Chromium:
https://chromium-review.googlesource.com/c/chromium/src/+/6015318, but
we still need to make it compatible with old Chrome versions, so just
make it `undefined` for latest Chrome version.

Enable ConvReplaceWithQLinear when using ACL (microsoft#22823)

Enable the ConvReplaceWithQLinear graph optimization when using the ACL
execution provider.

Fixes an issue where quantized Conv nodes followed by ReLU don't get
converted to QLinearConv, so ACL sees the weights as mutable and
therefore cannot run the Conv node.

Signed-off-by: Michael Tyler <[email protected]>

[CUDA] stable diffusion benchmark allows IO binding for optimum (microsoft#22834)

Update stable diffusion benchmark:
(1) allow IO binding for optimum.
(2) do not use num_images_per_prompt across all engines for fair
comparison.

Example to run benchmark of optimum on stable diffusion 1.5:
```
git clone https://github.com/tianleiwu/optimum
cd optimum
git checkout tlwu/diffusers-io-binding
pip install -e .

pip install -U onnxruntime-gpu
git clone https://github.com/microsoft/onnxruntime
cd onnxruntime/onnxruntime/python/tools/transformers/models/stable_diffusion
git checkout tlwu/benchmark_sd_optimum_io_binding
pip install -r requirements/cuda12/requirements.txt

optimum-cli export onnx --model runwayml/stable-diffusion-v1-5  --task text-to-image ./sd_onnx_fp32

python optimize_pipeline.py -i ./sd_onnx_fp32 -o ./sd_onnx_fp16 --float16
python benchmark.py -e optimum -r cuda -v 1.5 -p ./sd_onnx_fp16
python benchmark.py -e optimum -r cuda -v 1.5 -p ./sd_onnx_fp16 --use_io_binding
```

Example output in H100_80GB_HBM3: 572 ms with IO Binding; 588 ms without
IO Binding; IO binding gains 16ms, or 2.7%,

Optimum is working on enabling I/O binding:
huggingface/optimum#2056. This could help
testing the impact of I/O binding on the performance of the stable
diffusion.

Fix Linux CI pipeline where ep was not provided for py-packaging-linux-test-cpu.yml (microsoft#22828)

Current linux-ci-pipeline was broken due to missing parameters from
`py-packaging-linux-test-cpu.yml` template

Fix Linux CI pipeline

Register groupnorm for opset 21 (microsoft#22830)

This PR registers GroupNormalization for opset 21

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Fix spellchecks from Optional Lint (microsoft#22802)

<!-- Describe your changes. -->

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Change-Id: I561dfcdadcc6fa4cda899ef3bb181f0713fadebb

[ARM] MatMulNBits Fp16 support - API change only (microsoft#22826)

A break-down PR of microsoft#22651
Op API change only.
- add template to functions and classes that support fp32 and fp16
- rename functions, classes and files that support fp32 and fp16 from
SQNBxxx to QNBxxx

<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

Change-Id: Ib489e7858d42abcbe0514ac44e4d2172e32384a3

Re-enable test symbolic shape infer (microsoft#22737)

<!-- Describe your changes. -->
It seems after CI updated to py310, numpy got updated to 2.0 and sympy
1.2 failed to cast float numpy array.
Pointing sympy to 1.13 when py>=3.9 and re-enable unit test

<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Error: Linux CPU
CI

[Quant tool] Handle input models with pre-quantized weights (microsoft#22633)

Allows the QDQ quantizer to handle input models that already have some
pre-quantized weights. In this case, the qdq quantizer will properly
skip/handle the pre-quantized weights.

Also handles an operator (e.g., Conv) with a pre-quantized weight and a
float bias. The tool will read the pre-quantized weight's quantization
scale to compute the bias's scale (`bias_scale = input_scale *
weight_scale`).

Input model (pre-quantized Conv weight):

![image](https://github.com/user-attachments/assets/7d2626e4-49ad-47ae-bd0e-6339ac590435)

Output QDQ model (everything is quantized):

![image](https://github.com/user-attachments/assets/393804d3-f042-47bd-895f-3d667fb2ae94)

Customers may use external tools to quantize some weights (e.g., int4
for Conv/MatMul). The qdq quantizer should still be able to quantize the
rest of the model (float weights and activations) in this case.

Update Gradle version 8.7 and java version 17 within onnxruntime/java (microsoft#22771)

This change is to update the Gradle version within java project to 8.7,
it also upgrades the JAVA to 17. Gradle version from react-native was
also updated to 7.5 to make it compatible with changes from the Java
directory. However, the target java version remains the same. Java
version from these will be upgraded in a separated PR.

This is spited from microsoft#22206

This is the first step to upgrade the react native version.

Ovep develop 1.21 (microsoft#22824)

OVEP development changes for ORT 1.21 Release

Has critical bug fixes
Support for concurrency execution of models is enabled
Support for OV 2024.5
Memory optimizations for NPU platform

---------

Co-authored-by: jatinwadhwa921 <[email protected]>
Co-authored-by: Ankit Maheshkar <[email protected]>
Co-authored-by: sfatimar <[email protected]>
Co-authored-by: saurabhkale17 <[email protected]>
Co-authored-by: TejalKhade28 <[email protected]>
Co-authored-by: Javier E. Martinez <[email protected]>

Fix 1.20 cuda minimal build failure (microsoft#22751)

Fixes build failure for the cuda minimal build

<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
[This change](microsoft#19470) in
1.20 is causing build failures for the cuda minimal build.
Essentially, some cudnn logic was not guarded by the `USE_CUDA_MINIMAL`.
Also the build is looking for cudnn while in the cuda minimal build it
shouldn't depend on it, resulting in linking error.

cc @gedoensmax @chilo-ms

[ARM] MatMulNBits fp16 support - connect kernels (microsoft#22856)

A breakdown PR of microsoft#22651

<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

Change-Id: I3014c1002ff375a507bc04de7756baacf9a2b77a

[WebNN EP] Support Einsum op (microsoft#19558)

Adds support for einsum via WebNN matmul, transpose, reshape, reducesum,
identity and element-wise binary ops.

Refactor SkipLayerNorm and handle beta properly (microsoft#22862)

Signed-off-by: Liqun Fu <[email protected]>
Signed-off-by: Liqun Fu <[email protected]>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Change-Id: Ic5b8a6eb775542a57f07f5e593cc399dd7eeaa8f

Fix CUDA/DML package exception caused by ENABLE_CUDA_NHWC_OPS (microsoft#22851)

Now,  ENABLE_CUDA_NHWC_OPS is enabled by default.
It adds a new chance to create cuda provider while both cuda/dml are
enabled

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Optimize Transpose around QLinearSoftmax (microsoft#22849)

<!-- Describe your changes. -->

- Improved Transpose around QLinearSoftmax in Level 3 NHWC Transformer.
- Removed redundant code HandleQLinearConcat, HandleQLinearBinaryOp.

<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

By merging and eliminating redundant transpose , the Image Segmentation
i8 model (MobileNetv2 + DeepLabv3) achieves a 2.34X speedup.

Replace INFINITY by std::numeric_limits<float>::infinity() (microsoft#22868)

Replace INFINITY by `std::numeric_limits<float>::infinity()` to avoid
build errors with Visual Studio 2022 v17.12 Preview 5

microsoft#22728

[js/webgpu] Optimize transpose as reshape when suitable (microsoft#22870)

BUG microsoft#22031

Change-Id: I6c70d84228f1563792218c6c3c18b023852d4147

clang format code

Change-Id: I422a9474da9e9cfc9ac8819569a13520c5d2641f