### Description
<!-- Describe your changes. -->
When the onnx model reuses initializers in more than one ops, if one of
the ops wants to add this initializer to the skipped list, but the other
ops still need this initializer, it will cause the process to crash.

Therefore, like other EPs, we count `initializer_usage_`, the number of
occurrences of each initializer in all ops and modify the
`AddInitializersToSkip` to minus the corresponding initializers'
statistic one when adding the specific operators.

### 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
This PR is to update the win-ort-main branch to the tip main branch as
of 2025-01-23.

### PR List
ddf0d37 [QNN EP] Add LoggingManager::HasDefaultLogger() to provider
bridge API (#23467)
05fbbdf [QNN EP] Make QNN EP a shared library (#23120)
1336566 Add custom vcpkg ports (#23456)
2e1173c Update the compile flags for vcpkg packages (#23455)
1f628a9 [Mobile] Add BrowserStack Android MAUI Test (#23383)
009cae0 [js/webgpu] Optimize ConvTranspose (Continue) (#23429)
04a4a69 Use onnx_protobuf.h to suppress some GCC warnings (#23453)
2e3b62b Suppress some strict-aliasing related warnings in WebGPU EP
(#23454)
b708f9b Bump ruff from 0.9.1 to 0.9.2 (#23427)
c0afc66 [WebNN] Remove workarounds for TFLite backend (#23406)
8a821ff Bump vite from 6.0.7 to 6.0.11 in
/js/web/test/e2e/exports/testcases/vite-default (#23446)
220c1a2 Make ORT and Dawn use the same protobuf/abseil source code
(#23447)
b7b5792 Change MacOS-13 to ubuntu on for
android-java-api-aar-test.yml. (#23444)
19d0d2a WIP: Dp4MatMulNBits accuracy level 4 matmul for WebGPU EP
(#23365)
95b8eff [QNN EP]: Clean up QNN logging resources if an error occurs
during initialization (#23435)
626134c Bump clang-format from 19.1.6 to 19.1.7 (#23428)
0cf9753 Fix eigen external deps (#23439)
f9440ae Moving RN_CI Android Testing to Linux (#23422)
1aa5902 [QNN EP] workaround for QNN validation bug for Tanh with
uint16 quantized output (#23432)
7f5582a Seperate RN andriod and IOS into 2 separated Stages. (#23400)
73deac2 Implement some missing element wise Add/Sub/Mul/Div/Neg
operations for CPU and CUDA EPs (#23090)
949fe42 Upgrade Java version from react-native/android to Java 17
(#23066)
0892c23 Update Qnn SDK default version to 2.30 (#23411)
94c099b Fix type cast build error (#23423)
d633e57 [WebNN EP] Fix AddInitializersToSkip issues (#23354)
e988ef0 [QNN EP] Fix regression for MatMul with two quantized/dynamic
uint16 inputs (#23419)
7538795 Update onnxruntime binary size checks ci pipeline's docker
image (#23405)
6c5ea41 Revert "[QNN EP] Clean up correctly from a partial setup
(#23320)" (#23420)
e866804 Enable comprehension simplification in ruff rules (#23414)
0a5f1f3 bugfix: string_view of invalid memory (#23417)
4cc38e0 fix crash when first input of BatchNormalization is 1-D
(#23387)
0334414 Target py310 and modernize codebase with ruff (#23401)
87341ac [QNN EP] Fix segfault when unregistering HTP shared memory
handles (#23402)

### Motivation and Context
This update includes the change to make QNN-EP a shared library.

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: Adrian Lizarraga <[email protected]>
Co-authored-by: Justin Chu <[email protected]>
Co-authored-by: Yulong Wang <[email protected]>
Co-authored-by: Edward Chen <[email protected]>
Co-authored-by: Changming Sun <[email protected]>
Co-authored-by: Peishen Yan <[email protected]>
Co-authored-by: Tianlei Wu <[email protected]>
Co-authored-by: Hector Li <[email protected]>
Co-authored-by: Jian Chen <[email protected]>
Co-authored-by: Alexis Tsogias <[email protected]>
Co-authored-by: junchao-zhao <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: sushraja-msft <[email protected]>
Co-authored-by: Wanming Lin <[email protected]>
Co-authored-by: Jiajia Qin <[email protected]>
Co-authored-by: Caroline Zhu <[email protected]>

### Description
<!-- Describe your changes. -->
When the onnx model reuses initializers in more than one ops, if one of
the ops wants to add this initializer to the skipped list, but the other
ops still need this initializer, it will cause the process to crash.

Therefore, like other EPs, we count `initializer_usage_`, the number of
occurrences of each initializer in all ops and modify the
`AddInitializersToSkip` to minus the corresponding initializers'
statistic one when adding the specific operators.

### 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. -->
When the onnx model reuses initializers in more than one ops, if one of
the ops wants to add this initializer to the skipped list, but the other
ops still need this initializer, it will cause the process to crash.

Therefore, like other EPs, we count `initializer_usage_`, the number of
occurrences of each initializer in all ops and modify the
`AddInitializersToSkip` to minus the corresponding initializers'
statistic one when adding the specific operators.

### 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. -->