### Description
1. Enable VCPKG flag in Windows CPU CI build pipelines.
2. Increased the min supported cmake version from 3.26 to 3.28. Because
of it, drop the support for the old way of finding python by
"find_package(PythonLibs)". Therefore, in build.py we no longer set
"PYTHON_EXECUTABLE" cmake var when doing cmake configure.
3. Added "xnnpack-ep" as a feature for ORT's vcpkg config.
4. Added asset cache support for ORT's vcpkg build
5. Added VCPKG triplet files for Android build.
6. Set VCPKG triplet to "universal2-osx" if CMAKE_OSX_ARCHITECTURES was
found in cmake extra defines.
7. Removed a small piece of code in build.py, which was for support CUDA
version < 11.8.
8. Fixed an issue that CMAKE_OSX_ARCHITECTURES sometimes got specified
twice when build.py invoked cmake.
9. Added more model tests to Android build. After this change, we will
test all ONNX versions instead of just the latest one.
10. Fixed issues that are related to build.py's "--build_nuget"
parameter. Also, enable the flag in most Windows CPU CI build jobs.
11. Removed a restriction in build.py that disallowed cross-compiling
Windows ARM64 nuget package on Windows x86.
### Motivation and Context
Adopt vcpkg.
Move Linux GPU CI pipeline to A10 machines which are more advanced.
Retire onnxruntime-Linux-GPU-T4 machine pool.
Disable run_lean_attention test because the new machines do not have
enough shared memory.
```
skip loading trt attention kernel fmha_mhca_fp16_128_256_sm86_kernel because no enough shared memory
[E:onnxruntime:, sequential_executor.cc:505 ExecuteKernel] Non-zero status code returned while running MultiHeadAttention node. Name:'MultiHeadAttention_0' Status Message: CUDA error cudaErrorInvalidValue:invalid argument
```
### Description
* Build cuda nhwc ops by default.
* Deprecate `--enable_cuda_nhwc_ops` in build.py and add
`--disable_cuda_nhwc_ops` option
Note that it requires cuDNN 9.x. If you build with cuDNN 8, NHWC ops
will be disabled automatically.
### Motivation and Context
In general, NHWC is faster than NCHW for convolution in Nvidia GPUs with
Tensor Cores, and this could improve performance for vision models.
This is the first step to prefer NHWC for CUDA in 1.21 release. Next
step is to do some tests on popular vision models. If it help in most
models and devices, set `prefer_nhwc=1` as default cuda provider option.
### Description
Refactor the cmake code that is related to delay loading. Provide a
cmake option to control if delay loading should be enabled or not.
Disabling the option when python is enabled, due to a known issue.
### Motivation and Context
ONNX Runtime's python package depends on DirectML.dll, but supposedly
the DLL should be delay loaded.
This PR only refactor the code. It doesn't change the behavior.
1. Add python 3.13 to our python packaging pipelines
2. Because numpy 2.0.0 doesn't support thread free python, this PR also
upgrades numpy to the latest
3. Delete some unused files.
### Description
Similar to #20786 . The last PR was able to update all pipelines and all
docker files. This is a follow-up to that PR.
### Motivation and Context
1. To extract the common part as a reusable build infra among different
ONNX Runtime projects.
2. Avoid hitting docker hub's limit: 429 Too Many Requests - Server
message: toomanyrequests: You have reached your pull rate limit. You may
increase the limit by authenticating and upgrading:
https://www.docker.com/increase-rate-limit
