### Description
1. Remove 'dnf update' from docker build scripts, because it upgrades TRT
packages from CUDA 11.x to CUDA 12.x.
To reproduce it, you can run the following commands in a CentOS CUDA
11.x docker image such as nvidia/cuda:11.8.0-cudnn8-devel-ubi8.
```
export v=8.6.1.6-1.cuda11.8
dnf install -y libnvinfer8-${v} libnvparsers8-${v} libnvonnxparsers8-${v} libnvinfer-plugin8-${v} libnvinfer-vc-plugin8-${v} libnvinfer-devel-${v} libnvparsers-devel-${v} libnvonnxparsers-devel-${v} libnvinfer-plugin-devel-${v} libnvinfer-vc-plugin-devel-${v} libnvinfer-headers-devel-${v} libnvinfer-headers-plugin-devel-${v}
dnf update -y
```
The last command will generate the following outputs:
```
========================================================================================================================
Package Architecture Version Repository Size
========================================================================================================================
Upgrading:
libnvinfer-devel x86_64 8.6.1.6-1.cuda12.0 cuda 542 M
libnvinfer-headers-devel x86_64 8.6.1.6-1.cuda12.0 cuda 118 k
libnvinfer-headers-plugin-devel x86_64 8.6.1.6-1.cuda12.0 cuda 14 k
libnvinfer-plugin-devel x86_64 8.6.1.6-1.cuda12.0 cuda 13 M
libnvinfer-plugin8 x86_64 8.6.1.6-1.cuda12.0 cuda 13 M
libnvinfer-vc-plugin-devel x86_64 8.6.1.6-1.cuda12.0 cuda 107 k
libnvinfer-vc-plugin8 x86_64 8.6.1.6-1.cuda12.0 cuda 251 k
libnvinfer8 x86_64 8.6.1.6-1.cuda12.0 cuda 543 M
libnvonnxparsers-devel x86_64 8.6.1.6-1.cuda12.0 cuda 467 k
libnvonnxparsers8 x86_64 8.6.1.6-1.cuda12.0 cuda 757 k
libnvparsers-devel x86_64 8.6.1.6-1.cuda12.0 cuda 2.0 M
libnvparsers8 x86_64 8.6.1.6-1.cuda12.0 cuda 854 k
Installing dependencies:
cuda-toolkit-12-0-config-common noarch 12.0.146-1 cuda 7.7 k
cuda-toolkit-12-config-common noarch 12.2.140-1 cuda 7.9 k
libcublas-12-0 x86_64 12.0.2.224-1 cuda 361 M
libcublas-devel-12-0 x86_64 12.0.2.224-1 cuda 397 M
Transaction Summary
========================================================================================================================
```
As you can see from the output, they are CUDA 12 packages.
The problem can also be solved by lock the packages' versions by using
"dnf versionlock" command right after installing the CUDA/TRT packages.
However, going forward, to get the better reproducibility, I suggest
manually fix dnf package versions in the installation scripts like we do
for TRT now.
```bash
v="8.6.1.6-1.cuda11.8" &&\
yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo &&\
yum -y install libnvinfer8-${v} libnvparsers8-${v} libnvonnxparsers8-${v} libnvinfer-plugin8-${v} libnvinfer-vc-plugin8-${v}\
libnvinfer-devel-${v} libnvparsers-devel-${v} libnvonnxparsers-devel-${v} libnvinfer-plugin-devel-${v} libnvinfer-vc-plugin-devel-${v} libnvinfer-headers-devel-${v} libnvinfer-headers-plugin-devel-${v}
```
When we have a need to upgrade a package due to security alert or some
other reasons, we manually change the version string instead of relying
on "dnf update". Though this approach increases efforts, it can make our
pipeines more stable.
2. Move python test to docker
### Motivation and Context
Right now the nightly gpu package mixes using CUDA 11.x and CUDA 12.x
and the result package is totally not usable(crashes every time)
### Description
1. Update docker files and their build instructions.
ARM64 and x86_64 can use the same docker file.
2. Upgrade Linux CUDA pipeline's base docker image from CentOS7 to UBI8
AB#18990
### Description
<!-- Describe your changes. -->
### 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. -->
Get the latest gcc 12 by default
---------
Co-authored-by: Changming Sun <chasun@microsoft.com>
### Description
All our Windows build pipelines already uses cmake 3.26 except one
pipeline: QNN ARM64.
This PR does the same for Linux build pipelines.
### Motivation and Context
This change is related to #15704 .
- Use java/gradlew directly in .github/workflows/publish-java-apidocs.yml.
- Remove use of deleted step from tools/ci_build/github/azure-pipelines/android-arm64-v8a-QNN-crosscompile-ci-pipeline.yml.
- Remove Gradle installations and PATH updates from Dockerfiles and scripts. Now Gradle wrapper is used so a system Gradle installation is not needed.
### Description
Upgrade cmake version to 3.24 because I need to use a new feature that
is only provided in that version and later. Starting from cmake 3.24,
the
[FetchContent](https://cmake.org/cmake/help/latest/module/FetchContent.html#module:FetchContent)
module and the
[find_package()](https://cmake.org/cmake/help/latest/command/find_package.html#command:find_package)
command now support integration capabilities, which means calls to
"FetchContent" can be implicitly redirected to "find_package", and vice
versa. Users can use a cmake variable to control the behavior. So, we
don't need to provide such a build option. We can delete our
"onnxruntime_PREFER_SYSTEM_LIB" build option and let cmake handle it.
And it would be easier for who wants to use vcpkg.
### Motivation and Context
Provide a unified package management method, and get aligned with the
community. This change is split from #13523 for easier review.
