### Description
<!-- Describe your changes. -->
* promote trt version to 10.2.0.19
* EP_Perf CI: clean config of legacy TRT<8.6, promote test env to
trt10.2-cu118/cu125
* skip two tests as Float8/BF16 are supported by TRT>10.0 but TRT CIs
are not hardware-compatible on these:
```
1: [ FAILED ] 2 tests, listed below:
1: [ FAILED ] IsInfTest.test_isinf_bfloat16
1: [ FAILED ] IsInfTest.test_Float8E4M3FN
```
### 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
Use a common set of prebuilt manylinux base images to build the
packages, to avoid building the manylinux part again and again. The base
images can be used in GenAI and other projects too.
This PR also updates the GCC version for inference python CUDA11/CUDA12
builds from 8 to 11. Later on I will update all other CUDA pipelines to
use GCC 11, to avoid the issue described in
https://github.com/onnx/onnx/issues/6047 and
https://github.com/microsoft/onnxruntime-genai/issues/257 .
### Motivation and Context
To extract the common part as a reusable build infra among different
ONNX Runtime projects.
### Description
<!-- Describe your changes. -->
This branch is based on rel-1.18.0 and supports TensorRT 10-GA.
### 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
1. Move building on CPU machine.
2. Optimize the pipeline
3. Since there isn't official ONNX package for python 12, the python 12
test stage uses the packages built with ONNX source in build stage.
### Motivation and Context
1. Resolve the random hang in compilation
4. Save a lot of GPU resources.
---------
### 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. -->
### 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. -->
### 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
1. Fix python packaging test pipeline. There was an error in
tools/ci_build/github/linux/run_python_tests.sh that it installed a
released version of onnxruntime python package from pypi.org to run the
test. Supposedly it should pick one from the current build.
2. Refactor the pipeline to allow choosing cmake build type from the web
UI when manually trigger a build. Now this feature is for Linux only.
Because I don't want to change too much when we are about to cut a
release branch. After that I will expand it to all platforms. This
feature is useful for debugging pipeline issues, also, we may consider
having a nightly pipeline to run all tests in Debug mode which may catch
extra bugs because in debug mode we can enforce range check.
Test run:
https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=342674&view=results
### Motivation and Context
Currently the pipeline has a crash error.
AB#18580
### Description
<!-- Describe your changes. -->
* Integrate TRT 8.6EA on relevant Linux/Windows/pkg pipelines
* Update onnx-tensorrt to 8.6
* Add new dockerfiles for TRT 8.6 and clean old ones
* Update
[CGManifest](https://github.com/microsoft/onnxruntime/tree/main/cgmanifests)
files and ort build deps version
* yml/script update
* Enable built-in TRT parser option on TRT related pipelines by default
* Exclude test TopKOperator.Top3ExplicitAxisInfinity out of TRT EP tests
(8.6-EA has issue with topk operator)
## Description
1. Convert some git submodules to cmake external projects
2. Update nsync from
[1.23.0](https://github.com/google/nsync/releases/tag/1.23.0) to
[1.25.0](https://github.com/google/nsync/releases/tag/1.25.0)
3. Update re2 from 2021-06-01 to 2022-06-01
4. Update wil from an old commit to 1.0.220914.1 tag
5. Update gtest to a newer commit so that it can optionally leverage
absl/re2 for parsing command line flags.
The following git submodules are deleted:
1. FP16
2. safeint
3. XNNPACK
4. cxxopts
5. dlpack
7. flatbuffers
8. googlebenchmark
9. json
10. mimalloc
11. mp11
12. pthreadpool
More will come.
## Motivation and Context
There are 3 ways of integrating 3rd party C/C++ libraries into ONNX
Runtime:
1. Install them to a system location, then use cmake's find_package
module to locate them.
2. Use git submodules
6. Use cmake's external projects(externalproject_add).
At first when this project was just started, we considered both option 2
and option 3. We preferred option 2 because:
1. It's easier to handle authentication. At first this project was not
open source, and it had some other non-public dependencies. If we use
git submodule, ADO will handle authentication smoothly. Otherwise we
need to manually pass tokens around and be very careful on not exposing
them in build logs.
2. At that time, cmake fetched dependencies after "cmake" finished
generating vcprojects/makefiles. So it was very difficult to make cflags
consistent. Since cmake 3.11, it has a new command: FetchContent, which
fetches dependencies when it generates vcprojects/makefiles just before
add_subdirectories, so the parent project's variables/settings can be
easily passed to the child projects.
And when the project went on, we had some new concerns:
1. As we started to have more and more EPs and build configs, the number
of submodules grew quickly. For more developers, most ORT submodules are
not relevant to them. They shouldn't need to download all of them.
2. It is impossible to let two different build configs use two different
versions of the same dependency. For example, right now we have protobuf
3.18.3 in the submodules. Then every EP must use the same version.
Whenever we have a need to upgrade protobuf, we need to coordinate
across the whole team and many external developers. I can't manage it
anymore.
3. Some projects want to manage the dependencies in a different way,
either because of their preference or because of compliance
requirements. For example, some Microsoft teams want to use vcpkg, but
we don't want to force every user of onnxruntime using vcpkg.
7. Someone wants to dynamically link to protobuf, but our build script
only does static link.
8. Hard to handle security vulnerabilities. For example, whenever
protobuf has a security patch, we have a lot of things to do. But if we
allowed people to build ORT with a different version of protobuf without
changing ORT"s source code, the customer who build ORT from source will
be able to act on such things in a quicker way. They will not need to
wait ORT having a patch release.
9. Every time we do a release, github will also publish a source file
zip file and a source file tarball for us. But they are not usable,
because they miss submodules.
### New features
After this change, users will be able to:
1. Build the dependencies in the way they want, then install them to
somewhere(for example, /usr or a temp folder).
2. Or download the dependencies by using cmake commands from these
dependencies official website
3. Similar to the above, but use your private mirrors to migrate supply
chain risks.
4. Use different versions of the dependencies, as long as our source
code is compatible with them. For example, you may use you can't use
protobuf 3.20.x as they need code changes in ONNX Runtime.
6. Only download the things the current build needs.
10. Avoid building external dependencies again and again in every build.
### Breaking change
The onnxruntime_PREFER_SYSTEM_LIB build option is removed you could think from now
it is default ON. If you don't like the new behavior, you can set FETCHCONTENT_TRY_FIND_PACKAGE_MODE to NEVER.
Besides, for who relied on the onnxruntime_PREFER_SYSTEM_LIB build
option, please be aware that this PR will change find_package calls from
Module mode to Config mode. For example, in the past if you have
installed protobuf from apt-get from ubuntu 20.04's official repo,
find_package can find it and use it. But after this PR, it won't. This
is because that protobuf version provided by Ubuntu 20.04 is too old to
support the "config mode". It can be resolved by getting a newer version
of protobuf from somewhere.
1. Update CUDA version from 11.4 to 11.6.
2. Update Manylinux version
3. Upgrade GCC version from 10 to 11 for most x86_64 pipelines. CentOS 7 ARM64 doesn't have GCC 11 yet.
4. Refactor python packaging pipeline:
a. Split Linux GPU build job to two parts, build and test, so that the
build part doesn't need to use a GPU machine
b. Make the Linux GPU build job and Linux CPU build job more similar: share the same bash script and yaml file.
5. Temporarily disable Attention_Mask1D_Fp16_B2_FusedNoPadding because it is causing one of our packaging pipeline to fail. I have created an ADO task for this.
