1. Enable xnnpack test
2. Change TSA database name from onnxruntime_master to onnxruntime_main.
This is a leftover of renaming the "master" branch to "main"
3. Add two static analysis jobs for WinML and DML
4. Rename the machine pool "aiinfra-dml-winbuild" to
"onnxruntime-Win2019-GPU-dml-A10", so that the internal and public ADO
instances use the same machine pool name.
5. Move Windows GPU CI build pipeline from "onnxruntime-Win2022-GPU-T4"
to "onnxruntime-Win2022-GPU-A10" machine pool, because we do not have
enough T4 GPUs.
1. Update SDLNativeRules from v2 to v3. The new one allows us setting excluded paths.
2. Update TSAUpload from v1 to v2. And add a config file ".gdn/.gdntsa" for it.
3. Fix some parentheses warnings
4. Update cmake to the latest.
5. Remove "--x86" build option from pipeline yaml files. Now we can auto-detect cpu architecture from python. So we don't need to ask user to specify it.
