Fix Torch-TensorRT Bazel build on JetPack

[Mike-Sagiri]

Description

Update and fix TensorRT Bazel build support on NVIDIA JetPack platforms.
JetPack packages TensorRT headers and libraries differently from standard Linux TensorRT distributions.

This change:

• adds JetPack-specific include path support for third_party/tensorrt/local/BUILD
• adds JetPack-specific library path support for third_party/tensorrt/local/BUILD
• updates Bazel select() rules for JetPack environments for third_party/tensorrt/local/BUILD
• fixes incorrect TensorRT library resolution on JetPack systems for of third_party/tensorrt/local/BUILD
• updates dependencies for JetPack in setup.py and MODULE.bazel
• now the users can use --jetpack to build Torch-TensorRT from source successfully

Known issue:

• Since TensorRT 10.13+ not support cuda 12.x anymore, building Torch-TensorRT with TensorRT 10.13+ needs cuda 13 on JetPack. However, JetPack 6.2 and lower doesn't support cuda 13. When building Torch-TensorRT with TensorRT 10.7-, add_attention is not supported by TensorRT 10.14-. So the users may need to add torch.backends.cuda.enable_flash_sdp(False), torch.backends.cuda.enable_mem_efficient_sdp(False), torch.backends.cuda.enable_math_sdp(True) to solve the problem.
• A stable version for JetPack 6.x is Torch 2.10, Torch-TensorRT 2.10 and TensorRT 10.7.

Fixes # (issue)

Type of change

Please delete options that are not relevant and/or add your own.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

Checklist:

• My code follows the style guidelines of this project (You can use the linters)
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas and hacks
• I have made corresponding changes to the documentation
• I have added tests to verify my fix or my feature
• New and existing unit tests pass locally with my changes
• I have added the relevant labels to my PR in so that relevant reviewers are notified