PyTorch's PR #193605 auto-labels B200 CI for CuTeDSL and DLPack paths

PyTorch's CI infrastructure just got a critical safety net. PR #193605, authored with assistance from Claude Code, updates .github/labeler.yml to automatically attach the ciflow/b200 label to any PR touching CuTeDSL or DLPack-related files. CuTeDSL receives its tensors through the DLPack interface, yet its existing label paths were matmul/blas-only—meaning DLPack and DSL changes had zero CuTeDSL coverage before merge. That gap allowed a real bug to slip through: #182924 exported a nonzero byte_offset that tvm-ffi rejects, and it merged with a clean 421 CI checks.

The new labeler solves this by ensuring any changes to files like DLConvertor.cpp, torch/utils/dlpack.py, and test/test_dlpack.py trigger B200 GPU testing. Notably, torch/_tensor.py—which owns the __dlpack__ method—is deliberately left out because it changes too frequently for unrelated reasons and would over-trigger the expensive B200 job. The PR was verified via YAML parse and lintrunner, and approved by drisspg. For maintainers, this means integration-level bugs on NVIDIA's Blackwell B200 architecture get caught at PR time instead of surfacing after merge.