[cuda.core] test_graphics.py fails on headless multi-GPU Linux: EGL device does not match current CUDA device #2864

Problem

cuda_core/tests/test_graphics.py fails on headless Linux systems with multiple GPUs. The test fixture initializes CUDA Device(0) (subject to CUDA_VISIBLE_DEVICES), but pyglet's headless EGL backend selects its own default EGL device independently -- CUDA_VISIBLE_DEVICES reorders CUDA's device enumeration but has no effect on EGL's.

On systems where CUDA device 0 and EGL device 0 are different physical GPUs, cuGraphicsGLRegisterBuffer() / cuGraphicsGLRegisterImage() fail with CUDA_ERROR_INVALID_DEVICE, because CUDA-OpenGL interop resources must be registered on the CUDA device associated with the GL rendering context.

Repro environment

• Linux headless (no DISPLAY/WAYLAND_DISPLAY)
• 2x NVIDIA RTX PRO 6000 Blackwell Server Edition
• CUDA Toolkit 13.3.1, driver 610.43.02
• cuda-core 1.2.0, cuda-bindings 13.3.1, pyglet 2.1.14
• Python 3.10-3.14t

Observed

144 failures across 6 Python environments (24 test_graphics.py cases per env). Device-mapping validation showed the pass/fail pattern flips with CUDA_VISIBLE_DEVICES and PYGLET_HEADLESS_DEVICE, confirming EGL device index and CUDA device ordinal diverge on this class of system rather than differing by a fixed offset.

Not a regression in GraphicsResource -- the underlying CUDA/EGL device mismatch existed in cuda-core 1.1.0 too but was masked because those tests were skipped there.