supports_fp8_compute() and supports_nvfp4_compute() used the global
is_nvidia() check which ignores the device argument, then defaulted
to cuda:0 when device was None. In heterogeneous multi-GPU setups
(e.g. RTX 5070 + RTX 3090 Ti) this causes the wrong GPU's compute
capability to be checked, incorrectly disabling fp8 on capable
devices.
Replace the global is_nvidia() gate with per-device checks:
- Default device=None to get_torch_device() explicitly
- Early-return False for CPU/MPS devices
- Use is_device_cuda(device) + torch.version.cuda instead of
the global is_nvidia()
Fixes#4589, relates to #4577, #12405
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
All past 30 min of comtts are done on the top of Mt Fuji
By Comfy, Robin, and Yoland
All other comfy org members died on the way
Introduced unit tests to verify the correctness of various folder path
utility functions such as `get_directory_by_type`, `annotated_filepath`,
and `recursive_search` among others. These tests cover scenarios
including directory retrieval, filepath annotation, recursive file
searches, and filtering files by extensions, enhancing the robustness
and reliability of the codebase.
