0f2f4334e2
The start-route preflight caught the bf16-GPU and int8-torchao requirements but not the dense precisions' CUDA requirement: on a GPU-less host bf16_unsupported_reason exempts CPU-only, so a bf16/fp8 (or int8-with-torchao) DiT request passed the preflight, evicted resident workloads, then raised only in the trainer child. Add the dense-mode CUDA gate mirroring _resolve_base_precision so the doomed run is rejected up front. Also pin bf16_unsupported_reason in the two positive-path family-info tests so they are deterministic across GPU types (a non-bf16 CUDA box would otherwise empty every DiT family's advertised modes). |
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| .. | ||
| assets | ||
| auth | ||
| core | ||
| hub | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| storage | ||
| tests | ||
| utils | ||
| __init__.py | ||
| _platform_compat.py | ||
| cloudflare_tunnel.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||
| startup_banner.py | ||