Two cleanups derived from review of the matrix output:
1. Skip false-positive zero-arg patches in the runtime ledger.
Three patches have all-defaulted signatures but require either
runtime args or real CUDA, so calling them in isolation produces
a meaningless failure:
- patch_linear_scaling: defaults are None placeholders;
body starts with `assert rope_module is not None` etc.
- patch_llama_rope_scaling: same shape.
- patch_unsloth_smart_gradient_checkpointing: legitimately
allocates CUDA tensors via aten::empty.memory_format inside
initialize_unsloth_gradient_checkpointing(); the torch.cuda.*
Python spoof can't intercept that at the dispatcher level.
Add NEEDS_PRECONDITION = {...} to the shim and skip those by name.
Symbol presence is still verified via REQUIRED.
2. Drop the job-level `continue-on-error: true`.
Previously the cell reported SUCCESS even when steps failed, which
made the PR check UI lie. Real failures now turn the cell red.
Per-step `continue-on-error: true` stays so a single failed step
does not cascade and skip the rest of the ledger.
Three other failures the matrix surfaced are addressed by separate PRs
to source:
- unslothai/unsloth#5319 (patch_fast_lora missing import,
patch_sft_trainer_tokenizer Union NameError, openenv OSError)
- unslothai/unsloth-zoo#628 (skip MoE coverage on older transformers)
433cfa93d7