Two enhancements:
1) Matrix over (transformers, trl) version combos
The single-cell job becomes a 3-cell matrix:
- "T 4.57.6 + TRL <1": pinned transformers==4.57.6 with the latest TRL
in the 0.x line (resolves to 0.29.1 today). The just-before-5.x baseline.
- "T latest 5.x + TRL latest 1.x": absolute upstream tip on both. Today
that resolves to transformers 5.8.0 + trl 1.3.0 -- both BEYOND
unsloth/unsloth_zoo's <=5.5.0 / <=0.24.0 caps. The cell exists
explicitly to surface drift signal.
- "pyproject.toml pins (dynamic)": resolves the spec from pyproject.toml's
[project.optional-dependencies][huggingfacenotorch] (where unsloth
actually pins transformers + trl; top-level [project.dependencies]
is just typer/pydantic). Resolves to:
transformers>=4.51.3,!=4.52.{0,1,2,3},!=4.53.0,!=4.54.0,!=4.55.{0,1},!=4.57.{0,4,5},!=5.0.0,!=5.1.0,<=5.5.0
trl>=0.18.2,!=0.19.0,<=0.24.0
`fail-fast: false` so each cell runs independently. Pinned `pytest==9.0.3`
across cells avoids collection-behavior drift.
2) Aggressive CUDA spoof helper
New file tests/_zoo_aggressive_cuda_spoof.py extends tests/conftest.py:84-141's
import-time harness with deeper patches:
- Device topology: device_count, current_device, get_device_name,
get_device_properties (SimpleNamespace-style, A100-shaped: cap=(8,0),
80 GiB), is_initialized, set_device, synchronize, empty_cache.
- cudart() wrapper: cudaMemGetInfo / cudaGetDeviceCount / cudaSetDevice.
- memory module: mem_get_info, memory_stats, memory_allocated,
max_memory_allocated, memory_reserved, max_memory_reserved,
reset_peak_memory_stats.
- nvtx: range_push / range_pop / mark no-op stub.
- random API: cuda.manual_seed{,_all}, get_rng_state{,_all},
set_rng_state{,_all} routed to torch CPU RNG.
- Stream / Event no-op classes.
- pin_memory drop: torch.{empty,zeros,ones,empty_like,zeros_like,
ones_like,rand,randn,randint} wrappers strip pin_memory=True kwarg
(CUDA-host fast-copy has no meaning on a CPU runner; downgrading
silently is the right behavior here). Tensor.pin_memory() / is_pinned
no-op.
- amp.GradScaler stub if torch.cuda.amp doesn't import.
Locally validated effect on the runtime patch_* check:
- Without spoof: 50 OK / 6 FAIL (run #7 ledger)
- With aggressive spoof: 51 OK / 3 FAIL
The 3 remaining failures are real source bugs not CUDA-related:
- unsloth.models._utils.patch_fast_lora -> NameError 'fast_lora_forward'
- unsloth.models._utils.patch_linear_scaling -> bare AssertionError
- unsloth.models._utils.patch_llama_rope_scaling -> bare AssertionError
The three shim test files (_zoo_apply_fused_lm_head_shim.py,
_runtime_patch_check_shim.py, _tiled_mlp_check_shim.py) now import the
spoof helper before any unsloth_zoo import.
Drop `pip show … | head -2` from the post-install version printout in
favor of bare `pip show` (head -2 closes the pipe early under pipefail
and emits exit 120, see the run-#5 fix).
b972214210