* fix CI fallout from MLX subpackage refactor (#634)

Three small fixes triggered by tests on PRs #645 / unsloth#5426:

1) tests/test_upstream_pinned_symbols_accelerator.py read the legacy
   flat unsloth_zoo/mlx_trainer.py and mlx_loader.py paths directly.
   #634 moved those to unsloth_zoo/mlx/trainer.py and mlx/loader.py;
   point the tests at the new paths so they exercise the post-refactor
   sources.

2) unsloth_zoo/vision_utils.py:68 did an unconditional top-level
   import torchvision while torchvision is not a declared dependency.
   On a CPU-only install that lacks torchvision (e.g. zoo's Core CI
   matrix), every import of unsloth_zoo.vision_utils raises
   ModuleNotFoundError. Guard the import so the module loads; existing
   _read_video_torchvision call sites already only fire when video
   reading is requested.

3) tests/test_zoo_source_upstream_refs.py tries to resolve transformers
   qwen2_vl / qwen2_5_vl image-processing modules, both of which
   transitively `import torchvision`. Skip via pytest.importorskip
   when torchvision is not installed instead of failing the run.

Each fix is independent and minimal; no behavior change for installs
that have torchvision (the eager import path is identical), and no
behavior change for the MLX trainer / loader (the tests still pin
the exact same source-level invariants on the new file paths).

* tests/conftest: also stub unsloth.device_type on CPU-only runners

The post-#634 conftest stubs ``unsloth_zoo.device_type`` so importing
the package on a CPU-only CI runner doesn't trip ``get_device_type()``.
``test_unsloth_trainer_exec_marker`` (and any future test that does
``import unsloth.*``) goes one level up: it imports ``unsloth.trainer``,
which traverses ``unsloth/__init__.py`` → ``_gpu_init`` → ``unsloth/
device_type.py:get_device_type()``, raising the same NotImplementedError
zoo's stub was meant to suppress.

Parameterise ``_preload_real_device_type(package, prereqs)`` so the
same harness works for both packages, factor the fallback into
``_install_device_type_stub(name)``, and call both. unsloth's
``get_device_type()`` consumes ``unsloth_zoo`` helpers but has no
intra-unsloth prereqs, hence ``prereqs=()`` there.

* tests/conftest: don't stub unsloth.device_type after all

The previous commit (196a78b) stubbed unsloth.device_type so
test_unsloth_trainer_exec_marker could complete its
``import unsloth.trainer`` smoke. That makes ``import unsloth`` succeed
on CPU-only CI, which then runs
``unsloth/_gpu_init.py:_patch_trl_trainer()`` and rebinds
``trl.trainer.sft_trainer.SFTTrainer`` /
``transformers.models.ministral.MinistralAttention`` to Unsloth's
compiled wrappers.

``inspect.getsource(...)`` on those classes follows the wrapper's
``__init__.__code__.co_filename`` and returns the rewritten source --
which doesn't contain the literals the drift detectors anchor on
(``self._signature_columns``, ``self._prepare_dataset(``,
``class SFTTrainer``, named ``hidden_states``/``attention_mask``).
The HF=4.57.6 job went from -1 pre-existing failure
(``test_unsloth_trainer_exec_marker``, also failing on main) to -4 new
failures across ``test_MinistralAttention_forward_signature`` and the
three ``test_unsloth_rl_trainer_*`` checks. That's a regression.

Keep parameterised ``_preload_real_device_type`` and
``_install_device_type_stub`` -- they're harmless infrastructure and
useful if a future test needs the unsloth.device_type stub
specifically. Just don't fire the second preload at session setup.

``test_unsloth_trainer_exec_marker`` will continue to fail on
CPU-only CI as it does on main; that's a separate pre-existing issue
with ``unsloth/device_type.py`` raising on accelerator-less hosts and
should be fixed upstream in unsloth itself, not papered over in zoo's
conftest.

* device_type: mirror UNSLOTH_ALLOW_CPU=1 gate from unsloth #5429

unsloth/_gpu_init.py:125 imports DEVICE_TYPE from unsloth_zoo, not
local unsloth/device_type.py, so the env-var gate has to live here
too for `import unsloth.trainer` to succeed on CPU-only CI.

The companion unsloth PR landed as cb15a7a (#5429). Pairs with the
conftest change in this branch that sets UNSLOTH_ALLOW_CPU=1 before
triggering `import unsloth` from _apply_upstream_import_fixes_for_tests.

@functools.cache on get_device_type plus the module-level
DEVICE_TYPE = get_device_type() assignment mean the os.environ.get
runs exactly once per process. Production hosts with a real accelerator
hit the `cuda`/`xpu`/`hip` branches above and never reach the env-var
short-circuit.

* prod: graceful no-op for two transformers 5.x runtime bugs

Two upstream changes broke zoo at runtime (not just CI drift detection):

1. transformers 5.x removed transformers.cache_utils.HybridCache. zoo's
   utils.py falls back to `HybridCache = typing.Any`, which made
   `gemma.py:260 isinstance(past_key_values, HybridCache)` raise
   TypeError ("isinstance() arg 2 must be a type, a tuple of types,
   or a union") at runtime on the gemma mask path.

   Fix: expose HAS_HYBRID_CACHE alongside the existing HybridCache
   fallback in utils.py, and gate the isinstance call in gemma.py:260
   on the flag. When HybridCache is genuinely missing, the elif chain
   falls through to the dynamic-cache branch -- same observable
   behavior as the pre-5.x path that never matched the type.

2. transformers 5.x rewrote PreTrainedModel.save_pretrained. The
   source-string anchors zoo's LoRA-merge-on-save optimization patches
   in `merge_and_dequantize_lora` (state_dict_split assignment,
   `state_dict[tensor].contiguous()`, `def save_pretrained`, and the
   filename_to_tensors for-loop on the push_to_hub path) are all gone.
   Each downstream `raise RuntimeError("Failed to find ...")` would
   fire, killing `merge_and_dequantize_lora(push_to_hub=True)` on 5.x.

   Fix: scan all required anchors upfront in saving_utils.py. If any
   are missing on installed transformers, emit a one-time warnings.warn
   and fall back to vanilla `model.save_pretrained(...)`. The end-user
   sees the warning, no crash, and is told to call
   `model.merge_and_unload()` (or equivalent) before saving if they
   want merged LoRA weights on disk. The per-anchor RuntimeError
   raises downstream are kept as defense-in-depth for partial drift
   (one anchor renamed, others intact) that the upfront check might
   miss.

The two corresponding drift detectors in tests/ are rewritten in the
companion commit as positive assertions: 4.57.6 keeps the strict
existence check; 5.x asserts the anchor is gone AND zoo's fallback
covers it (`HAS_HYBRID_CACHE` flag / `_required_anchors` list).

* tests: version-gate transformers-5.x drift detectors

Sixteen drift detectors in the Core HF=default / HF=latest matrix
slices were pointing at upstream symbols / source strings that
transformers 5.x intentionally removed:

* 9 `temporary_patches/*_for_causal_lm_forward_named_params` --
  cache_position moved from named forward param into
  **kwargs: Unpack[TransformersKwargs] (DeepseekV3, GptOss, CsmDepth,
  Csm, Qwen3Moe, Qwen3Next, Qwen3VLMoe, MinistralModel, GraniteMoeHybrid).
* 4 compiler/source rewriter probes -- output_attentions branching
  removed, MoE routing_weights cast refactored, Trainer
  is_torch_tpu_available/is_torch_xla_available both removed,
  _update_causal_mask hasattr probe all-False.
* 1 routing_weights.to substring probe in compiler_rewriter_exhaustive.
* 1 GptOssConfig dedent-compare -- rope_theta/initial_context_length/
  rope_scaling collapsed into rope_parameters dict.
* 1 GptOssConfig kwarg signature -- same rope_theta rename.

For all 16, the zoo runtime patch already gracefully no-ops on 5.x
(verified by the Explore audit: try/except + relaxed patch_function +
hasattr guards + str.replace's silent no-op-on-miss). Skip the
detector on 5.x with a clear "<symbol> removed on transformers
{version}" message; keep it strict on 4.57.6 where real drift could
still surface.

Two more drift detectors -- test_hybrid_cache_class_present and the
two saving_utils.py pinned-string tests -- become positive assertions:
on 5.x they confirm zoo's prod fix correctly identifies the missing
anchor (HAS_HYBRID_CACHE is False / `_required_anchors` covers the
missing strings) and the graceful fallback is wired up.

Conftest also sets UNSLOTH_ALLOW_CPU=1 before the existing
`import unsloth` trigger, which unblocks `test_unsloth_trainer_exec_marker`
on CPU-only CI runners (the companion unsloth PR #5429 lets that
import succeed without an accelerator).

* tests: also gate test_MinistralAttention_forward_signature on 5.x

Missed this one in 18c9f62. Same root cause as MinistralModel:
transformers 5.x reflowed MinistralAttention.forward, zoo's
``patch_function(..., match_level='relaxed')`` falls back to a
``(self, *args, **kwargs)`` wrapper, the named-param probe sees the
wrapper signature and drift-fails. Runtime call still works because
the wrapper forwards via kwargs. Skip on 5.x, keep strict on 4.57.6.

* tests: probe Ministral stash + skip relaxed-wrapper case

Zoo's ministral.py:94-96 wraps the actual implementation in a generic
``def forward(self, *args, **kwargs): return _full_forward(...)``
adapter before calling patch_function -- this lets `check_args_kwargs`
accept params transformers 5.x removed (cache_position) by routing
them through **kwargs. The side effect: `inspect.signature(
MinistralAttention.forward)` after patching shows the wrapper, not the
real named params.

This test used to pass only because the test runner couldn't fully
trigger zoo's TEMPORARY_PATCHES loop (`unsloth/models/_utils.py:580`
runs at import time but unsloth import was being silently aborted).
With UNSLOTH_ALLOW_CPU=1 now making `import unsloth` succeed, the
patch fires correctly and the live signature is the wrapper.

Fix: probe the `_original_modeling_ministral_MinistralAttention_forward`
stash that `patch_function(store_original=True)` writes, falling back
to the live attribute. If the live attr is the relaxed wrapper and
there's no stash, the named-param probe isn't meaningful -- the
runtime kwargs contract is enforced elsewhere. Skip with a clear
message. 4.57.6: stash is present and the named-param probe still
runs strict; real drift in the upstream signature still surfaces.

* tests: gate qwen2_5_vl image-processor drift on 5.x

transformers 5.x dropped the slow image processors entirely
(image_processing_qwen2_5_vl.py and image_processing_qwen2_5_vl_fast.py
are both gone in v5.5.0). Qwen2.5-VL now reuses Qwen2VLImageProcessor
directly. zoo's misc.py:1500-1506 patch site for Qwen2_5_VLImageProcessor
is try/except ImportError-wrapped, so it silently no-ops on 5.x and the
runtime shim still fires via the Qwen2VLImageProcessor patch at
misc.py:1485-1498 (the class Qwen2.5-VL inherits at runtime).

The Qwen2.5-VL image-processor path was previously hidden by
``pytest.importorskip("torchvision")`` -- PR #648 added torchvision to
the upstream-regression matrix install, which unmasked the drift.
Runtime is unaffected. Add the same 5.x skip pattern used by the other
16 gated detectors so the dead-code patch site doesn't block CI.

4.57.6 keeps the strict path-existence check.