* fix: add XPU device support and update hardcoded CUDA selections
* fix: add XPU device support for pytest CUDA skipped tests
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* Fix device handling for PR #7401
- perplexity_eval.py: use DEVICE_TYPE_TORCH, not DEVICE_TYPE. The latter can
be "hip" or "mlx", which .to() rejects, so this regressed ROCm.
- test_batched_leftpad_generation_gpu.py: XPU diverges here today, so mark it
non-strict xfail on XPU instead of reverting to a CUDA-only guard. Keeps the
real XPU gap visible and turns green once it is fixed.
- Guard torch.xpu.is_available() with hasattr, matching device_type.py.
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* Re-enable the flash varlen attention test in CI for PR #7401
attention_dispatch.py now predefines flash_attn_func / flash_attn_varlen_func
as None, so test_run_attention_flash_varlen_receives_window_and_softcap no
longer needs flash_attn importable to be monkeypatched. Verified on a runner
shaped like the CPU-only one: the test fails against main's attention_dispatch
and passes at this head, so the deselect is now dead weight.
* Tighten comments for PR #7401
Drop the hasattr rationale: torch.xpu has existed since torch 2.3 and the
dependency floor is 2.4, so no supported build predates the namespace. The
guard stays as cheap defence, but the comment claimed something untrue.
---------
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* Fix text-only VLM CPT packing truncation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Handle streaming vision datasets in packing
* Harden multimodal packing detection
* Preserve safe packing boundaries
* Scope stream packing checks to VLMs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Narrow VLM packing detection
* Align packing mode and eval safety
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Add qwen3_5/qwen3_next to PADDING_FREE_BLOCKLIST to avoid packed-sequence contamination
* Detect hybrid linear-attention models structurally instead of by name for packing guard
* Add experimental varlen packing for hybrid linear-attention models
Feed seq_idx to the causal conv and cu_seqlens to the gated-delta scan so
sample packing / padding-free reset state at sequence boundaries for hybrid
linear-attention models (Qwen3.5, Qwen3-Next). Gated behind
UNSLOTH_EXPERIMENTAL_HYBRID_PACKING and fail-closed: when the flag is off or
the accelerated kernels (causal_conv1d + fla) are unavailable, the guard keeps
these models on the padded path.
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* Harden hybrid linear-attention varlen packing shim
Make patch_hybrid_linear_attention_varlen robust across transformers 4.57.6
through 5.x and TRL 0.22.2 through 1.x, following the import_fixes.py style:
- Read UNSLOTH_EXPERIMENTAL_HYBRID_PACKING at call time so the flag takes effect
when set after importing unsloth.
- Idempotent: repeat calls on a patched model return True without re-validating
the wrappers or double-wrapping; signatures are checked on captured originals.
- Prefer the authoritative packed_seq_lengths (via get_packed_info_from_kwargs)
over position_ids resets, handling pad_to_multiple_of trailing tokens.
- Suppress injection for cached forwards (use_cache / past_key_values) so
generation and eval are left on the untouched decode path.
- Validate every gated-delta module before mutating any (transactional).
- Bind position_ids / use_cache from both positional and keyword args.
- Verify dispatch at runtime (Unsloth wraps each module forward, so the mixer
source is not statically inspectable) and warn once if the shim is never hit.
- Emit one deduped diagnostic on each fail-closed path.
Add CPU unit tests covering the hybrid guard detection, the boundary builders,
and the shim (fail-closed, active, idempotent, cached no-op, runtime handshake).
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* Abort hybrid packing when the varlen shim is not fully dispatched
The runtime handshake used a single per-module hit flag written by both the conv
and scan wrappers, so a partial dispatch (only one kernel routed through
self.<kernel>) passed the any() check and trained on contaminated data, and a
missing dispatch only logged a warning. Track conv and scan dispatch separately,
require both on every gated-delta module on the first packed forward, and raise
before loss/backward when either is missing (the batch is already flattened, so
there is no padded recovery at that point). Also skip an empty packed_seq_lengths
before it reaches max(), and document the position_ids fallback's left-pad
assumption.
Add tests for no-dispatch and partial (conv-only / scan-only) abort, the
packed_seq_lengths preference over a competing position_ids, MRoPE 3D position
ids, and the pad_to_multiple_of trailing-segment path through the metadata builder.
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* Import the hybrid packing patch from its submodule to satisfy the import-hoist lint
* Fail closed for hybrid packing on encoder-decoder, chunked-loss, and string-name models
The varlen shim only helps decoder-only hybrid models that run their mixer
through self.<kernel> on a live nn.Module forward. Three cases slipped past
the guard:
- Encoder-decoder configs (is_encoder_decoder) reached the packing path even
though flattening a cross-attention batch is unsound. Block them explicitly.
- TRL's chunked_nll loss (the 1.x default) calls the backbone directly and
bypasses model.forward, so the per-instance forward wrapper that refreshes
the varlen stash never runs. Detect that path and keep the model padded.
- A string model_name reaches the trainer before the module exists, so the
instance shim has nothing to patch. Resolve the config up front and keep
string hybrids on the padded path.
Adds encoder-decoder / decoder-only / chunked-loss / string-model tests.
* Harden the SFT source-injection replacements and forward auth args for string models
The wrapped-packing injection rewrote the sourced unsloth_zoo sft_prepare_dataset
with str.replace anchored on the exact 'All Unsloth Zoo code licensed under
LGPLv3' comment. str.replace never raises on a missing anchor, so a supported
newer unsloth_zoo (the dependency is only lower-bounded) that moved that header
would silently drop the setup while the truncation and pack_dataset edits still
referenced _unsloth_wrapped_packing / _inspect, raising NameError on every SFT
dataset preparation.
- Install the setup at the sft_prepare_dataset signature via re.subn (a structural
anchor that always exists) and raise if even that is missing.
- Route the remaining edits through a _require_replace helper that fails loudly on a
missing required anchor (or warns once for an optional one), formalizing the
verify-then-replace idiom the DPO patchers in this file already use.
- Reuse the guarded _unsloth_pack_has_strategy at the pack_dataset call instead of
re-calling inspect.signature(pack_dataset) unguarded, so a non-introspectable
pack_dataset cannot crash there after the setup already handled it.
- _resolve_string_model_config now forwards token / use_auth_token / cache_dir /
code_revision, so a private hybrid resolves its config instead of falling through
as non-hybrid and enabling packing without the varlen shim.
Adds regression tests for the drift-resistant injection, the helper, and the
string-model auth forwarding.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Honor top-level SFTConfig.trust_remote_code when resolving a string model
TRL merges the top-level args.trust_remote_code into the load via
model_init_kwargs.setdefault("trust_remote_code", args.trust_remote_code) before
create_model_from_path, so a remote-code hybrid is commonly set with
SFTConfig(trust_remote_code=True) rather than inside model_init_kwargs. The config
probe only read model_init_kwargs, so AutoConfig could fail for such a model, leave
model_config None, and let the guard treat it as non-hybrid, enabling packing
without the varlen shim. Mirror TRL's setdefault (model_init_kwargs wins).
* Tighten hybrid-packing comments for concision
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---------
Co-authored-by: alkinun <alkinunl@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Etherl <61019402+Etherll@users.noreply.github.com>
* Fix text-only VLM CPT packing truncation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Handle streaming vision datasets in packing
* Harden multimodal packing detection
* Preserve safe packing boundaries
* Scope stream packing checks to VLMs
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Narrow VLM packing detection
* Align packing mode and eval safety
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add qwen3_5/qwen3_next to PADDING_FREE_BLOCKLIST to avoid packed-sequence contamination
* Detect hybrid linear-attention models structurally instead of by name for packing guard
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Install wrapped-packing setup at the signature, not the Zoo license comment
The _unsloth_wrapped_packing / _inspect setup block was injected by matching the
exact 'All Unsloth Zoo code licensed under LGPLv3' comment line in the sourced
sft_prepare_dataset. The unsloth_zoo dependency is only lower-bounded, so a newer
Zoo that moves or drops that header made the setup a silent no-op while the
truncation and pack_dataset rewrites still emitted references to those names,
raising NameError on every SFT dataset preparation.
Anchor the setup on the function signature instead (a structural location that
always exists) and fail loudly if it cannot be found, so the helper variables are
always defined before they are referenced across Zoo versions.
Adds a regression test that patches in a Zoo source without the license header.
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Co-authored-by: Etherl <61019402+Etherll@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
* Reduce and tighten comments and docstrings in tests
Shorten verbose comments and docstrings across the test suite without
changing any test logic. Remove narration that restates the next line,
collapse long module and test docstrings to a single line, and drop banner
separators. Keep regression context (issue and PR references, run ids),
skip reasons, mocking and timing rationale, license headers, lint and type
directives, and commented-out code.
Comments and docstrings only: an AST signature check confirms no code,
assertions, or string literals changed, and the suite byte-compiles cleanly.
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Trim and tighten code comments and docstrings across the repository. Comment-only: every changed file verified code-identical to main via AST/token comparison.
Raise ruff line-length to 100 and extend the local pre-commit format pipeline (def-signature magic-comma normalization, short multi-line assert collapse, kwarg '=' spacing, blank-line-after-short-import removal, adjacent string-literal / f-string+plain merge, redundant-pass pruning). Every transform re-checks the file AST and is dropped if it would differ; the whole-repo reformat is verified AST-identical per file and idempotent.
* Refactor Ollama template wiring and harden packing helpers
Signed-off-by: Mohammad Miadh Angkad <MAngkad.BSDSBA2027@aim.edu>
* Fix Qwen3 and Gemma3n template bindings and tidy packing test helper
* Fix gptoss Ollama comment and tinyllama stop parameter
- Fix wrong comment referencing gemma3n for gptoss_ollama in chat_templates.py
- Add missing stop keyword to tinyllama PARAMETER in ollama_template_mappers.py
* Fix _DummyTrainer compatibility across TRL versions
The try/except only handled the removal of return_position_ids
(TRL v0.24+) but not the absence of padding_free (TRL v0.18.2).
Gracefully degrade through all optional collator flags so the
test works from trl>=0.18.2 through v0.27+.
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---------
Signed-off-by: Mohammad Miadh Angkad <MAngkad.BSDSBA2027@aim.edu>
Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
JoshuaL3000