* Fix FlashAttention fp32 crash with DoRA (use_dora=True)
DoRA upcasts lora_magnitude_vector to fp32 for the optimizer, which promotes
the q/k/v_proj output to fp32. FlashAttention only accepts fp16/bf16, so the
fp32 q/k/v raised 'FlashAttention only support fp16 and bf16 data type'.
Downcast q/k/v to the compute dtype before the flash kernels.
Fixes#1013
* Apply kwarg-spacing format hook to DoRA dtype test (pre-commit)
* DoRA+FA2: downcast any fp32 among Q/K/V and clamp to a flash-supported dtype
* Tighten code comments (no logic change)
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Fix misleading 'only for image models' error for Qwen3-VL when torchvision is missing
transformers >= 5.4 hard-requires torchvision for VLM image/video processors and
no longer falls back to a slow processor. Without torchvision the processor load
raises ImportError, unsloth degrades to a text-only tokenizer, and the vision data
collator later fails with 'UnslothVisionDataCollator is only for image models!'.
Detect this case at load time and raise a clear, actionable error pointing at the
missing torchvision dependency instead.
Fixesunslothai/unsloth#4202
* Apply kwarg-spacing format hook to vision torchvision guard (pre-commit)
* Make torchvision-missing detection precise: check availability first, match specific error text
* Tighten code comments (no logic change)
* Make missing-torchvision VLM error version-agnostic
The raise also fires on transformers 4.57.x for VLMs with a video processor
(Qwen2.5-VL, Qwen3-VL), where AutoVideoProcessor requires torchvision. The old
message claimed 'transformers >= 5.4 requires torchvision', which is inaccurate
on 4.57.x. Reword to state torchvision is required for this model's vision
processors without a version-specific claim.
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* fix: use EMPTY_LOGITS on the fused-CE not-return_dict path (#2068)
CausalLM_fast_forward's fused cross-entropy path (small batch, labels set,
UNSLOTH_RETURN_LOGITS off) computes the loss straight from hidden_states
via unsloth_fused_ce_loss and never materializes `logits`. The
return_dict=True branch returns EMPTY_LOGITS, but the `not return_dict`
branch returned `(logits,) + outputs[1:]`, raising
"UnboundLocalError: cannot access local variable 'logits'" whenever it ran
(e.g. training with return_dict=False). Same bug in the llama and mistral
fast-forward paths.
Return EMPTY_LOGITS on that branch too, matching the adjacent return_dict
output. Verified on GPU: a forward(return_dict=False, labels=...) that
raised UnboundLocalError now returns (loss, EMPTY_LOGITS, ...) and
backward() succeeds.
Adds tests/test_fused_ce_not_return_dict_logits.py, a CPU source-drift guard
(the fused path itself is GPU/triton only) asserting both fast-forward paths
keep using EMPTY_LOGITS there.
* Address review: parse the fused-CE drift line with whitespace-tolerant regexes
The drift detector sliced the source with exact string matching
(source.index("output = (") + the next newline), so a formatter respacing or
rewrapping the assignment would break the parse. Switch to anchored regexes that
tolerate whitespace and line wrapping, keeping the match anchored after the
fused guard so it targets the fused-CE branch and not the normal
output = (logits,) path. Behavior and the two drift assertions are unchanged.
* Tighten code comments (no logic change)
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
* studio/setup.sh: guard empty CUDA arch detection in the source build
PR #5826 hardened setup.sh for fresh CUDA toolkits, but the source build
still set -DCMAKE_CUDA_ARCHITECTURES only when nvidia-smi reported a
compute capability. When that query returns nothing the build proceeded
with no explicit arch list, so llama.cpp built PTX only. On a driver older
than the toolkit that binary fails at runtime with "the provided PTX was
compiled with an unsupported toolchain" - the build succeeds, so neither
the build-time check nor the CPU fallback caught it (issue #5854).
Resolve the arch list before committing to a CUDA build. A new pure helper
_resolve_cuda_archs parses and de-duplicates the nvidia-smi compute_cap
output and honors an explicit UNSLOTH_LLAMA_CUDA_ARCHS override. When the
result is empty, build CPU llama.cpp instead of a PTX-only binary, with a
clear message pointing at the override - so the user still ends up with a
working llama-server. The override also lets advanced users force a native
build on hosts where nvidia-smi cannot report compute_cap.
No behavior change when an arch is detected: -DGGML_CUDA=ON plus the arch,
CUDA flags and NVCC_PREPEND_FLAGS are assembled exactly as before.
Adds tests/sh/test_resolve_cuda_archs.sh (single/multi/dedup/empty/garbage/
whitespace/override cases), wired into tests/run_all.sh and the
studio-backend-ci.yml shell-test loop.
* studio/setup.sh: resolve nvidia-smi via /usr/bin fallback for arch detection
Addresses review feedback on the empty-CUDA-arch guard: _setup_has_usable_nvidia_gpu
classifies a host as NVIDIA-usable using nvidia-smi on PATH OR /usr/bin/nvidia-smi,
but the new arch detection probed only `command -v nvidia-smi`. On a GPU host where
nvidia-smi is off PATH (reachable only at /usr/bin), arch detection returned empty
and the new empty-arch branch dropped the build to CPU, losing CUDA. Mirror the same
PATH-then-/usr/bin resolution so those hosts still get a native CUDA build.
Also scope _resolve_cuda_archs locals with `local` (no behavior change; it already
runs under command substitution).
* tests: update compute_cap-probe assertion for $_smi_bin resolution
The nvidia-smi /usr/bin fallback parameterized the binary in the compute_cap
probe (_setup_run_smi "$_smi_bin" ...), so the literal-string assertion in
test_compute_cap_probe_timeout_wrapped no longer matched. Assert the probe is
preceded by _setup_run_smi (timeout-wrapped) instead, scanning all occurrences
so the comment mention is ignored. Same intent, binary-agnostic.
* tests: ruff-format the compute_cap probe assertion (pre-commit)
Collapse the backslash-continued assert onto one line and normalize slice
spacing so the ruff-format pre-commit hook (0.6.9) is satisfied. Formatting
only; no behavior change.
* Tighten code comments (no logic change)
* studio(windows): build CPU when CUDA arch is undetectable (#5854)
The Windows source build added -DGGML_CUDA=ON unconditionally but only set
-DCMAKE_CUDA_ARCHITECTURES when $CudaArch was detected. With no detectable
compute capability that produced a PTX-only binary, the same hole the Linux
fix closed. Build CPU llama.cpp in that case, and honor UNSLOTH_LLAMA_CUDA_ARCHS
to force a CUDA build, matching setup.sh. Detected-arch builds are unchanged.
* test: anchor NVCC_PREPEND_FLAGS scope check on the final CPU branch
The undetectable-arch CPU fallback adds an earlier -DGGML_CUDA=OFF, so the
ordering check now anchors on -DGGML_CUDA=ON and the last -DGGML_CUDA=OFF
instead of the first.
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
* Studio Playwright: snooze update banner before sending
The llama.cpp update banner is a fixed bottom-right toast (z-9998). When an
update is available it overlaps the composer's Send button and its subtree
intercepts the click, so send_and_wait times out (flaky; surfaces on the
Windows studio UI smoke, passes otherwise). Snooze the banner if it is
showing before each send, then wait for it to detach.
* Also snooze the web update banner before sending
The web update banner (web-update-banner, z-9999) is a fixed bottom-right
toast like the llama.cpp one and can overlap the Send button too. Loop over
both banners and snooze whichever is showing.
* Add HF dataset streaming mode to Studio
* Added default value for datasetStreaming in training-config-store.ts
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Handle None max_steps for streaming validation
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fast-fail streaming validation and guard incompatible modes
Reject dataset_streaming at the API boundary when hf_dataset is empty,
the dataset is vision/audio, or max_steps is not set. Probe eval split
with get_dataset_split_names before the streaming load so typos fail
immediately instead of mid-training. Guard column_names=None after map
on iterables. Hide the UI toggle for non-text configurations and clear
the stale flag when config becomes incompatible.
* studio: add streaming dataset tests, iterable helper, and streaming template/format support (WIP)
Work-in-progress on top of feat/studio-dataset-streaming-mode (PR #4946):
- new test_training_streaming.py and iterable.py dataset helper
- streaming support in chat_templates.py and format_conversion.py
- additional streaming guards in trainer.py / models / routes
- frontend streaming wiring in params-section and training-config-store
Committed to preserve uncommitted work before merging latest main.
* studio: fix review-team findings for streaming + main merge
BLOCKER: streaming + raw-text/CPT crashed on len(IterableDataset). Guard it in the
start route (reject format_type=="raw" or training_type=="Continued Pretraining")
and in isStreamingSupported (datasetFormat !== "raw").
Also:
- models/training.py: validate hf_dataset/subset/split (charset+length, block ..//);
cap dataset slice indices (le=1e9); note validator ordering
- chat_templates.py: guard _apply_custom_mapping .map() for streaming
- trainer.py: warn when packing+streaming
- training-config-store.ts: persist-migration bump to v11 (standalone datasetStreaming
backfill); add isVisionModel to NON_PERSISTED; toast on silent streamingCompatiblePatch
mutations in the 4 indirect setters
- tests: route rejections (max_steps, raw/cpt), slice cap, unsafe hf_dataset
* studio: enable raw-text/CPT dataset streaming + streaming UX polish
- raw_text: keep the lazy filter but skip len()-based row counting for
IterableDatasets so raw-text / CPT can stream; guard the eval-size log
- routes/trainer: drop the raw/CPT streaming block; add a defensive
not-streaming guard on the eval auto-split (train_test_split)
- dataset-section: streaming toggle is visible-but-disabled and lists the
exact unmet requirement(s) in its tooltip; block embedding models
- training-start-overlay: show "streaming (no full download)" instead of a
stuck download bar for streaming runs
- trim the streaming test suite to the high-value cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: address streaming review (MLX/embedding guards, sliced eval split, rehydrate timing)
- routes: reject dataset_streaming for embedding training and on Apple Silicon
(MLX); both loaders materialize the full dataset instead of streaming
- trainer: validate the base eval split name so streaming eval accepts HF slice
syntax such as "validation[:1000]"
- training-config-store: defer the onRehydrateStorage setState to a microtask so
it doesn't hit the store's TDZ during synchronous hydration
- test: streaming start rejects embedding models
* studio: harden HF dataset streaming (column_names, split slicing, empty/eval bounds, gating)
Address a deeper streaming review:
- raw_text: resolve_column_names() guards IterableDataset.column_names=None
(from_generator / unresolved features) so raw-text and CPT streaming no longer
raise TypeError before training
- models/routes: reject HF slice syntax in train_split/eval_split when streaming
(load_dataset(streaming=True) raises "Bad split"); reject mixed sources
(local/S3) and embedding/MLX streaming at the API, not just in the UI
- trainer: an empty post-slice/filter stream fails preflight with a clear message;
streaming eval is capped (STREAMING_EVAL_MAX_SAMPLES) so each eval terminates;
the manual-slice shortcut falls back to a regular load when train_split is sliced
- format_conversion: streaming conversions preflight the first mapped row so
format errors surface before training, not mid-iteration
- frontend: block streaming on Apple Silicon; clear datasetStreaming when a
dataset is detected as image/audio at start
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* studio: fix CI for streaming PR (lint blocker + no-torch sandbox + preflight test)
- trainer.py: drop unused `IterableDataset` import (hoist safety-net blocker).
- test_training_streaming.py: only select real classes (isinstance type) when
locating the trainer class, so a MagicMock-stubbed global is never passed to
object.__new__ (fixes TypeError on the Python 3.10-3.13 jobs).
- no-torch import sandboxes (test_e2e_no_torch_sandbox.py,
test_studio_import_no_torch.py): teach the chat_templates/format_conversion
exec stubs and the full-import-chain copy list about the new `.iterable`
module so the AFTER/runtime cases import without torch again.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
* Installer: respect a declined Studio auto-start and keep Ctrl+C shutdown logs ordered
The `curl | sh` Studio auto-start prompt had two issues on Linux/macOS/WSL
(install.sh). install.ps1 already gates on input redirection, so Windows is
unaffected.
1. Typing n, or any closed/EOF /dev/tty, still launched Studio. The read
fallbacks defaulted to "y" (read failure, and the no-tty branch), so any
answer other than a cleanly delivered y/n line auto-started a blocking
foreground server. Default those to "n"; a real Enter still counts as yes
via ${_reply:-y}.
2. On Ctrl+C the shell prompt printed in the middle of Studio's shutdown logs.
The non-interactive installer shell took the default SIGINT action and died
before the child finished its graceful shutdown, so the prompt raced ahead
of "All subprocesses cleaned up". trap '' INT in the installer shell so it
waits for Studio's own graceful shutdown.
* Studio: wait for the uvicorn thread before the terminal returns on Ctrl+C
Builds on #6565 by @Imagineer99. The studio server runs uvicorn in a daemon
thread, so on Ctrl+C the process could return to the shell while that thread
was still writing its shutdown logs, interleaving them with the prompt.
Retain the uvicorn thread and join it (flushing stdout/stderr) before terminal
entrypoints return, from run.py's main shutdown path and the CLI shutdown paths.
Refinements over #6565:
- Bound the join at 5s (_SERVER_SHUTDOWN_JOIN_TIMEOUT, matching the existing
_graceful_shutdown subprocess timeouts) so a stalled uvicorn shutdown cannot
hang the terminal; the timeout warning branch is now reachable.
- Restore SIG_DFL for SIGINT/SIGTERM at the start of the signal handler so a
second Ctrl+C force-quits, and drop the redundant in-handler wait (the
post-loop wait already covers the signal path).
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: keep child Ctrl+C working and restore SIGBREAK
- install.sh: run studio in a subshell that resets INT to default
(trap - INT; exec ...) so the foreground child does not inherit the
installer shell's ignored SIGINT, which would otherwise swallow the
studio process's own Ctrl+C and graceful shutdown.
- run.py: also restore SIGBREAK to SIG_DFL in the signal handler so a
second Ctrl+Break force-quits on Windows, matching SIGINT/SIGTERM.
* install.sh: capture studio exit with || under set -e so the migration hint still prints
* Trim shutdown-fix comments to be terser (comments only, no code change)
* Dedup CLI shutdown-wait into finally blocks (review follow-up)
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Add regression tests for the stray-forward compile-cache reset
Follow-up to #6511, which fixed the bug but whose squash merge did not
include the tests. These cover the two issues that fix addressed, under
the GPU-free tests/conftest.py harness:
- _unsloth_reset_stray_compile_cache is an exported module-level symbol in
unsloth.models._utils (it previously lived only inside the RL trainer
template string, so every non-RL import silently no-op'd)
- _unsloth_install_pretrain_detector keeps a recorded "seen" forward on an
idempotent reinstall with a live hook, and only resets it after teardown
- only a grad-enabled pre-train forward marks the cache poisoned
- the reset warns and clears seen when a stray forward was seen, tears the
hook down even on the clean path, and walks the .model/.base_model/.module
wrapper chain to reach a nested marker
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Pin UNSLOTH_COMPILE_DISABLE in the warn-path reset tests
The reset only warns and resets Dynamo when UNSLOTH_COMPILE_DISABLE != "1".
A GPU-free CI env that sets it to "1" would make the warn assertion in
test_reset_clears_seen_and_warns_when_a_stray_forward_was_seen flaky.
monkeypatch it to "0" in both warn-path tests so the warn / no-warn
assertions are deterministic and test the seen flag, not the env.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Windows installer: fix DiskPart UAC, drive-root cache, spurious rename warning, CPU-base messaging
amd-smi gate (DiskPart UAC mid-install): the AMD torch wheel ships hipInfo.exe
inside the venv, and the bitsandbytes fix prepends that venv Scripts dir to PATH.
shutil.which("hipinfo") then found it and flipped _amd_smi_allowed() to True, so
the post-install AMD probe fell through to `amd-smi list` (the venv hipInfo failed
to report gcnArchName, which is why the arch came from the GPU-name table) and
amd-smi elevated, popping the DiskPart UAC. Fix: a hipinfo resolved inside the
active venv (sys.prefix) is the torch-wheel binary, not a HIP SDK, and must not
open the gate. Mirrored in install_python_stack.py, install_llama_prebuilt.py, and
backend utils/hardware/amd.py (the runtime VRAM poller had the same latent prompt).
TORCHINDUCTOR_CACHE_DIR: move from C:\tc to <StudioHome>\TORCHINDUCTOR_CACHE_DIR so
the inductor/Triton cache lives under the user's Studio home, not the system drive
root. Long paths are already enabled above so deep inductor paths still fit.
unsloth.exe rename: skip the rename (and its "pip may fail with WinError 32"
warning) when SKIP_STUDIO_BASE=1. In the install.ps1 flow base packages are not
reinstalled, so unsloth.exe is never rewritten; the self-rename only failed because
setup runs via unsloth.exe (the running launcher holds its own file). The
'studio update' flow still attempts it.
CPU PyTorch messaging: clarify that the CPU base is temporary and setup replaces it
with GPU ROCm wheels, and print an explicit "GPU ROCm PyTorch installed" line after
the AMD wheels land, so the log makes clear the final install is GPU-accelerated.
Adds two regression tests covering the venv-internal vs external hipInfo gate.
Verified end-to-end on a Strix Halo box (Radeon 8060S / gfx1151): install.ps1
--local from this branch completed exit 0 with no DiskPart prompt, no rename
warning, the cache under the Studio home, and "GPU ROCm PyTorch installed
(gfx1151)"; Studio then booted and detected "ROCm (HIP 7.13.99004) -- AMD Radeon
8060S Graphics".
* Windows installer: drop the unreliable unsloth.exe rename and its WinError 32 warning
setup.ps1 used to rename the running unsloth.exe out of the way before the
base-package upgrade so pip could replace it. That rename never actually
worked: setup runs *via* unsloth.exe, so renaming our own running
uv-trampoline launcher failed with a sharing violation (WinError 32) and only
printed a scary 'could not rename unsloth.exe; pip may fail with WinError 32'
warning on every Windows install and update.
It also was not needed. pip tolerates a running/locked console-script .exe: it
moves the old one aside and writes the new one. The base upgrade routes through
pip on Windows, so the upgrade succeeds (or, in the install.ps1 flow with
SKIP_STUDIO_BASE=1, the base is not touched at all) and unsloth.exe is left
intact either way.
Removing the rename block and its failed-install restore block removes the
false warning for all Windows devices in both the install and update flows.
* Windows installer: gate venv-internal hipInfo.exe in PowerShell amd-smi probe; harden venv path checks
Follow-up to PR #6296.
- install.ps1 and setup.ps1: ignore the AMD torch wheel hipInfo.exe that lives
inside the Studio venv when probing for a HIP SDK, so amd-smi no longer reopens
the DiskPart UAC during install/update. Mirrors _path_inside_venv in the Python
installers, which already do this.
- amd.py, install_llama_prebuilt.py, install_python_stack.py: normcase the venv
containment check (Windows paths are case-insensitive) and run the
HIP_PATH/ROCM_PATH candidate through it too.
- setup.ps1: fall back to a short TORCHINDUCTOR cache dir when long paths are
unavailable, and create the dir wildcard-safely.
- tests: isolate sys.prefix in the gate helper, add HIP_PATH/ROCM_PATH cases, and
assert the PowerShell venv exclusion.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Windows installer: install ROCm PyTorch directly for a known AMD arch
When the GPU arch is known (name-inferred from the GPU-name table) but ROCm
could not be probe-verified (no HIP SDK, no amd-smi), the bootstrap installed
a CPU PyTorch base that setup.ps1 then force-reinstalled as ROCm. The
repo.amd.com wheels bundle their own runtime (no HIP SDK required), which
setup.ps1 already relies on, so the CPU base was a pure wasted download/install.
- Gate the ROCm index on a known arch, not only on probe-verified ROCm, so a
mapped arch installs ROCm torch directly. Unmapped arches and no-GPU hosts
still get CPU (unchanged).
- Fall back to a CPU base if the ROCm-index install fails, so a transient
repo.amd.com outage does not abort the install (setup.ps1 retries ROCm).
- Correct the stale comment that claimed ROCm wheels need a confirmed HIP SDK.
- Add a regression test for the arch-based gate.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Windows installer: correct the unsloth.exe rename-removal comment
The comment claimed the base upgrade 'routes through pip on Windows' and that
pip 'moves the old unsloth.exe aside, then writes the new one'. That is not what
the code does. install_python_stack tries uv first; on a locked launcher uv
aborts and falls back to pip, but the pip fallback strips --upgrade-package and
base.txt lists only bare unsloth/unsloth-zoo, so pip finds them already
satisfied and no-ops. The running unsloth.exe is left intact at its current
version either way. Reword the comment to describe the real uv-first /
pip-fallback-no-op behavior. No functional change.
* Windows installer: close two gaps in the venv-internal hipinfo exclusion
Review follow-up. The amd-smi/DiskPart gate could still reopen in two cases:
- setup.ps1 ran the HIP probe long before $VenvDir is assigned, so without
VIRTUAL_ENV (the `unsloth studio update` path) $venvRoots was empty and the
venv-internal hipInfo.exe was not recognized. Seed the venv root from
UNSLOTH_SETUP_PYTHON and the default Studio home too (both installers).
- The HIP_PATH/ROCM_PATH candidate was accepted without the venv filter, so an
env var pointing into the venv (AMD wheel) still set $HipSdkInstalled. Run
Test-HipinfoIsVenvInternal on the candidate as well (both installers).
Extend the PS gate test to assert both. Both .ps1 parse clean; install tests
pass (the venv-internal / HIP probe coverage at 359 passed).
* Windows installer: correct the CPU-base message for arches with no ROCm wheels
After gating the ROCm index on a known arch, a mapped arch sets $ROCmIndexUrl
and installs ROCm directly, so it no longer reaches the "temporary CPU base"
branch. That branch is now reached only by a name-inferred arch with no ROCm
wheels (e.g. RDNA2 gfx103X), where setup.ps1 does NOT install ROCm. The old
text ("setup replaces it with GPU ROCm wheels ... the final install IS
GPU-accelerated") was therefore always wrong there. Say plainly that PyTorch
stays on CPU for this GPU.
* Windows installer: seed the venv-internal hipInfo check from a custom Studio home
Test-HipinfoIsVenvInternal seeded the venv root from VIRTUAL_ENV, VenvDir, the
setup python, and the default %USERPROFILE% path only. A standalone
`unsloth studio update` with a custom UNSLOTH_STUDIO_HOME (or STUDIO_HOME alias)
and none of those set would not recognize the venv hipInfo on PATH, reopening the
amd-smi/DiskPart gate. Seed the custom home too, in both installers, and assert
it in the gate test.
* Studio installer: resolve venv aliases and expand ~ in the hipInfo venv filter
Two review points on the amd-smi/DiskPart UAC gate:
1. _path_inside_venv compared os.path.abspath of sys.prefix and the hipInfo
path, which does not resolve symlinks, junctions, or 8.3 short names. A venv
reached through an aliased path then fails the check, so its bundled
hipInfo.exe is mistaken for an external HIP SDK and amd-smi runs (the
DiskPart prompt this fix exists to suppress). Switch to os.path.realpath in
all three copies (amd.py, install_llama_prebuilt.py, install_python_stack.py).
2. setup.ps1's early venv-internal hipInfo probe seeded the venv root from a
custom Studio home (UNSLOTH_STUDIO_HOME / STUDIO_HOME) without expanding a
leading ~, while the canonical resolver does. With a tilde form,
[IO.Path]::GetFullPath kept the literal ~ relative to cwd, so the custom-home
hipInfo escaped the filter and reopened the gate. Expand ~ in the probe the
same way as the resolver.
tests/studio/install/test_pr5940_followups.py: 30 passed (adds a symlink
realpath case and a setup.ps1 tilde-expansion guard).
* Studio installer: mirror the hipInfo venv filter and ROCm wheel pins into install.ps1
Follow-up review on the same install.ps1 paths:
1. install.ps1's venv-internal hipInfo probe (Test-HipinfoIsVenvInternal)
seeded the venv root from a custom Studio home without expanding a leading
~, unlike the canonical resolver and setup.ps1. A tilde form left
[IO.Path]::GetFullPath with the literal ~ (relative to cwd), so the
custom-home hipInfo escaped the filter and reopened the amd-smi/DiskPart
gate. Expand ~ in the probe, matching the setup.ps1 fix.
2. The AMD ROCm path installed torchvision/torchaudio bare while pinning torch
to below 2.12. AMD's per-arch index publishes the companions independently
and may ship torchvision 0.27 (for torch 2.12) before removing 0.26, so a
bare resolve can pick an ABI-incompatible set and fall back to CPU. Add
torchvision/torchaudio floor maps and pass the pinned specs, mirroring
setup.ps1 and install_python_stack.py.
3. The ROCm-to-CPU fallback torch install used Invoke-InstallCommand (no
retry), the only torch step in the file without it. Switch to
Invoke-InstallCommandRetry so the recovery path survives a transient index
failure.
tests/studio/install/test_pr5940_followups.py: 33 passed (parametrized tilde
check over both installers, a torch/companion floor-map parity test, and a
CPU-fallback retry guard).
* Studio installer: scan all PATH hipinfo so the venv copy can't shadow a real HIP SDK
The amd-smi HIP-SDK probe used shutil.which("hipinfo") / Get-Command hipinfo,
which return only the first hit on PATH. The AMD torch wheel ships hipInfo.exe
inside the venv and the bnb fix (plus the Studio backend) prepend the venv
Scripts dir to PATH, so that venv-internal copy lands first. When a real HIP SDK
hipinfo sits later on PATH with HIP_PATH/ROCM_PATH unset, the first-hit probe
stopped at the venv copy, treated it as "not a HIP SDK", and closed the amd-smi
gate -- AMD users in that PATH-only SDK setup lost amd-smi telemetry and could
fall back to CPU. Scan every PATH entry and keep the first hipinfo that is not
venv-internal; only the venv copy is ignored, so the UAC/DiskPart suppression is
unchanged.
Applied to all three Python copies (install_llama_prebuilt.py,
install_python_stack.py, backend/utils/hardware/amd.py) via a new
_external_hipinfo_on_path helper, and both PowerShell callers (install.ps1,
setup.ps1) now use Get-Command hipinfo -All filtered by Test-HipinfoIsVenvInternal.
tests/studio/install/test_pr5940_followups.py: 36 passed (real-PATH scan tests, a
shadow-regression test for the exact venv-first ordering, and a parity check that
every Python copy uses the scanning helper).
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio uninstallers: fix leftovers (false "removed", shared icon, llama lock)
Auditing a dual native+WSL uninstall on a real device surfaced three leftovers:
1. uninstall.ps1 removed the data dir (which holds unsloth.ico) before the
shortcuts that reference that icon, so Explorer's icon cache briefly held it
open. Remove-Item -Recurse reported success yet left the locked file, and the
dir was never re-attempted, so it orphaned with a false "removed" log.
_RemovePath now verifies the path is actually gone (retrying transient locks)
and reports honestly, and the data dir is re-swept after the shortcuts go.
2. install.sh writes a shared unsloth.ico to %LOCALAPPDATA%\Unsloth Studio for
the WSL shortcut, but uninstall.sh never removed it, orphaning the icon (and
dir) after a WSL uninstall. uninstall.sh now drops that icon and the dir when
empty, in both the powershell.exe and drvfs-fallback paths.
3. ~/.unsloth/.llama.cpp.install.lock was never removed, so the rmdir of
~/.unsloth failed and the dir lingered. Both uninstallers now remove the lock.
Verified by running both uninstallers on a real dual install: device fully clean
(no install dirs, shortcuts, PATH/registry entries, shared icon, or lock left).
* install.sh: auto-route Strix Halo WSL to an existing Ubuntu 24.04
ROCm-on-WSL is the GPU runtime for Strix Halo and only targets Ubuntu
24.04. When the installer runs in a newer default distro (e.g. 26.04) it
cannot enable the GPU and silently falls back to CPU. If a 24.04 distro
already exists, re-run the install there and stop in the current one so the
GPU path is taken without the user having to know about the distro
requirement.
Runs before venv creation so the wrong distro is left untouched, guards
against re-route loops via UNSLOTH_WSL_REROUTED, leaves a working ROCm
distro alone (librocdxg present), and skips the GGUF-only / opt-out /
non-Strix cases. When no 24.04 distro exists we keep today's behaviour:
continue to CPU and print the `wsl --install Ubuntu-24.04` guidance, never
auto-downloading a distro.
Adds tests/sh/test_strixhalo_wsl_reroute.sh (hermetic: extracts the
function, rewrites its paths to fixtures, mocks wsl.exe) covering the full
decision matrix, wired into tests/run_all.sh.
* uninstall.ps1: keep shared unsloth.ico for a surviving WSL shortcut
A dual native+WSL install shares %LOCALAPPDATA%\Unsloth Studio\unsloth.ico:
install.sh points the WSL shortcut's icon there while the native install owns the
dir. The native uninstaller removed the whole dir unconditionally, so uninstalling
native while keeping WSL left the WSL shortcut with a blank icon. The old code only
avoided this when Explorer happened to hold the icon open, which is unreliable; on a
real dual install the dir was deleted and the WSL shortcut went blank.
_RemoveDataDirKeepingWslIcon now scans the Start Menu + Desktop for a surviving
"Unsloth Studio (WSL ...).lnk" and, if found, removes everything in the data dir
except unsloth.ico (keeping the dir) instead of deleting it; with no WSL shortcut it
removes the dir as before. uninstall.sh still drops the icon and the empty dir when
WSL itself is uninstalled, so every uninstall order ends clean.
Adds tests/studio/test_uninstall_dual_install_icon.ps1 (AST-extracts the helper and
runs it against a temp dir with controlled shortcut dirs) covering the dual,
native-only, empty, and missing-dir cases, wired into the windows-inference smoke
workflow. Verified on a real dual install: native uninstall now keeps unsloth.ico
and the WSL shortcut's icon stays intact.
* installer: condense AMD/ROCm code comments (no behavior change)
Tighten the comments added for the Strix Halo native+WSL installer work so
they are shorter and clearer without losing intent: the venv-internal hipInfo
amd-smi gate, the ROCm torch/companion floor maps, the WSL 24.04 reroute, and
the dual-install uninstall icon handling. Comment-only; code paths unchanged.
107 insertions, 166 deletions across 11 files.
* install.sh: run the Strix Halo WSL reroute before any STUDIO_HOME write
The reroute fired after mkdir -p "$STUDIO_HOME" and the legacy-venv migration,
so rerouting 26.04 -> 24.04 left an empty ~/.unsloth/studio stub in the origin
distro (and ran venv migration in the distro about to be abandoned). Move the
reroute ahead of the venv section so the origin distro is left untouched, matching
the function's own comment. Behavior is identical on every non-reroute path.
* installer: fix ROCm CPU-fallback, hipinfo gate edge cases, uninstall icon, WSL 22.04
- install.ps1: clear $ROCmIndexUrl/$ROCmTorchFloor after the CPU fallback so the
flavor-repair block does not retry the failed ROCm index and abort the install;
pin the ROCm companion specs ($visionSpec/$audioSpec) in the repair path too.
- install.ps1 + setup.ps1: skip a bare drive root in Test-HipinfoIsVenvInternal so a
non-venv UNSLOTH_SETUP_PYTHON does not match the whole drive; iterate
HIP_PATH/HIP_PATH_57/ROCM_PATH and take the first non-venv hipinfo.
- amd.py, install_llama_prebuilt.py, install_python_stack.py: strip surrounding
quotes from PATH entries before probing for hipinfo.
- install.sh: pipefail the WSL reroute curl|sh; do not reroute supported Ubuntu 22.04.
- uninstall.sh: keep the shared unsloth.ico while any Unsloth shortcut (native or
another WSL distro) still references it, in both the powershell and drvfs paths.
- tests: regression coverage for all of the above.
* installer: forward reroute options, guard ROCm bootstrap, harden hipinfo gate
- install.sh: forward the caller's --package/--python/--verbose/--tauri and a custom
UNSLOTH_STUDIO_HOME into the WSL reroute (was a bare default install); bail on
--local; run the reroute BEFORE dependency/uv install so the origin distro is left
untouched; set UNSLOTH_SKIP_ROCM_WSL_SETUP after a failed reroute so the later
ROCm-on-WSL bootstrap does not install into the unsupported origin distro.
- install.ps1 + setup.ps1: Get-Command hipinfo -CommandType Application so only real
executables match (not an alias/function named hipinfo).
- uninstall.ps1: guard $env:APPDATA when building the default shortcut search dirs.
- tests: cover option forwarding, --local bail, the bootstrap guard, and the gate change.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* installer: guard origin ROCm bootstrap on every CPU-only fallback; harden ~ expansion
WSL reroute: the no-wsl.exe, no-24.04-target and --local fallbacks all tell the
user the install continues CPU-only, but only the failed-reroute branch set
UNSLOTH_SKIP_ROCM_WSL_SETUP=1. The later _maybe_bootstrap_rocm_wsl gate keys off
that flag, so the other three branches could still install ROCm into the
unsupported origin distro (e.g. 26.04). Set the skip guard on all of them.
Forward UNSLOTH_ROCM_WSL_AUTO into the reroute so a Tauri/consented GPU bootstrap
carries through to the rerouted 24.04 child instead of dropping to the prompt path.
install.ps1/setup.ps1: guard the venv-probe ~ expansion on a non-empty
$env:USERPROFILE so Join-Path does not throw on a profile-less service account.
Tests: add no-wsl.exe and UNSLOTH_ROCM_WSL_AUTO reroute cases, the USERPROFILE
guard assertion, and route shell-test fixtures through a single trap-cleaned root.
* installer: pin + soften Windows ROCm Python repair, reroute to 22.04, harden gates
install_python_stack.py: the Windows AMD ROCm repair in _ensure_rocm_torch()
installed bare torch/torchvision/torchaudio via the fatal pip_install -- the same
asymmetry already fixed on the PowerShell side. A transient repo.amd.com failure
could abort the whole install even after install.ps1/setup.ps1 fell back to CPU.
Pin companions per-arch (gfx120X/Strix -> the rocm7.2 trio, mirroring the PS floor
maps) and make the retry nonfatal: keep the existing build and let the user re-run
update to retry ROCm, so the chain install.ps1 -> setup.ps1 -> stack stays CPU-safe.
install.sh: reroute now targets an installed Ubuntu 24.04 OR 22.04 (24.04 preferred);
both are AMD-supported for ROCm-on-WSL, matching the leave-alone set, so a box with
only 22.04 reaches the GPU instead of staying CPU-only.
install.ps1/setup.ps1: a bare ~ for UNSLOTH_STUDIO_HOME left an empty Join-Path child
(PS 5.1 throws); fall back to USERPROFILE directly and only join a real remainder.
_path_inside_venv (amd.py + both installers): guard a root-dir sys.prefix so commonpath
can't classify every path on the drive as venv-internal (defensive; venv never at root).
uninstall.sh: guard an empty LOCALAPPDATA in the PS-interop icon cleanup (mirror APPDATA).
Tests: add 22.04-target reroute cases, Windows ROCm pin+nonfatal coverage (text +
behavioral), root-dir guard coverage, and bare-~/LOCALAPPDATA guard assertions.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* install.sh: match WSL reroute target by exact distro name, not substring
The 24.04/22.04 reroute target was chosen with grep -F (substring), so a custom
distro such as 'Ubuntu-24.04-test' (with no exact Ubuntu-24.04) was picked as the
target; the later 'wsl -d Ubuntu-24.04' then fails and the Strix Halo install stays
CPU-only. Match whole lines (grep -ixF) and reuse the matched name so only a real
Ubuntu-24.04/22.04 is targeted. Adds substring-rejection + exact-vs-custom tests.
* install.sh: keep the WSL reroute target to Ubuntu 24.04 (helper-supported only)
The ROCm-on-WSL bootstrap (scripts/install_rocm_wsl_strixhalo.sh) dies on any
VERSION_ID other than 24.04 and pins the noble repo, so treating 22.04 as
GPU-supported let the parent report a successful reroute while the child fell
back to CPU. Drop 22.04 from the supported set and the reroute target list;
24.04 stays the sole target (keeping the exact whole-line distro match). An
already-working ROCm on any other version is still left alone by the librocdxg
check above.
tests: reroute 22.04 cases updated to the 24.04-only behavior; make the
"no wsl.exe" case hermetic so a real host wsl.exe can't leak in on dev boxes;
stop the tauri exit-order check from mis-flagging the reroute helper's
[ "$TAURI_MODE" = true ] && ... --tauri one-liner.
* installer: tighten comment wording across the Strix Halo install/uninstall paths
Condense the verbose multi-line comment blocks (amd-smi hipinfo gate, ROCm
torch install + CPU fallback, WSL reroute, uninstall icon-keep) into fewer,
clearer lines. Comments and a few docstrings only; no code, logic, or
behavior change. Verified with bash -n, the PowerShell parser, and ast.parse,
and the installer test suite still passes.
* add AGPL-3.0 SPDX headers to the .sh/.ps1 scripts missing them
Every shell and PowerShell script under the Studio/installer surface now
carries the standard SPDX-License-Identifier: AGPL-3.0-only + copyright
header (after the shebang where present): the installer (install.sh,
install.ps1), build.sh, the .github and src-tauri scripts, the installer
test suite, and the moe kernel test. Header-only, line endings preserved;
bash -n, the PowerShell parser, and the installer tests all pass.
* installer: drop the duplicate AGPL header from install.sh and install.ps1
Both already carry an SPDX-License-Identifier: AGPL-3.0-only header below
their usage comment block; the prior header pass added a second one at the
top because it only scanned the first few lines. Remove the duplicate so each
file keeps a single original header.
* installer: force-reinstall CPU fallback torch; propagate Tauri NEED_SUDO from reroute
install.ps1/setup.ps1: when the AMD ROCm wheel install fails and we fall back to a
CPU base, force-reinstall the torch/vision/audio triplet. A failed ROCm install can
leave an unpinned ROCm torch (e.g. 2.10.0+rocm on gfx110X/gfx90a) that still
satisfies the CPU torch>=2.4,<2.11.0 range, so without --force-reinstall uv keeps the
ROCm build and only swaps the companions -- a mismatched venv the flavor-repair block
won't fix. setup.ps1 scopes the forced reinstall to the ROCm-fallback path
() so the genuine CPU-only install stays fast.
install.sh: the Strix Halo WSL reroute treated every nonzero child exit as a reroute
failure and fell back to CPU. In --tauri mode the child uses exit 2 ([TAURI:NEED_SUDO])
to ask the desktop app to elevate for the target distro; capture the child's exit code
and propagate exit 2 in Tauri mode (the child already printed the NEED_SUDO line)
instead of masking it. CLI mode still falls back to CPU on a generic failure.
Tests: reroute Tauri exit-2 propagation (and non-Tauri CPU-fallback) cases;
run_func now preserves the child exit code; force-reinstall assertions for both
PowerShell installers.
Note: codex's _rr_q apostrophe finding is a false positive -- the helper already
emits POSIX-correct 'O'\''Brien' and round-trips under both sh and bash.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* setup.ps1: fix $cpuForce array collapse in the ROCm->CPU torch fallback
An if-expression assignment ($cpuForce = if ($ROCmCpuFallback) { @("--force-reinstall") })
collapses the single-element array to a scalar string, so @cpuForce splatting enumerated
it character-by-character into broken single-letter args (- - f o r c e ...), which made
uv/pip reject the install and aborted the whole Studio setup on the AMD ROCm->CPU fallback
path. Build $cpuForce as a real array assigned outside the if-expression so the splat passes
a single --force-reinstall arg. Genuine CPU-only installs stay fast (empty array, no flag).
Test now asserts the array-build form and rejects the if-expression form.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* uninstall: remove the isolated Node.js runtime (~/.unsloth/node)
The isolated Node.js runtime (install_node_prebuilt.py, added with the managed-Node
change) installs to ~/.unsloth/node in default mode -- a sibling of studio, so deleting
<studio> leaves it behind (~200MB orphaned after uninstall). Both uninstallers already
remove the other default-mode siblings (llama.cpp/.cache/.staging); add node alongside
them. uninstall.ps1 also adds it to the handle-lock sweep so a held node.exe can't block
the delete. Env/custom mode nests node under the custom root, removed with that root.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Studio: defer llama.cpp update probes and self-heal MLX on macOS
Two macOS startup problems shared one root area in the FastAPI lifespan:
- The llama.cpp capability + freshness probes ran inline before the server
yielded, so a cold/slow/flaky network on the GitHub freshness check blocked
'Application startup complete' (~34s on CI, longer in the field). Move both
probes to a daemon thread; app.state stays None until ready (status routes
already re-probe at request time). Opt out with UNSLOTH_DISABLE_UPDATE_CHECK=1.
- Train and Export were greyed out because mlx/mlx-lm/mlx-vlm arrive only
transitively and a resolver backtrack silently drops them, so CHAT_ONLY stayed
true. Add utils/mlx_repair.py: when Apple Silicon is detected without MLX,
reinstall mlx/mlx-lm/mlx-vlm by name on a daemon thread and re-run hardware
detection (opt out UNSLOTH_DISABLE_MLX_AUTOREPAIR=1). Surface a chat_only_reason
in /api/health plus a sidebar tooltip so a greyed Train/Export explains itself
instead of failing silently.
* Studio: guard model defaults against a None model name
load_model_defaults(None) called model_name.lower() with no guard, raising
'Error loading model defaults for None' before any model is selected. Return
an empty dict for a falsy/non-str name.
* Studio: drop obsolete upstream macOS + Windows Blackwell prebuilt pins
Both pins worked around gaps in ggml-org upstream prebuilts, but Studio now
routes every GPU host and all of macOS to the unslothai/llama.cpp fork
(published_repo_for_host), which ships the needed bundles, so both pins are
dead code on the default install path:
- macOS b9415: macOS always routes to the fork (its own macOS bundles), and
host_supports_macos_minos() is the backstop. The pin only fired under an
explicit --published-repo ggml-org override.
- Windows Blackwell b9360: Windows-NVIDIA routes to the fork, whose
windows-x64-cuda13 bundle covers Blackwell (manifest max_sm 120, toolkit
13.3), so the pin's self-disable check makes it dormant on every default
install; it could only activate under the same upstream override on a
13.0-13.2 driver.
Remove the pin constants, functions, and call sites. Keep the Blackwell
capability detection (_drop_blackwell_incapable_windows_cuda, _host_is_blackwell,
_windows_cuda_attempt_covers_blackwell) that still drops a non-sm_120 cuda-12.4
build on a Blackwell host. After this, an explicit --published-repo ggml-org
override on a Blackwell 13.0-13.2 host loses its GPU fallback and lands on CPU;
the default fork path is unaffected. Update the install selection-logic and
macOS-compat unit tests for the new no-pin behavior.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: walk back deeper on the macOS upstream prebuilt path
After removing the b9415 macOS pin, the explicit --published-repo ggml-org
upstream path still used the default 2-release fallback, so a pre-macOS-26 host
behind a run of macOS-26-only builds would exhaust two too-new plans (minos is
only checked post-download) and drop to a source build before reaching a
loadable older release. Walk back as deep as the fork macOS path
(DEFAULT_MAX_MACOS_RELEASE_FALLBACKS), turning the removed static pin into
dynamic discovery. Addresses review feedback on the macOS upstream fallback.
* Studio: pin transformers during MLX self-heal so it cannot break Studio
mlx-lm/mlx-vlm declare transformers>=5, but the single-env install pins
transformers==4.57.6. The self-heal used --upgrade with no constraint, so it
could upgrade transformers in the live venv and break the rest of Studio just to
make import mlx.core pass. Pin transformers to the installed version via a
constraint file: the resolver either finds an mlx build compatible with it or
fails (we stay chat-only), never upgrading transformers underneath Studio.
Addresses review feedback on the MLX repair install.
* Studio: harden MLX self-heal against an unsupported mlx-vlm
Pinning transformers alone made uv backtrack mlx-vlm to 0.3.9 (below unsloth-zoo's
mlx-vlm>=0.4.4), which imports but breaks VLM Train/Export -- so the self-heal
could clear chat-only onto a broken stack. Mirror the main installer: set
UV_OVERRIDE=overrides-darwin-arm64.txt so a current mlx-vlm coexists with the
transformers pin, require the same minimum versions unsloth-zoo declares, and
gate/validate on a full mlx_stack_available() check (not a bare import) so an
old or partial stack stays chat-only. Addresses PR review.
* Studio: filter Blackwell-incapable CUDA in resolve_upstream_asset_choice
resolve_upstream_asset_choice returned the first windows-cuda choice unfiltered,
so a Blackwell host could be handed an sm_120-incapable cuda-12.4 build while the
sibling planners drop it. Apply _drop_blackwell_incapable_windows_cuda here too
and fall through to the CPU bundle on a Blackwell host with no capable GPU asset.
Addresses PR review.
* Studio: re-poll health so MLX self-heal reaches an open UI
The sidebar cached the initial /api/health, so a successful background MLX
self-heal (chat_only flips false) did not re-enable Train/Export until a manual
reload. While chat-only for the recoverable mlx_unavailable reason, re-poll
/api/health and stop once Train/Export become available. Addresses PR review.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: make the disabled Train/Export tooltip reachable
The greyed Train/Export items pass a tooltip explaining why (e.g. MLX missing),
but a disabled <button> fires no pointer events and SidebarMenuButton only showed
tooltips while collapsed, so the explanation never appeared. Wrap a disabled
button in a focusable span and show its tooltip while expanded too; enabled items
keep the collapsed-only behavior. Addresses PR review.
* Studio: gate Train/Export on the full MLX stack, not bare mlx.core
detect_hardware enabled MLX training whenever `import mlx.core` worked, but the
MLX self-heal (utils/mlx_repair) treats a stack without mlx-lm/mlx-vlm at the
versions unsloth-zoo requires as inadequate. That asymmetry let the UI enable
Train/Export on exactly the partial/backtracked stack the self-heal is trying to
repair (greyed-in-but-broken VLM export). Gate on the same mlx_stack_available()
criterion so a partial stack stays chat-only (reason mlx_unavailable) and the
background repair restores it. Addresses PR review.
* Fix MLX repair and health auth for PR #6494
* Fix macOS upstream prebuilt fallback for PR #6494
* Fix MLX stack validation for PR #6494
* Fix MLX self-heal validation for PR #6494
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Review fixes: isolate hardware-state test, robust transformers pin
- test_chat_only_reason.py: detect_hardware() assigns module globals directly,
which monkeypatch does not revert; the autouse fixture now saves and restores
DEVICE/CHAT_ONLY/CHAT_ONLY_REASON/IS_ROCM so a chat-only verdict here cannot
leak into other backend tests (e.g. test_utils.py) on a GPU host.
- mlx_repair.py: read the transformers version from importlib.metadata instead of
importing transformers, so the install pin is not silently dropped when
transformers has valid metadata but fails to import.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix CI: model full MLX stack in dispatch tests, keep selection test offline
dispatch (macOS) job:
- detect_hardware now gates MLX on the full stack (mlx_stack_available imports
mlx_lm/mlx_vlm and checks dist versions), so faking only mlx.core makes the
apple_silicon_mlx profile resolve to CPU. The dispatch tests assert the routing
decision when the stack IS usable, so model a complete stack:
test_hardware_dispatch_matrix patches utils.mlx_repair.mlx_stack_available and
test_is_mlx_dispatch_gate patches hardware._has_usable_mlx_stack. The stack
predicate's own internals stay covered by test_mlx_repair.py.
Repo tests (CPU) job:
- test_no_cuda_attempt_on_published_path_for_13_1 fell through to a live
github_release_assets() upstream fetch after the Blackwell filter dropped every
published attempt, which the offline security scanner blocks. Stub that fetch so
the walk-back deterministically finds no usable CUDA build and raises
PrebuiltFallback without network.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Harden MLX self-heal: prepare transformers constraint inside the try
attempt_mlx_repair runs on a daemon thread, but _transformers_constraint_args was
called before the try. A failure there (e.g. tempfile.mkstemp on a full disk or a
bad TMPDIR) would propagate unhandled and silently kill the self-heal thread.
Move the call inside the try and initialize constraint_path so any such failure
is caught and leaves Studio chat-only instead of crashing the thread.
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* Fix save crash for legacy list-form _tied_weights_keys (NemotronH)
transformers >= 5 save_pretrained reads module._tied_weights_keys.keys(),
which raises 'list' object has no attribute 'keys' for modules that still
declare the attribute as a list (e.g. NemotronH backbone.layers.N.mixer.*_proj),
crashing GGUF export and merged saves part-way through.
Coerce any legacy list/tuple _tied_weights_keys into the dict form transformers
5.x expects, mapping each key to itself. Only the keys are read (as dedup
patterns) so behaviour is preserved, and older transformers that iterate the
attribute directly see the same keys. The helper is idempotent and best-effort
so a save never fails over it. Called from unsloth_save_model,
unsloth_save_pretrained_gguf and unsloth_generic_save after tokenizer patching.
Adds version-independent unit tests covering list/tuple coercion, dict and
None/empty pass-through, idempotency and odd-object tolerance.
* Coerce empty/set _tied_weights_keys too
transformers only skips _tied_weights_keys when it is None, so an empty list,
tuple or set still reaches .keys() and raises the same AttributeError. Coerce
every non-dict container (including the empty case and sets) to a dict, and add
tests for empty/set inputs.
* Tighten comments in tied-weights save fix
* Scope tied-weights-keys coercion to the save call
Coercing legacy list-form _tied_weights_keys to {k: k} fixed the transformers
5 save crash, but persisted a self-mapping on the live model. transformers 5
re-ties from the dict's values, so a later resize/re-tie would no-op the tie
instead of pointing the output weights back at the input embeddings.
Replace the in-place mutation with a decorator that coerces before the save and
restores the originals afterwards (including on exception), so the save sees the
dict form transformers needs while the model keeps its original tie metadata.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim comments to be more succinct
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* studio/setup.ps1: complete Visual Studio 2026 support for the CUDA llama.cpp build
Builds on #6038 (VS 2026 / v18 detection). Once the generator is detected as
Visual Studio 18 2026, two things still broke the CUDA llama.cpp build:
- the CUDA to VS MSBuild integration copied the CUDA .targets into a hardcoded
VC\v170 (VS 2022) BuildCustomizations folder, so a VS 2026 (v180) toolchain
saw no CUDA toolset and cmake failed with "No CUDA toolset found".
- cmake was installed with no version check, but the "Visual Studio 18 2026"
generator requires CMake 4.2+.
This adds Get-VcBuildCustomizationsDir (derives v160/v170/v180 from the detected
generator, falls back to v170), a CMake 4.2 guard for the VS 2026 generator
(upgrades via winget once, else fails with a clear message), and routes both the
copy target and the failure hint through the derived path.
No behavior change for VS 2022/2019/2017: the folder resolves to v170 and the
guard is skipped. Adds windows-latest Pester unit tests (tests/studio_setup_ps1)
plus a workflow that runs them.
* Address review: make VS 2026 self-contained + gate CMake guard to source build
- Find-VsBuildTools now detects VS 2026: vswhere catalog_productLineVersion 2026
-> "Visual Studio 18 2026", and the filesystem scan covers the "18"/"2026" dirs
(incl. non-standard editions like Preview). Adapted from #6038 by
@LeoBorcherding, so the v180 BuildCustomizations path and the CMake guard are
actually reachable on a VS 2026-only host.
- Move the CMake 4.2 guard out of Phase 1 into the committed-source-build branch.
The preferred prebuilt llama.cpp path never reaches it, so a VS 2026 host on
CMake < 4.2 is no longer blocked from using the prebuilt.
- winget upgrade -> install fallback when the on-PATH cmake is not the Kitware
winget package, and log winget failures instead of swallowing them.
- Add a windows-latest Find-VsBuildTools VS 2026 discovery regression test.
* tests(vs2026): define New-FakeVsTree in BeforeAll so It blocks can see it
The Find-VsBuildTools discovery tests are Windows-only (-Skip on non-Windows),
so they first ran on the windows-latest Pester job, where New-FakeVsTree raised
CommandNotFoundException: it was defined in the Describe body, which Pester 5
executes only during discovery, so the function did not persist into the
run-phase It scope. Move it into a BeforeAll block (which runs in the run phase
and is visible to the It blocks). No production code change.
* Address review: probe cmake generator support, fall back to older VS, fix cmake PATH after winget
The VS 2026 CMake guard previously gated only on the cmake version (>= 4.2)
and hard-failed otherwise. Review on #6473 raised three real gaps:
- A VS-bundled cmake below 4.2 can still drive the VS 2026 generator. Probe
cmake --help (Test-CmakeListsGenerator / Test-CmakeCanDriveGenerator) and
accept it when the generator is advertised, not just on the version floor.
- After winget upgrade/install, an older cmake earlier on PATH kept being
resolved. Add-DefaultCmakeToPath prepends the default install dir so the new
cmake wins before re-probing.
- When cmake cannot drive VS 2026 but an older Visual Studio (2022/2019/2017)
is installed and usable, fall back to it (Get-FallbackVsGenerator) instead of
hard-failing, preserving the pre-VS-2026 build path.
Tests mock the cmake command rather than dropping a shim on PATH: PowerShell
caches its application-path table, so a real cmake on the runner (present on
windows-latest) wins over a PATH shim. A function mock is resolved first and is
cache-proof cross-platform.
* Detect VS installed under the Preview edition dir for older versions
Find-VsBuildTools already scans every subdir for VS 2026, but the older-version
(2017/2019/2022) filesystem fallback and Get-FallbackVsGenerator only checked
BuildTools/Community/Professional/Enterprise. A Preview-channel install lives
under a 'Preview' edition folder, so it was missed when vswhere was also
unavailable. Add 'Preview' to both edition lists and guard each with a Windows
Pester test.
* Add real-VS integration matrix: detect actual VS 2022 and VS 2026 in parallel
The unit tests validate VS detection logic with mocked vswhere and fake install
trees (all five versions). This adds a parallel integration job that runs the
real Find-VsBuildTools / Get-VcBuildCustomizationsDir against the Visual Studio
actually preinstalled on GitHub-hosted runners:
- windows-2022 -> real Visual Studio 2022, expect generator v170
- windows-2025-vs2026 -> real Visual Studio 2026, expect generator v180
It asserts our detection matches the real install, the install path exists, the
derived toolset matches, and that the derived v-number is a real folder on the VS
install. VS 2017/2019/2015 are retired from hosted images, so only 2022 and 2026
can be exercised against a genuine install; the rest stay covered by the mocks.
* Detect VS 2026 via vswhere: it reports productLineVersion '18', not '2026'
Real-VS CI on the windows-2025-vs2026 runner showed vswhere reports
catalog_productLineVersion='18' (the internal major) for Visual Studio 2026, not
the marketing year '2026' that VS <= 2022 report. The vswhere map only had
'2026', so on a real VS 2026 host the vswhere branch returned null and detection
survived only via the filesystem scan (Source='filesystem'); a VS 2026 installed
outside the default Program Files location would not be found at all.
Extract a pure Resolve-VsGeneratorFromLabel that accepts both the year and the
internal-major form ('18'/'17'/'16'/'15' as well as '2026'/'2022'/'2019'/'2017')
and use it for both the vswhere and filesystem branches. Add pure unit tests
(cross-platform) for the mapping, including the '18' -> VS 2026 case.
* ci: dot-source Resolve-VsGeneratorFromLabel in the real-VS integration job
Find-VsBuildTools now calls Resolve-VsGeneratorFromLabel, so the integration
step must extract it too; without it the job failed with the helper not
recognized.
* Defer Visual Studio + CMake to the llama.cpp source build (prebuilt path needs no build tools)
The Windows installer required Visual Studio Build Tools and CMake eagerly in
Phase 1 (winget install + exit 1 if absent), before the llama.cpp prebuilt-vs-
source decision. But the preferred path downloads a prebuilt llama.cpp (no
compiler), the backend only shells out to the prebuilt llama-server.exe, and
PyTorch is pip wheels -- so VS and CMake are only needed for the from-source
build last resort. The eager requirement forced every Windows user to install
multi-GB Visual Studio + CMake they never use, or the installer failed.
Change (mirrors the already-lazy Resolve-CudaToolkit / OpenSSL):
- Phase 1c/1d now only DETECT cmake / VS and log; they never winget-install or
exit. The prebuilt install runs zero build-tool installs and is unblocked on
hosts without build tools.
- New Ensure-BuildToolsForLlamaSourceBuild installs CMake (best effort) + VS
(hard requirement, exit 1 with the existing guidance if it cannot be found),
called only when a source build is actually committed, before
Resolve-CudaToolkit. git stays eager (pip needs it for git+ deps).
Tests:
- Pester: the early probe (Find-VsBuildTools) returns null without exiting when
no VS is present; Ensure-BuildToolsForLlamaSourceBuild no-ops when VS is
already detected.
- New studio-windows-no-vs-smoke.yml: Job A renames Visual Studio + vswhere away
and hides cmake, runs the real install.ps1 --local --no-torch, and asserts the
prebuilt llama.cpp installed (no source-build fallback, no VS/CMake install),
PyTorch CPU imports, the backend is healthy, and a /v1/chat/completions
inference returns a reply -- all with no Visual Studio. Job B confirms the GPU
CUDA prebuilt is available and the resolver runs without VS.
* Fix VS 2026 CUDA source build ordering and fallback VS discovery
Same fix as on the stacked base branch (studio-vs2026-cuda-msbuild):
- Move Resolve-CudaToolkit below the CMake gate/fallback in the source build path. It copies the CUDA MSBuild .targets into the current VS generator's BuildCustomizations folder, so running it before a VS 2026 to older-VS fallback left the .targets under v180 while cmake configured v170 ("No CUDA toolset found"). It now runs after the final generator is selected.
- Get-FallbackVsGenerator now queries vswhere first, matching Find-VsBuildTools, so a VS installed outside the default Program Files roots is found instead of failing with a hard exit.
- Add Pester regression tests: the source build resolves CUDA after the fallback, and the fallback queries vswhere.
* Ensure the Visual C++ Redistributable is present for the prebuilt llama.cpp and PyTorch
The prebuilt llama-server.exe and the PyTorch wheels dynamically link the MSVC runtime (VCRUNTIME140.dll, MSVCP140.dll, VCRUNTIME140_1.dll). The Universal CRT ships with Windows 10+, but the VC++ 2015-2022 redistributable does not, so a clean box can fail to launch llama-server or import torch with a missing VCRUNTIME140.dll.
- Add Test-VCRedistInstalled (System32 vcruntime140_1.dll, with a registry fallback gated on version 14.20+) and Ensure-VCRedist (winget Microsoft.VCRedist.2015+.x64, non-fatal), called as Phase 1b.5 so it runs even on the no-build-tools prebuilt path. It is a no-op when the runtime is already present, which is the common case.
- Add Pester tests for the detection: present via the DLL, present via the registry, absent, and an old 2015-only redist that is too low.
* Add a CI job that validates the VC++ runtime detection on a real Windows runner
Runs on windows-latest and windows-2025-vs2026: asserts Test-VCRedistInstalled reports present on the stock image, removes both detection signals (the System32 DLL via a redirected SystemRoot and the HKLM runtime keys, restorably) to confirm detection fires on a genuinely clean box, then does a literal uninstall/reinstall round trip with the official installer and the Ensure-VCRedist winget path. The runtime is restored before the job ends.
* Dot-source the full logging closure in the VC++ runtime CI job
Ensure-VCRedist calls step/substep, which reach Write-StudioStdoutMirror and Get-StudioAnsi; extract those too so the job does not fail with an unrecognized command. Also note that the runtime is ref-counted by Visual Studio on the hosted image, so the literal package uninstall is a no-op there (the clean-box section already proves detection fires when the runtime is genuinely absent).
* Tighten comments in setup.ps1, the VS2026 tests and workflow
Comment-only: condense the verbose helper/test/CI comments to one or two lines, drop the obvious ones, keep the non-obvious rationale. Verified comment-only by comparing the PowerShell code-token stream before and after (no code tokens changed); Pester suite still green.
* Fold the no-VS and setup.ps1 VS2026 Windows CI into studio-windows-inference-smoke.yml
Move the no-vs-cpu/no-vs-gpu-resolve and pester/vs-integration/vcredist-clean-box jobs into the existing Windows GGUF CI workflow and delete the two standalone files, so a studio change triggers one Windows workflow instead of three. Path filter gains tests/studio_setup_ps1/**; job keys and artifact names stay unique.
* CI: assert a Windows ROCm prebuilt exists in the no-VS resolve job
The no-vs-gpu-resolve job confirmed a Windows CUDA asset but never a ROCm one,
and the resolver step resolves to CPU on hosted runners (no AMD GPU), so the
AMD no-VS guarantee rode only on shared resolver code. Grep the per-gfx
windows-x64-rocm-gfx bundles in the same asset-availability step so a release
that drops the Windows ROCm prebuilts fails loudly.
---------
Co-authored-by: Daniel Han <michaelhan2050@gmail.com>
* Update studio root-resilience tests for the inference-backend refactor
#6490 moved the studio_root() probe and its (ImportError, OSError, ValueError)
handler out of _find_llama_server_binary / _kill_orphaned_servers into the shared
_resolved_studio_root_and_is_legacy() classifier, and switched the WSL ROCm lib-dir
ordering to lib_dirs.extend(_wsl_system_rocm_lib_dirs()). These source-introspection
tests still asserted the old inline structure, so they fail on main (surfaced by any
PR that trips the Repo tests path filter, e.g. the Windows installer PRs). Point them
at the new structure and assert the defense in its new home; no runtime change.
* Address review: qualify the classifier call and harden helper-body extraction
Assert the callers invoke LlamaCppBackend._resolved_studio_root_and_is_legacy()
through the class namespace (more precise than the bare name), and end the
helper-source slice at the next sibling def/decorator at the same indent instead
of the literal @staticmethod string, so a future docstring that mentions a
decorator can't truncate the helper mid-body and break exec().
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Harden evaluate_fetch against execution-context-destroyed during navigation
The Mac Studio chat-UI Playwright test intermittently failed with 'Page.evaluate: Execution context was destroyed, most likely because of a navigation' (e.g. run 27904470348). evaluate_fetch already retried transport failures (the JS result status==0), but the page.evaluate call itself can throw at the Python level when a navigation or auth refresh destroys the execution context mid-call, which was uncaught and crashed the script.
Wrap the evaluate in a try/except that retries this transient class of error (execution context destroyed, frame detached, target closed) within the existing attempt budget, letting the page settle via wait_for_load_state before retrying. Real or persistent errors still propagate (re-raised on the final attempt or for non-transient messages).
* Add reusable robust_evaluate and route auth-token reads through it
Promote the execution-context-destroyed retry from evaluate_fetch into a reusable robust_evaluate(page_or_locator, expression, arg) helper, and have evaluate_fetch use it (no behaviour change to the transport retry). Route the post-login localStorage auth-token reads in playwright_chat_ui.py and playwright_extra_ui.py through it too, since those direct evaluates run right after auth redirects and are the same navigation-race class. The stable composer/IME evaluates that never overlap a navigation are left as-is. Helper retry semantics covered by unit checks (transient retries then succeeds, non-transient re-raises, persistent re-raises after the budget, locator settles via .page).
* Apply repo ruff-format kwarg-spacing to the hardened Playwright evaluates
* Don't replay single-use POSTs (auth/refresh) when robust_evaluate retries a context loss
* Match context-loss markers case-insensitively and only replay idempotent fetches
Playwright varies the casing of the detached-frame/destroyed-context error
across versions, so the substring check now lowercases both sides. evaluate_fetch
no longer replays mutating methods on a mid-call context loss: the default now
retries only GET/HEAD/OPTIONS, so a duplicate POST /api/inference/load (rejected
while the first is still loading) or a spent POST /api/auth/refresh is never
re-sent. Callers can still override per call.
---------
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
* Studio: use an isolated Node.js for the frontend build instead of replacing the system Node/npm
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: address Node isolation review (no-Node probe crash, PATH refresh, OXC provisioning, venv python, runtime node resolver)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix/adjust Node isolation for PR #6533
* Studio Node: don't cache a negative node resolution; accept Node metadata in setup.sh ownership guard
- node_runtime: memoize only a version-adequate executable so a Node installed
by a separate-process 'studio update' is picked up without a backend restart.
- setup.sh: _studio_owned_adoptable also accepts UNSLOTH_NODE_PREBUILT_INFO.json,
matching the setup.ps1 Node ownership guard (custom-home parity).
* Studio setup.ps1: skip OXC npm install gracefully when npm is absent
Mirror setup.sh's `command -v npm` guard so a pip-installed Studio with no
system Node skips the OXC runtime install (validator degrades at runtime) instead
of exit 1 aborting the whole setup. Tighten test_node_probe_guard.ps1's probe
regex so it only matches the two system-version probes, not this new npm guard.
* Wire test_node_probe_guard.ps1 into Windows CI for PR #6533
* Harden isolated Node install and probes for PR #6533
- install_node_prebuilt.py: keep an existing, still-usable isolated Node
when nodejs.org's dist index is unreachable instead of aborting the
update on a transient outage (existing_install_usable + tolerant fetch).
- install_node_prebuilt.py: pin NPM_CONFIG_PREFIX/npm_config_prefix and
drop NODE_PATH in _run_node so any npm -g stays inside the isolated
prefix; Windows npm otherwise writes to %APPDATA%\npm.
- install_node_prebuilt.py: resolve tar hard-link targets against the
archive root (symlink targets stay link-parent relative).
- setup.ps1: wrap the system node/npm probes in try/catch so a present
but broken shim degrades to the bundled Node instead of aborting setup.
- setup.ps1: run the isolated Node install with the handed-off/venv Python
(ReusedSetupPython); the main resolver runs later and bare python may be
a Store stub this early.
- setup.sh: log when the OXC validator runtime is skipped for missing npm,
matching setup.ps1.
- node_runtime.py: move the version-floor comment onto _version_meets_floor.
- Tests for the offline-reuse and broken-shim paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim verbose comments across the Studio Node installer for PR #6533
Comments-only pass: collapse the multi-line section banners to single lines,
drop comments that restate obvious code, and tighten the remaining docstrings
and "why" notes without losing intent. No code changes (verified with an AST
comment-only check on the Python files and a non-comment-diff scan on setup.sh
and setup.ps1). Net 109 fewer lines; the install, decision, and probe-guard
suites stay green.
* Harden Node install from review: validated Python, version floor, legacy home, lock race
For PR #6533, addressing the latest review pass:
- setup.ps1: run the isolated Node install with the validated reused/venv Python.
An incompatible reused interpreter (old venv, conda, stale UNSLOTH_SETUP_PYTHON)
is no longer used; fall back to the resolved python instead.
- setup.ps1: a STUDIO_HOME/UNSLOTH_STUDIO_HOME override equal to the legacy default
now uses the legacy sibling node dir (~/.unsloth/node), matching the runtime
resolver and setup.sh, so OXC can find the Node it installed.
- install_node_prebuilt.py: reject an explicit --node-version below the floor
(^20.19 || >=22.12 || >=23) instead of installing a Node the build cannot use.
- install_node_prebuilt.py: atomically rename a stale install lock before unlinking
so two concurrent runs without filelock cannot both acquire it.
Tests added for the version floor (parametrized + explicit-below-floor rejection).
Full install suite: 937 passed, 1 skipped; setup.ps1 parses; decision tests green.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address latest review: armv7l + later-fetch offline reuse for PR #6533
- install_node_prebuilt.py: reject 32-bit ARM (armv7l) up front. Node 24 LTS
ships no linux-armv7l build, so the old path failed late with a confusing
"no sha256"; it now fails fast with a clear unsupported-architecture error.
- install_node_prebuilt.py: extend the offline-reuse fallback to the SHASUMS and
archive fetches. If index.json resolves a newer Node but a later download fails
and a usable isolated Node is already on disk, keep it instead of aborting a
non-force update.
Tests added: armv7l/armhf are unsupported; a SHASUMS failure keeps an existing
usable Node and re-raises when none is present. Full install suite: 941 passed.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add UNSLOTH_STUDIO_HOME node-dir tests (install side + resolver) for PR #6533
* Add regression tests pinning the reuse path read-only and isolating installer writes
Lock in the two invariants behind the isolated-Node design: reusing a good
system Node never mutates the user's Node/npm, and the installer's own npm
calls only ever write inside its install_dir.
- tests/studio/install/test_install_node_prebuilt_logic.py: assert _run_node
redirects NPM_CONFIG_PREFIX/npm_config_prefix into install_dir and drops an
inherited NODE_PATH; assert _ensure_npm_floor scopes the npm self-upgrade to
install_dir (never -g against the system) and is a no-op once npm meets the floor.
- tests/sh/test_system_node_readonly.sh (new, wired into studio-backend-ci.yml):
the setup.sh NODE_SOURCE=system arm runs no global install and sets no
NPM_CONFIG_PREFIX, with a positive control that the bundled arm does.
- tests/studio/test_node_decision.ps1: symmetric structural guard that the prefix
pin and the only global install (bun) live in the bundled branch, not the system arm.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* studio: run /generate/stream's sync generator off the event loop to avoid blocking it
* fix: close generator in finally on client disconnect in generate_stream
* Fix/adjust generate stream test for PR #6466
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix/adjust generate stream cancellation for PR #6466
* Fix/adjust generate stream cleanup for PR #6466
* fix: cancel incomplete generate stream cleanup
---------
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: imagineer99 <samleejackson0@gmail.com>
* Windows installer: repair a stale CPU PyTorch instead of looping forever
A Windows machine with an NVIDIA CUDA 13 driver (e.g. RTX 6000 Pro on enterprise
drivers) could get permanently stuck at:
Stale venv detected (torch cpu != required cu130).
[ERROR] The existing Studio environment needs repair.
Re-run install.ps1 so it can replace the environment safely with rollback.
Re-running install.ps1 did not help. install.ps1 installs torch with
"torch>=2.4,<2.11.0" --index-url .../cu130 but no --force-reinstall, so when a
torch==X+cpu is already present uv treats it as satisfying the range (PEP 440
ignores the +cpu/+cuXXX local label) and makes no change -- the CPU wheel is
never replaced. setup.ps1 then rejects the venv as cpu != cu130 and exits, but it
cannot create a venv or install torch, so the loop never resolves. The migrated-
venv branch also preserves existing torch and never reinstalls it.
After the install step, detect the installed torch flavor (cuXXX/cpu/rocm) and,
when it does not match the tag implied by the selected index, force-reinstall the
torch/torchvision/torchaudio triplet from the correct index via three
--reinstall-package flags. No-op on a healthy matching venv; skipped for
--no-torch, ROCm (already --force-reinstalls), and CPU-only machines.
Adds two pure helpers (ConvertTo-TorchFlavorTag, Get-ExpectedTorchFlavorTag), a
PowerShell unit test (tests/studio/test_torch_flavor.ps1), and a CI parse gate for
install.ps1 (previously unparsed).
* install.sh: repair a stale CPU PyTorch on Linux too (parity with install.ps1)
install.sh has the same latent bug as the Windows installer: the CUDA torch
install uses "torch>=2.4,<2.11.0" --index-url .../cuXXX with no
--force-reinstall, so an already-present torch==X+cpu satisfies the version
range (PEP 440 ignores the +cpu/+cuXXX local label) and uv leaves it in place.
The migrated-venv branch also preserves existing torch. Unlike Windows there is
no stale-venv check in setup.sh, so on Linux the symptom is silent CPU training
rather than a hard loop -- same root cause.
Mirror the install.ps1 fix: after the install block, detect the installed torch
flavor (_torch_flavor_tag) and, when it does not match the index tag
(_expected_torch_flavor_tag), force-reinstall the torch/torchvision/torchaudio
triplet from the selected index via --reinstall-package. No-op on a healthy
matching venv; skipped for --no-torch, ROCm (its own repair force-reinstalls),
and CPU-only / macOS hosts. Adds tests/sh/test_torch_flavor.sh (run in
studio-backend-ci and run_all.sh).
* Installer: catch CPU-fallback on AMD/WSL too (repair ROCm, warn when unfixable)
Extend the torch-flavor safety net beyond NVIDIA:
- install.sh now auto-repairs a stale CPU torch on standard pytorch.org ROCm
indexes too (the rocm-index install path lacked --force-reinstall, unlike the
Windows ROCm install). Reuses the rocm-adjusted $TORCH_CONSTRAINT + rocm index,
so it pulls the correct ROCm wheels.
- Both installers gain a universal post-install warning: when a GPU build was
expected (cuXXX / rocm, including the repo.amd.com gfx* arch indexes) but torch
is still CPU-only, warn loudly instead of silently training on CPU. This catches
the cases auto-repair cannot safely fix (AMD gfx arch indexes that need
--find-links, a migrated AMD venv on Windows where the ROCm install was skipped).
- Mac / Intel / CPU-only hosts resolve to the cpu index -> expected == installed
-> no-op, no false warning. WSL uses install.sh, so the NVIDIA repair + warning
apply there.
Adds Get-InstalledTorchTag (ps1) and _torch_index_repairable (sh) helpers and
extends both unit tests. gfx*/AMD indexes now map to the 'rocm' expected flavor.
* Installer: tighten torch-flavor comments (no logic change)
Condense the rationale comments added for the stale/CPU PyTorch repair in
install.ps1, install.sh and the two helper unit tests; same intent, fewer
lines. Comment-only: AST parse of install.ps1/setup.ps1 clean, helper unit
tests (15 ps1, 24 sh under bash and dash) and the integration sims
(24 ps1, 28 sh) still pass, banner markers the sims slice on are unchanged.
* Installer: bound torch probe, auto-repair gfx, fix ROCm gate parity
install.ps1: in Get-InstalledTorchTag, call WaitForExit(30000) and drain stdout
and stderr asynchronously instead of reading stdout synchronously first, so a
hung or noisy "import torch" (a wedged CUDA/driver, the exact failure this PR
targets) can no longer block the probe past the timeout.
install.sh and install.ps1: treat the repo.amd.com gfx* indexes as plain
--index-url reinstallable. They are PEP 503 simple indexes uv resolves in full
(torch plus every transitive dep) via --index-url, the same URLs the fresh
ROCm install paths already use, so a stale CPU torch on AMD Strix now auto-repairs
to the correct ROCm build instead of only warning.
install.sh: include */gfx* alongside */rocm* in the bitsandbytes install and
ROCm torch repair gates, so a custom UNSLOTH_AMD_ROCM_MIRROR whose path lacks
/rocm/ still installs the AMD bitsandbytes build and repairs ROCm torch.
tests/sh/test_torch_flavor.sh: gfx indexes now assert repairable, plus a
gfx1151 case and an unknown-mirror not-repairable case.
* install.ps1: guard Get-InstalledTorchTag against an empty python path
Make the early return explicit for an empty $PythonExe instead of relying on
Test-Path -LiteralPath '' returning false, so the probe stays safe under
Set-StrictMode or a future refactor that drops the [string] annotation.
* Load repo-code VLMs that register AutoModel in auto_map
FastModel.from_pretrained already falls back from the VLM auto class to
AutoModelForCausalLM for repo-code VL models that register only that class
in their auto_map (e.g. Nemotron-VL). Models like DeepSeek-OCR and
DeepSeek-OCR-2 instead register their architecture under AutoModel, so they
fell through to AutoModelForImageTextToText and raised "Unrecognized
configuration class ... for AutoModelForImageTextToText".
Generalize the guard: when neither vision auto class is registered, fall
back to whichever generic auto class the repo actually registered
(AutoModelForCausalLM, else AutoModel).
* Do not hard-error on a newly initialized position_ids buffer
RaiseUninitialized turns transformers' "some weights of ... were not
initialized" warning into a hard error. position_ids is a deterministic
arange buffer that transformers itself lists in
_keys_to_ignore_on_load_missing, so re-initializing it is correct rather
than a sign of a corrupt checkpoint. Some VLMs (e.g. DeepSeek-OCR) ship it
non-persistently, which tripped the guard. Allowlist position_ids alongside
the existing classifier/predictions head weights.
* Only ignore missing-weight records that are exclusively position_ids
The previous substring check skipped the whole "Some weights of ..." record
whenever position_ids appeared anywhere in it. Transformers reports every
missing key in one record, so a corrupt or incompatible checkpoint missing a
real parameter could load with randomly initialized weights as long as one
missing key contained position_ids. Parse the "newly initialized: [...]" list
and suppress only when every listed key is a position_ids buffer; otherwise
raise as before.
* Match the concrete VLM auto class name when checking auto_map
Transformers resolves remote code by the exact auto class name being called,
and AutoModelForVision2Seq aliases to AutoModelForImageTextToText on
transformers >= 5. Checking for both spellings treated a config that only
registers the legacy AutoModelForVision2Seq key as having a supported VLM
class, skipping the AutoModelForCausalLM fallback that used to load it and
failing as an unrecognized config under AutoModelForImageTextToText. Match
only the concrete class name we would actually pass, keeping the AutoModel
and AutoModelForCausalLM fallbacks.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Preserve VLM mode on the vLLM path when falling back to AutoModel
A repo-code VLM that registers only AutoModel or AutoModelForCausalLM (DeepSeek-OCR, Nemotron-VL) routes to that generic class, so is_vlm, derived from the resolved auto class, is False. That is correct for processor selection (these repos ship no AutoProcessor) but wrong for the vLLM path, where is_vision_model=is_vlm made vLLM treat a vision_config model as text-only and skip the VLM guard and conversion.
Add is_vlm_config, derived from the config vision_config (and gated on not text_only so a text-only resolve still wins), and use it for the fast_inference VLM guard and the is_vision_model flags passed to load_vllm, get_vllm_state_dict and convert_vllm_to_huggingface. Processor selection still uses is_vlm, so DeepSeek-OCR keeps loading via its tokenizer. DeepSeek-OCR with fast_inference now raises the clear 'Fast inference is only supported for ...' error instead of being mishandled as text-only.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Package scanners: close fail-open gaps in the sdist fallback and hidden-payload paths
Follow-up hardening on the now-blocking scanners so the enforcing gate cannot
report clean while a malicious artifact goes unscanned.
scan_packages.py
- Hidden payload: also flag a network call AND an os/subprocess exec that live
only in a blanked docstring/string of an exec/eval file (the fetch-then-run
shape of an exec(__doc__) dropper). Either alone in real code was already
covered; hidden together they are the payload.
- Pinned releases fail closed: _release_files no longer falls back to the latest
artifact when a pinned version is missing or empty, so a yanked/bad pin is an
error instead of a different file being scanned in its place.
- requires_dist is read from the pinned release's metadata, not the project-level
(latest) document, so a sdist-only pin follows its own dependency tree.
- Environment markers are evaluated (PEP 508) instead of dropping any marker that
merely contains the word extra, so default-true markers like extra != 'dev' are
kept; conservative fallback keeps a dep on any uncertainty.
- Transitive recovery is a depth-bounded worklist: a wheel dependency whose own
child is sdist-only is fetched (--no-deps) and scanned, then its children are
recovered in turn, rather than being silently skipped.
scan_npm_packages.py
- Baseline keys use the package-relative path instead of the basename, so the
same basename in a different directory is not over-suppressed.
Tests cover each case; full scripts pass AST and ruff checks.
* Address review: tighten marker scope, decoy-proof the dropper check, fail closed on missing pin metadata
- Markers: keep any dep whose marker can hold on another install target
(sys_platform == 'win32', python_version == '3.13'); only drop a marker that
depends solely on extra and is false with no extra. A scanner runs on one
target but must cover code installed on others. Pure-extra markers are
evaluated against default_environment() with extra unset.
- Hidden dropper: the network+exec docstring check now inspects the removed
(blanked) span directly, so a benign visible network or subprocess call cannot
mask a payload that still lives in a docstring. Carrier checks stay
blanked-only (an in-code carrier is already caught by the normal check), so
corpus findings are unchanged.
- requires_dist: a pinned version whose own metadata cannot be fetched recovers
nothing rather than substituting the latest release's dependency tree.
- Transitive recovery: the last-ditch direct-sdist branch also chases the
recovered package's declared deps, matching the other branches.
- npm baseline: schema bumped to v2 (package-relative keys); a pre-v2 baseline
with entries is ignored (fail closed) instead of mis-applying basename keys.
Tests cover each case; scripts pass AST, ruff, and the import-hoist verifier.
* Scanner: exclude comments from hidden-payload check, flag missing pin metadata as incomplete
Hidden network+exec detection now inspects only docstring/string spans (what exec(__doc__)/exec(<str>) can actually run), so a real exec() beside comments that mention a network and a subprocess call no longer false-positives. Missing pinned-release metadata in transitive recovery records a download_error so the --with-deps path fails closed instead of treating it as no dependencies. Adds regression tests for both.
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---------
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* Fix scan_packages.py --fix crash on download_packages() tuple return
`download_packages()` returns `(results, download_errors)`, but the two
`--fix`-path call sites still treated the return value as the bare results
list. `find_safe_version` did `downloaded = download_packages(...)` followed
by `if not downloaded:` (always false: a 2-tuple is truthy) and
`for _, archive_path in downloaded:`, which unpacked the results list into
two variables -> ValueError in the normal single-archive `--no-deps` case.
`_run_fix` indexed `downloaded[0][1]`, i.e. the second archive of the results
list instead of the first archive's path -> IndexError. So `--fix` crashed
exactly when a CRITICAL finding needed remediation. The main scan path already
unpacks the tuple; this aligns the two `--fix` sites with it.
Adds CPU-only regression tests for both sites.
Closes#6412
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Update scripts/scan_packages.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* Update scripts/scan_packages.py
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
* Studio: reach the published source asset when a mix build's commit 404s
A llama.cpp "mix" prebuilt records a merge commit that is never pushed to
the fork, so the codeload/archive URLs for that commit 404. The merged
source tree is instead published as a release asset alongside the prebuilt
(llama.cpp-source-commit-<sha>.tar.gz). The installer resolves that asset
URL from the approved-checksums manifest, but when the manifest omits the
top-level repo/release_tag the URL resolves empty, hydration falls through
to the 404-ing commit archive, and the prebuilt install drops to a slow
source build (or fails outright).
Extract exact_source_asset_url() and resolve the asset's host and tag
defensively: the artifact's own repo, then the manifest repo, then the
source repo; and the manifest release tag, then the tag we actually
installed the prebuilt from (the source asset is its sibling on the same
release). Normal installs build the identical URL as before, so this only
adds a working fallback for the degenerate manifest.
Add unit coverage for the resolver, including the empty repo/release_tag
regressions.
* Studio: cover exact_source_asset_url through the real parser chain
Add TestExactSourceAssetUrl.test_resolves_through_real_parser_chain, which runs
parse_approved_release_checksums -> preferred_source_archive -> exact_source_asset_url
so a regression in the parser or source-selection wiring cannot pass while only the
hand-built helper unit tests stay green.
* Keep server-side tools enabled under --secure and on every bind
--secure binds loopback and exposes Studio only through an authenticated
Cloudflare HTTPS tunnel, but it was grouped with a raw 0.0.0.0 bind and
force-disabled all server-side tools (web search, Python, terminal). The
process tool policy overrode the client's enable_tools request, so the
model was never told the tools existed and answered in plain text. The
plain 'unsloth studio' command had no way to re-enable and printed nothing.
Tools now default on for every bind. The bind host and --secure no longer
change the tool policy; only an explicit --enable-tools/--disable-tools
forces it on or off. Both 'unsloth studio' and 'unsloth studio run' accept
the flags and the startup banner states the resolved policy.
- run.py: replace _apply_default_tool_policy(host, secure) with
_apply_cli_tool_policy(enable_tools); add an enable_tools kwarg to
run_server and --enable-tools/--disable-tools to the argparse.
- _tool_policy.py: resolve_tool_policy defaults to on for every host and
no longer prompts on a network bind.
- studio.py: drop the secure-as-public tool gating, add the flags to the
plain command, and reword the startup banner.
- Update and extend the secure-flag and tool-policy tests.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Add tool-policy notice to plain server banner and refresh run --help
Follow-up to PR review:
- run.py: the plain 'unsloth studio' / --secure / direct run.py path went
through _emit_startup_output without any tool-policy line, so a
network-reachable launch was silent about code execution now that tools
default on. Thread enable_tools through _emit_startup_output /
_emit_secure_startup_output and print a one-line policy notice, followed by
a single stop hint.
- studio.py: the 'unsloth studio run' --enable-tools/--disable-tools and --yes
help still described the removed loopback-on/network-off default and the
confirmation prompt; reword to match the new policy.
- Add tests for the banner notice and the refreshed help text.
* Update CI tool-policy resolver tests for default-on behavior
tests/python/test_unsloth_run_tool_policy_resolver.py still asserted the
removed network-bind policy (0.0.0.0 and LAN IP default off, explicit enable
prompts and aborts on a declined prompt), so it failed the Python CI jobs.
Rewrite the truth table: every bind defaults on, explicit on/off always wins,
and the resolver never prompts (yes/silent/prompt kept for compatibility).
* Trim comments for the tool-policy change
Shorten the verbose docstrings and block comments added for --secure tool
handling; keep the security-relevant intent. Verified comment-only via an AST
diff (code unchanged).
* Add deterministic test that server-side tools execute under --secure
Drive the GGUF agentic tool loop with a fake llama-server stream and let the
real execute_tool run: python counts 1..100, terminal returns a UTC datetime,
and web_search runs through real _web_search with only the ddgs network
boundary mocked. A policy assertion pins that the post-fix --secure path
(policy None + per-request enable_tools) is what keeps these executions
reachable. No model, GPU, or live network; runs in the existing backend CI.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Align _emit_startup_output banner test with the moved stop hint
The tool-policy notice now prints between the access banner and the stop
hint, so the stop hint is emitted once at the end instead of inline in the
banner (include_stop_hint is False and print_studio_stop_hint runs once).
Update the plain-localhost case to match; the mismatch and wildcard cases
already asserted this wiring.
---------
Co-authored-by: Michael Han <michaelhan2050@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.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.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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---------
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The Linux installer ordered its CUDA runtime-line attempts purely by torch's
reported CUDA major (preferred_runtime_line), so a Blackwell host running a
cu12x torch build hoisted cuda12 ahead of an available native cuda13 bundle.
This brings the Linux selector to parity with the existing Windows Blackwell
preference: on an sm_120 host, prefer the highest CUDA-major line that ships
a bundle covering every visible host SM, then fall back to the torch line.
Selection-time only. No external pin and no source build: in-release cuda13
bundles already cover sm_120, and the per-artifact SM filter still drops any
incapable bundle (cuda12-older / cuda13-older) and prevents fall-through to a
non-Blackwell build. The override is gated on _host_is_blackwell and only
reorders lines that are already detected and driver-compatible, so it never
forces cuda13 when its runtime libraries are absent or the driver is pre-13,
and non-Blackwell hosts keep the exact torch-preference behavior.
The runtime-line ranking only considers well-formed "cuda<major>" lines and
skips any malformed or future-format value (e.g. "cuda13.1") instead of
crashing the major sort, matching how the surrounding selector already
tolerates unknown lines.
Adds focused selection tests covering the override, the incapable-cuda13
skip, the cuda13-unavailable fallback, the non-Blackwell no-op, the
malformed-runtime_line skip, and cuda14 forward-compat.
* studio: set _stats_logger in kill-process test backend
#6377 added a self._stats_logger cleanup step to _kill_process's finally block.
test_kill_process_records_timestamp_on_actual_kill (added in #6400) builds the
backend via __new__, which bypasses __init__ where _stats_logger is set, so once
both landed on main the test raised AttributeError: 'LlamaCppBackend' object has
no attribute '_stats_logger'. Set _stats_logger on the hand-built backend,
mirroring __init__, so the kill path's finally has the attribute it expects.
* test: assert torchao override step on normal Linux, not overrides.txt
#6400 moved the torchao dependency override from a fixed pin in overrides.txt to
a torch-matched spec installed via --force-reinstall (_select_torchao_spec), and
turned overrides.txt into a comment-only pointer. It updated the Windows variant
(test_windows_only_includes_overrides) to check for --reinstall, but left
test_normal_linux_includes_overrides asserting overrides.txt is installed, which
no longer happens. Check for the override step (--reinstall) instead, matching
the Windows test.
* test(ui): tolerate ERR_ABORTED on /login re-login in shutdown step
The Shutdown step re-logs in after a CLI password rotation that revoked the prior
token. The SPA auth guard can client-side-redirect mid-navigation against the
stale token, aborting page.goto("/login") with net::ERR_ABORTED. It is a race
(passes on main most of the time). Resolve on domcontentloaded and tolerate the
abort, relying on the password-field wait that follows to confirm we reached
/login, matching the wait_until used by the other navigations in this file.
* Studio: drop the VBS launcher to clear the Kaspersky false positive
The Windows shortcut launched Unsloth Studio through wscript.exe ->
launch-studio.vbs, and that VBS used CreateObject("WScript.Shell").Run to
start a hidden -ExecutionPolicy Bypass PowerShell. That wscript + .vbs +
bypass-powershell shape is the canonical trigger for generic VBS-dropper
heuristics (Kaspersky HEUR:Trojan.VBS.Agent.gen). The launcher is benign;
only its shape is the problem.
- install.ps1: stop generating launch-studio.vbs and point the Desktop /
Start Menu .lnk straight at powershell.exe -WindowStyle Hidden running
launch-studio.ps1. The shortcut is saved WindowStyle 7 (minimized) so the
brief console flash is muted. launch-studio.ps1 (health poll, port,
mutex, browser) is byte-for-byte unchanged.
- install.ps1: delete a pre-existing launch-studio.vbs on upgrade, so the
flagged file does not linger on machines that already installed it.
- install.ps1 / install.sh: run the heavier ie4uinit -ClearIconCache plus
StartMenuExperienceHost tile-cache rebuild only on a first install or a
real icon change, instead of on every no-op reinstall. That repeated
clear-cache plus kill cluster is itself a dropper-like behavioral pattern.
- tests: forbid VBS generation and require the legacy-VBS cleanup.
Linux, macOS and WSL install paths are unchanged. WSL already targets
wsl.exe from its .lnk and never used a VBS; its only change is the same
icon-cache gating.
* Studio: add launcher-chain smoke coverage to the Windows UI CI
The shortcut launch path was previously untested: studio-windows-ui-smoke
installed then booted `unsloth studio` directly, so a broken .lnk could ship
silently. After install the job now seeds a legacy launch-studio.vbs, asserts
the upgrade removed it, asserts the .lnk targets hidden powershell.exe (never
wscript.exe), and launches via the shortcut's stored command, waiting for
/api/health to report healthy.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Package scanners: cut false positives and make the CI gate blocking
scan_packages.py and scan_npm_packages.py red-failed on legitimate
library code, so the security-audit steps were left advisory. Reduce
the false positives at the source and flip both gates to blocking.
scan_packages.py:
- Scan code only: blank comments and bare docstrings/doctests before
matching (line numbers preserved), so prose and >>> examples cannot
trip a finding.
- Drop the platform.system() branch from the anti-analysis regex (under
DOTALL it matched across the whole file, so every cross-platform
library tripped it) and fix the dead /proc/self/status alternative.
- Add a reviewed baseline allowlist (scan_packages_baseline.json) keyed
on (package, basename, check): only non-baselined CRITICAL/HIGH exit
1, and a new kind of finding in a listed file still fails.
- sdist fallback: when --with-deps cannot resolve a shard (a sdist-only
package or a version conflict), drop to per-spec and fetch the raw
sdist from the PyPI JSON API (no pip build, no setup.py), so every
package is still scanned and no shard exits 2.
scan_npm_packages.py:
- Mirror the code-only JS/TS scanning (blank // and /* */ comments,
string/template/regex aware) and the baseline allowlist. The npm
corpus is clean today, so the baseline is empty.
security-audit.yml:
- Flip both scan steps to blocking (SCAN_ENFORCE=1), capturing the
scanner exit via PIPESTATUS so tee does not mask it.
tests/security: add coverage for the strip, baseline and sdist paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review feedback on the package scanners
- Do not blank f-strings during code-only scanning (they evaluate at
import); and when a file uses exec/eval, rescan the original for
payload carriers hidden in a docstring/string so exec(__doc__) style
payloads stay visible.
- sdist fallback: recover transitive deps with their version specifier
(fetch the pinned version, not latest), and recover deps in the
--no-deps branch too so a sdist-only transitive dependency is still
scanned instead of silently skipped.
- Baseline: key by package-relative path, not basename, so a future
same-named file in another directory is not auto-suppressed.
Regenerated the baseline accordingly.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* fix: use partial hipinfo output on crash to avoid CPU fallback (#6043)
`hipinfo.exe` on some RDNA 4 hosts (e.g. RX 9060 XT / gfx1200) exits
with STATUS_ACCESS_VIOLATION (0xC0000005) after printing the
gcnArchName line. The previous guard `$LASTEXITCODE -eq 0` in
studio/setup.ps1 and `if result.returncode == 0` in
install_python_stack.py discarded this partial-but-valid output,
causing the installer to fall through to WMI name inference which sets
HasROCm=false and installs CPU PyTorch instead of the ROCm wheel.
Fix: check for gcnArchName in stdout first; accept the arch regardless
of exit code. Only fall through to the amd-smi / WMI path when no
gcnArchName is present at all (crash before any output, or a genuine
"no device" error). A cyan INFO substep is emitted when the arch is
recovered from a crashed hipinfo run so users can see what happened.
Adds a regression test covering the crash-with-valid-output path.
Fixes#6043
* Fix/adjust hipinfo crash fallback for PR #6292
---------
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Studio: fix Mac IME input-method switch leaving composer Send disabled
On macOS, switching input method (Ctrl+Space / menu-bar language icon)
fires compositionstart but never compositionend — leaving composingRef
pinned at true and the Send button permanently disabled even after
switching back to English.
Two immediate recovery paths added to useImeComposerInputHandlers
(thread.tsx) and SharedComposer (shared-composer.tsx):
* onKeyDown else-if: clears composingRef on the first non-IME keystroke
after a stuck composition, unblocking Send on that very keydown rather
than waiting for the 2500ms watchdog.
* onBlur handler: clears composingRef unconditionally on textarea focus
loss — safe because the OS always commits or cancels any active
composition before surrendering focus to another element.
Two new Playwright regression steps (6e, 6f) added to
playwright_chat_ime_i18n.py assert recovery within 1500ms (well below
the 2500ms watchdog), covering both recovery paths.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix IME regression test idle handoff for PR #5762
* Fix IME cleanup console guard for PR #5762
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix IME Enter guard for PR #5762
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
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Co-authored-by: wasimysaid <wasimysdev@gmail.com>
* fix(studio): Windows GGUF cancel hang + CPU spinlock overhead (#5692)
Two fixes for Windows-native GGUF inference via llama-server:
**Issue 1 — GPU/CUDA Hang on Stream Cancellation:**
- Add `Connection: close` header to all httpx requests proxying to
llama-server, preventing Keep-Alive from masking downstream socket
closure.
- Introduce `_await_disconnect_then_close` background watcher that
polls `request.is_disconnected()` every 100ms and calls
`resp.aclose()` immediately when the client disconnects. This runs
alongside the existing cancel-POST watcher and covers client aborts
that never reach the /cancel endpoint (tab close, proxy aborts,
Colab, mobile navigation, etc.).
- Change all StreamingResponse `Connection: keep-alive` headers to
`Connection: close`.
**Issue 2 — High CPU Spinlock & KV Cache Backup Overhead:**
- Set OMP_WAIT_POLICY=PASSIVE and OMP_NUM_THREADS=2 in the
llama-server subprocess environment on Windows to prevent OpenMP
from spin-waiting on all logical cores while the GPU decodes.
- Limit `--threads` to 2 on Windows when the model is fully
GPU-offloaded (`-ngl -1`). Auto-detect otherwise.
- Pass `--cache-ram 0 --ctx-checkpoints 0 --no-cache-prompt
--checkpoint-every-n-tokens -1` on Windows to disable prompt-cache
snapshots that copy KV cache to system RAM over the WDDM/PCI-E bus.
Closes#5692.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix: use local import to avoid ruff F823 (sys used before assignment)
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* review: address gemini review feedback
- Simplify _fully_gpu_offloaded init: default to False, only set True
in the gpu_indices branch, drop redundant else.
- Log exceptions in _await_disconnect_then_close at debug level instead
of silent pass, per review suggestion.
* Adjust review feedback for PR #5749
- _await_disconnect_then_close: set cancel_event before resp.aclose() so
the streamer's RemoteProtocolError handler treats the watcher-driven
close as cancellation, not an upstream error. Both call sites pass
cancel_event through.
- Windows --cache-ram / --no-cache-prompt / --ctx-checkpoints block: gate
on _fully_gpu_offloaded so CPU and partial-offload Windows runs keep
prompt-cache reuse across turns.
- Windows OMP_WAIT_POLICY / OMP_NUM_THREADS env: same gate so CPU and
partial-offload Windows runs keep default OpenMP parallelism.
* Shorten code comments touched by PR #5749
* Clean up local imports and rename underscore locals in PR #5749
- Drop the function-local `import sys as _sys` introduced as an F823
workaround; remove the redundant in-function `import os`/`import sys`
block so module-level imports resolve sys/os instead. F823 no longer
triggers because no shadowing import remains inside load_model.
- Rename `_fully_gpu_offloaded` and `_t` to `fully_gpu_offloaded` and
`threads_arg`. Underscore-prefixed names usually mean private/module-
level; plain locals match Python style for in-function temporaries.
No behavior change. ruff clean, py_compile clean, 35 studio cancel-
infra tests + 13 launch-gating AST locks + 6 disconnect-watcher locks
+ 4 spoof live-import tests all pass.
* Fix Windows GGUF follow-ups for PR #5749
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix cache flag gating for PR #5749
* Fix Python 3.9 annotations for PR #5749
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---------
Co-authored-by: Anmol Mishra <anmolx.work@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* Studio: enable stdio MCP servers on a loopback bind
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Studio: address codex review on stdio MCP loopback gate
* Studio: fix banner URL and preserve stdio MCP env opt-in on network binds
* Studio: scope loopback to exact aliases and honor force-disable on run_server reuse
* Studio: cover force-disable across a public re-bind and fix a stale test comment
* Studio: keep stdio MCP off on Colab loopback launches
* Studio: set tool policy before server startup
---------
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* Expose MLX grad value clipping in Studio
* update test
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* dataset ordering + wd
* fix mlx smoke step expectations
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* cast norm activation output back to original input dtype
* address mlx studio review feedback
* Fix present-but-None seed override for PR #5656
studio/backend/core/training/worker.py
`config.get("model_random_state", random_seed)` only fills the
default when the key is absent. When a caller passes
`config["model_random_state"] = None` explicitly (which happens
any time a JSON payload sends an explicit `null`), the old code
forwarded `None` to FastMLXModel and disabled deterministic init
silently. Same for `lora_random_state`. Treat absent and explicit
None the same way: fall back to random_seed.
studio/backend/tests/test_training_raw_support.py
Update the source-string assertions to match the new lines.
* Guard optional MLXTrainingConfig fields and normalize random_seed for PR #5656
The MLX worker now passes `cast_norm_output_to_input_dtype` and
`dataset_order` only when the linked unsloth-zoo dataclass actually
declares them. Released zoo trees that predate the paired PR can still
construct `MLXTrainingConfig` without raising
`TypeError: unexpected keyword argument`. Once the dependency floor is
bumped to a release that contains both fields, the feature-detect
guards become no-ops.
`random_seed = config.get("random_seed", 3407)` was unguarded against
explicit `None` from raw / backend callers. The same value seeded the
trainer and was the fallback target for `model_random_state` /
`lora_random_state`. Normalize once at the top of the function and use
the normalized value everywhere so an explicit `None` cannot reach
FastMLXModel / get_peft_model / MLXTrainingConfig.
Existing seed source-pattern test updated to match the new normalize
helper. New test asserts the feature-detection guards exist and that
the unconditional kwargs do not include the gated fields.
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* Normalize seed / cast / max_grad_value at TrainingBackend for PR #5656
Round-3 review consensus: the per-field guards that landed in the MLX
worker only protect the MLX path. The same `TrainingBackend.start_training`
config still reaches the CUDA/text trainer at `worker.py:2267`, the
embedding LoRA init at `worker.py:2450`, and embedding TrainingArguments
at `worker.py:2624` with raw `None` values, so an explicit
`random_seed=None` from a raw / backend caller still breaks non-MLX
training even after the previous fix.
Move the normalization into `TrainingBackend.start_training` itself,
where it runs once for every training mode:
- `_coerce_seed(value)`: explicit `None`, non-int, or absent all become
3407. Every downstream worker now sees an int.
- `_coerce_optional_bool(value, default)`: explicit `None` falls back
to `default` instead of `bool(None) == False`. Also normalizes the
common raw-config / YAML string aliases ("true" / "false" / "0" /
"1"). Used for `cast_norm_output_to_input_dtype`.
- `_coerce_optional_nonneg_float(name, value)`: rejects negative
numerics from raw / backend callers, matching the Pydantic
`ge=0` constraint the HTTP route already enforces. Used for
`max_grad_value`.
worker.py MLX path: the existing `bool(config.get(key, True))` for
`cast_norm_output_to_input_dtype` was changed to also fall back on
explicit `None`, so direct worker callers (bypassing
`TrainingBackend.start_training`) are equally safe. `max_grad_value`
also raises on negative values inside the worker for the same reason.
TrainingStartRequest.random_seed default bumped from 42 to 3407 so
direct REST callers that omit the field receive the same default as
the Studio frontend and the MLX worker.
New regression test exercises the three new helpers across explicit
None, valid values, string aliases, and negative-value rejection.
* Tighten feature-detect test paren tracking for PR #5656
The block-extraction used , which stops at the
first inner closing paren (e.g. )
and would silently miss a future unconditional
/ added later in the same dict literal. Switched to
proper paren-depth tracking so the unconditional block is checked end-to-end.
* Shorten verbose comments in MLX Studio backend
* Handle MLX Studio EOS appending by mode
* Wire MLX leaf norm clipping through Studio
* Respect VLM layer filters for explicit LoRA targets
Rationale / guardrails for the local Studio/vision push:
When callers provide explicit VLM LoRA target_modules together with layer filters, FastVisionModel still needs to route the explicit targets through get_peft_regex. Otherwise the layer filters are ignored and adapters can be attached outside the requested language/vision scope.
Do not revert this to plain list(target_modules) for explicit module lists. The CUDA/Studio-facing contract is that explicit targets and layer filters compose: target_modules selects module names, while finetune_language_layers / finetune_vision_layers / finetune_attention_modules / finetune_mlp_modules constrain where those targets are allowed.
The regression test covers the language-only explicit q_proj case and source-checks that explicit targets are wrapped through get_peft_regex when filters are active.
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* Refresh MLX smoke clip-config note for leaf_norm default
Trim the 11-line comment block to 5 lines and correct the stale claim
that MLXTrainingConfig defaults to max_grad_value=1.0. The new default
is max_grad_leaf_norm=1.0 (same memory profile as elementwise but
direction-preserving). The smoke still pins max_grad_value=1.0
explicitly to keep the 13-seed pass-rate fixture stable.
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* Forward max_grad_leaf_norm through the training route and warn when layer filters constrain explicit target_modules for PR #5656
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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* Installer: drop redundant -WindowStyle Hidden from the Windows launcher VBS
The desktop / Start Menu shortcut launches Studio through a generated
launch-studio.vbs that runs:
shell.Run "powershell ... -WindowStyle Hidden -File launch-studio.ps1", 0, False
The second argument to shell.Run is intWindowStyle 0 (hidden), so WScript
already launches the child windowless. The child -WindowStyle Hidden is
therefore redundant: dropping it keeps the launcher hidden and behaviour
identical, while removing the WScript-spawns-hidden-ExecutionPolicy-Bypass
PowerShell token combination that antivirus heuristics weight. That shape was
reported as a Kaspersky HEUR:Trojan.VBS.Agent false positive during install.
Adds tests/studio/install/test_launch_studio_launcher.py to stop the flag from
being reintroduced and to assert the launcher stays windowless via
shell.Run(cmd, 0, False).
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* Fix llama.cpp prebuilt: skip the already-installed same-release fallback
install_prebuilt computes diffusion_visual_server_backfill_needed from the
newest candidate (plan.attempts[0]); when that is True it passed
existing_install_dir=None to validate_prebuilt_attempts, which disabled the
"existing install already matches this candidate" skip for the WHOLE plan. So
when the newest bundle failed validation the installer re-downloaded and
re-extracted an older fallback bundle that was already correctly installed.
Pass the real install dir always and gate the skip per-attempt: a matching
candidate is skipped unless that specific candidate still needs the
DiffusionGemma backfill re-extract.
Also make test_llama_cpp_search_roots_handles_studio_root_oserror read the full
_find_llama_server_binary / _kill_orphaned_servers method bodies instead of a
fixed 4000-char window. The except handler it asserts already exists, but the
function grew past the window so the guard silently failed; slicing to the next
sibling def keeps the check correct as the file grows.
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* fix: extend llama.cpp first-token timeout
* fix: timeout label pluralization
* studio: distinguish llama stream timeout phases
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* Fix/adjust timeout handling for PR #5841
* Fix lint failure for PR #5841
* Fix/adjust stream timeout handling for PR #5841
* Fix/adjust first token timeout for PR #5841
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* Fix/adjust passthrough timeouts for PR #5841
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* Fix/adjust preheader stream cancellation for PR #5841
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* Fix/adjust timeout PR diff for PR #5841
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* Fix/adjust Python 3.9 stream iteration for PR #5841
* Fix first body timeout for PR #5841
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* Fix first token timeout deadlines for PR #5841
---------
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
The prebuilt bundles ship llama-diffusion-gemma-visual-server, but
runtime_patterns_for_choice pruned it, so a fresh install never placed
it next to llama-server. ensure_diffusion_visual_server then found no
standalone release asset and skipped it, leaving Studio unable to serve
DiffusionGemma GGUFs natively (it required DG_VISUAL_BIN or a source
build). Keep the binary in the runtime allowlist on Linux, macOS and
Windows so it lands in build/bin and is activated automatically.
* install.sh: persist ROCm-on-WSL drop-in even when rocminfo already works
_maybe_bootstrap_rocm_wsl calls _ensure_rocm_probe_env (which exports a
transient HSA_ENABLE_DXG_DETECTION + adds /opt/rocm/bin to PATH on the
installer process) right before the "rocminfo enumerates gfx1151 -> already
set up, return early" gate. On any reinstall over an existing /opt/rocm --
the common case, since the uninstaller keeps shared ROCm userspace but
removes /etc/profile.d/unsloth-rocm-wsl.sh -- that probe env makes rocminfo
succeed, so the gate returns 0 WITHOUT ever persisting the drop-in. The
transient env dies with the installer, so the next login shell (Studio,
llama-server) sees no GPU: torch cuda_avail=False, rocminfo finds nothing,
the llama.cpp ROCm prebuilt segfaults on a GPU it can't reach.
Factor the drop-in writer into _persist_rocm_wsl_dropin() and call it before
the early return so the persistent env is restored whenever librocdxg is
present. Idempotent (only writes when the drop-in is missing), gated on
librocdxg so it never fires on non-WSL/non-ROCDXG hosts, root-writes or
sudo-tees like before. The fast-path branch now reuses the same helper.
Reproduced on gfx1151 (Radeon 8060S) under dash (the curl|sh shell):
before the fix a reinstall left the drop-in absent and torch cuda_avail
False; after, the drop-in is persisted and a fresh login shell reports
cuda_avail True. Verified under both dash and bash, and idempotent on
re-run.
* Studio WSL: load system HIP before a prebuilt's bundled runtime (gfx1151)
The lemonade / published llama.cpp ROCm prebuilts bundle their own HIP
runtime (libamdhip64) built for bare-metal Linux. In WSL the GPU is reached
through the system ROCm's librocdxg bridge over /dev/dxg, which the bundled
runtime cannot drive -- it segfaults on the first GPU call. So:
- install_llama_prebuilt.py: the prebuilt's llama-quantize/llama-server
validation runs with the bundle dir first on LD_LIBRARY_PATH, segfaults
(empty stderr), and the install silently falls back to a CPU source build
(which on this host can't even build for GPU -- hipcc absent). The Strix
Halo WSL user ends up on CPU despite a working GPU.
- llama_cpp.py: even if a GPU prebuilt were kept, the serve-time launcher
put the bundle dir first too, so it would crash at load.
Fix: on a ROCDXG WSL host (gated on /dev/dxg + "microsoft" /proc/version +
a librocdxg-providing /opt/rocm), prepend the system ROCm lib dir to
LD_LIBRARY_PATH so the WSL-capable libamdhip64 + librocdxg load first, while
the bundle still supplies libggml-hip / librocblas with the gfx1151 kernels.
Set HSA_ENABLE_DXG_DETECTION=1 alongside. Added _wsl_system_rocm_lib_dirs()
to both modules (kept identical so a prebuilt that passed install validation
runs the same way at serve time). Strict no-op on bare-metal Linux, NVIDIA,
macOS, and Windows.
Verified on gfx1151 (Radeon 8060S) in WSL (ROCm 7.2.1 + librocdxg, Adrenalin
ROCDXG): before, the lemonade gfx1151 prebuilt segfaulted and the install
fell back to a broken CPU build; after, install_llama_prebuilt validates and
keeps the GPU prebuilt (source=published, prebuilt_fallback_used=False), and
Studio serves Qwen3-1.7B-GGUF at 53 tok/s with the model resident in GPU
memory (llama-server device_info: ROCm0 = AMD Radeon 8060S).
* tests: cover the WSL ROCDXG drop-in + system-HIP-ordering fixes
- _wsl_system_rocm_lib_dirs: no-op without /dev/dxg, on bare-metal Linux,
and on WSL without librocdxg; returns the system lib dir on a ROCDXG WSL
host.
- binary_env: prepends the system ROCm lib dir ahead of the bundle and sets
HSA_ENABLE_DXG_DETECTION on WSL; unchanged on bare-metal Linux.
- install.sh: _persist_rocm_wsl_dropin exists, is gated on librocdxg, and the
rocminfo-already-works early return calls it before returning.
- llama_cpp.py: the serve-time launcher prepends the WSL rocm dirs before the
bundle dir (mirrors binary_env).
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* Tighten WSL ROCDXG fix comments (no logic change)
Condense the drop-in / system-HIP-ordering comments and docstrings added in
this PR. Verified comment-only via AST parse + py_compile + sh/bash -n, the
308-test rocm_support suite, and a dash functional re-run of the bootstrap
(drop-in still persisted, env still set).
---------
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* fix/uv-bytecode-timeout
* make sure that win installer upgrades uv for bytecode timeout
* Clarify uv bytecode timeout comment in install.sh and install.ps1
* Read installer scripts as UTF-8 in parity test so it runs on Windows
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* Prefer freshly installed uv when an older one shadows it on PATH
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* Fix EmptyLogits gathering in nested structure and patch recursively_apply on accelerator module
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* Wire EmptyLogits Accelerate patch into startup and fix find_device, pickling, tests for PR #6092
- Call patch_accelerate_recursively_apply() in _gpu_init.py so real imports
install it; previously it was only invoked by the tests
- Make both wrappers idempotent so repeated calls do not stack
- Rework find_device: skip EmptyLogits while still finding real tensors in any
order, keep returning None for tensor-free payloads (AlignDevicesHook relies
on None), fall back to PartialState().device only for sentinel-only payloads
- Give EmptyLogits stateless __reduce__ and drop the stomped pickle stubs on
EMPTY_LOGITS so debug mode gather_object works in real distributed runs
- Put test tensors on PartialState().device so the debug mode test also passes
on GPU machines, and add drift tests for startup wiring, idempotency and
find_device ordering
Verified on 2x B200: ACCELERATE_DEBUG_MODE=1 torchrun gather/broadcast/pad of
sentinel and mixed payloads all pass, training losses unchanged, full drift
suite 25/25.
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* Define EmptyLogits equality on the class for PR #6092
Gathered sentinel copies must compare equal in accelerate debug mode
regardless of whether the patched recursively_apply saw the sentinel first
in that process. Class body __eq__ requires restoring __hash__ explicitly.
Verified: 123 case simulation battery on accelerate 0.34.2 through latest,
2 process gloo CPU and NCCL GPU debug mode runs, drift suite 25/25.
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* Fix UnicodeDecodeError on Windows reading subprocess output in save path
On Windows the default text encoding is the locale code page (cp1252), not
UTF-8. The text-mode subprocess calls in save.py (text=True /
universal_newlines=True) set no explicit encoding, so they decode
llama.cpp / Ollama output with cp1252. When a child process emits a byte
undefined in cp1252 -- e.g. 0x9d, which appears inside the UTF-8 encoding
of common punctuation / box-drawing glyphs and in non-ASCII file paths --
the read raises UnicodeDecodeError and aborts GGUF export.
Add encoding="utf-8", errors="replace" to all 8 text-mode subprocess calls.
errors="replace" also avoids silent mojibake for inputs whose bytes happen
to be valid-but-wrong in cp1252.
Add tests/saving/test_save_subprocess_utf8_encoding.py:
- an AST drift detector asserting every text-mode subprocess call in
save.py pins encoding="utf-8" (runs without importing torch/unsloth_zoo)
- a behavioural test reproducing the cp1252 failure and the utf-8 fix
Relates-to: #2660
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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* add FastModel config passthrough
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* fix fastmodel config passthrough for task configs
* fix config-driven FastModel task model selection
* fix text only fastmodel task config selection
* fix fastmodel task config inference from user configs
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* fix fastmodel problem_type config passthrough
* fix fastlanguagemodel config passthrough: FastLlamaModel owns user config
* fix fastlanguagemodel config passthrough: forward user config to causal loads and keep checkpoint quantization_config
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The post-download llama-quantize / llama-server smoke test JIT-compiles CUDA kernels on the first GPU forward pass and stalls every install and update by minutes on Blackwell (sm_100). Gate it behind _RUN_STAGED_PREBUILT_VALIDATION, disabled for now, keeping the smoke test and the source-build fallback it triggers fully intact so it can be restored by flipping the flag to True.
Hashless external prebuilts (e.g. lemonade) are not in the approved-sha256 manifest and rely on the functional smoke test as their only integrity gate, so they are always validated regardless of the flag; only approved bundles, already proven by the sha256 manifest, skip it.
The sha256 archive verification and the static Linux/macOS preflights are unchanged and still run for every install.
test_sidebar_account_block_uses_leading_tight hardcoded gap-0.5 in its selector, but the sidebar account-block div moved to gap-px during UI polish (#6196), so the regex stopped matching and the test failed across every studio PR's Repo tests (CPU). Match the gap utility loosely (gap-\S+) since this guard is about the leading-* class for descender clipping, not the spacing.
* Handle rope_type 'default' on transformers 5 to stop false RoPE warning
transformers 5 reports rope_type="default" for every plain (unscaled) config
and dropped "default" from ROPE_INIT_FUNCTIONS. _compute_config_rope_inv_freq
then did ROPE_INIT_FUNCTIONS["default"], hit KeyError, returned None and logged
"Could not apply RoPE scaling 'default'; long-context generation may degrade"
on every model load. The inv_freq was still correct (the constructor recomputes
vanilla on None), but the warning is a false alarm for unscaled models.
Compute the unscaled inv_freq directly for rope_type "default"/None instead of
going through ROPE_INIT_FUNCTIONS, so plain configs return the right value with
no warning. Scaled types (llama3/linear/yarn/...) are unchanged.
Also skip test_object_style_rope_scaling_on_config_delegates_correctly when
transformers strict-validates rope_scaling (5.x): it rejects a non-dict object
on config.rope_scaling, so the object-style delegation path cannot be set up
there. The test still runs and asserts on transformers <5.
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* fix(rocm): stop overwriting ROCR_VISIBLE_DEVICES in apply_gpu_ids
ROCR_VISIBLE_DEVICES uses HSA agent-level indexing, not physical GPU
indices. Setting it to a bare integer breaks multi-GPU ROCm systems
where the parent already set ROCR_VISIBLE_DEVICES=0,1: narrowing to
1 causes torch.cuda.is_available() to return False in the training
worker, producing a misleading 'no HIP accelerator' error even on a
correctly configured ROCm host.
HIP_VISIBLE_DEVICES is sufficient for GPU selection on ROCm.
Leave ROCR_VISIBLE_DEVICES inherited from the parent environment.
* test(rocm): update apply_gpu_ids test to assert ROCR_VISIBLE_DEVICES is not overwritten
* Fix config.rope_scaling being dropped by the replaced rotary embedding (#2405)
On modern transformers, LlamaModel builds its rotary embedding from config
using unsloth's replacement LlamaRotaryEmbedding class, whose config path
computed vanilla inv_freq and ignored config.rope_scaling entirely. The
llama3/linear/longrope dispatch in patch_llama_rope_scaling rewrites
LlamaAttention.__init__, which no longer constructs rotary embeddings, so it
never fires; the model-level rotary is then copied onto every attention
layer. Result: Llama-3.1/3.2/3.3 ran with unscaled RoPE on the
FastLanguageModel path and collapsed into repetition loops past roughly 29K
tokens (PASS at 28867, FAIL at 31767 in needle retrieval). FastModel was
unaffected because vision.py keeps transformers' own rotary. qwen2, qwen3,
qwen3_moe, mistral and cohere assign the same base class, so any rope-scaled
config of those families was equally exposed.
The fix makes the base class config path compute inv_freq and
attention_scaling via transformers' ROPE_INIT_FUNCTIONS (covers llama3,
linear, dynamic, yarn, longrope), with an inline llama3 fallback reading
factors from config for older transformers, degrading to prior behavior on
any failure. attention_scaling is applied in _set_cos_sin_cache (1.0 default,
exact no-op for unscaled paths) and persists across extend_rope_embedding.
A type(self) guard prevents double-scaling via the legacy scaled subclasses.
Adds tests/utils/test_rope_scaling_drift.py (AST tripwire + behavioral
inv_freq/cos-cache/extension checks, validated to fail 4 of 5 on the unfixed
code) and wires it into the existing consolidated CI HARD GATE step.
Verified on GPU: 48K-token needle retrieval flips FAIL to PASS for
FastLanguageModel in bf16 and 4bit, 20K stays PASS, scaled inv_freq matches
transformers exactly, and the left-padded batch generation guard still gets
exact solo-vs-batched token matches.
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* Address review: normalize object-style rope_scaling, vectorize llama3 fallback
config.rope_scaling can be a config object rather than a dict on newer
transformers; _rope_scaling_as_dict normalizes it (to_dict/dict/vars
fallbacks) before any .get() access, with a regression test using a
dataclass stand-in. The inline llama3 fallback now uses torch.where instead
of a per-frequency Python loop; verified bit-for-bit equal to transformers
ROPE_INIT_FUNCTIONS for factor 8 (Llama-3.1) and factor 32 (Llama-3.2).
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* Address review: CPU-safe rope guard tests, normalized config for delegation
The rotary constructor builds per-device CUDA caches, so the behavioral tests
that instantiate it cannot run on GPU-less CI. Restructured into three layers:
the AST tripwire now also asserts the constructor stays wired to
_compute_config_rope_inv_freq; the CPU layer tests that pure helper directly
(llama3 dict, llama3 object, linear object, default type) with no
instantiation; the instantiation and cache tests are gated behind a real CUDA
probe (actual tensor allocation, so import-time CUDA spoofs cannot fool the
gate). Verified: 9 passed with GPU; 5 passed 4 skipped with CUDA hidden; 5
failed 4 skipped on the unfixed code in CPU mode.
Delegation to ROPE_INIT_FUNCTIONS now retries with a shallow config copy
carrying the normalized rope_scaling dict when the original was an object the
installed transformers cannot read; covered by a linear-object test, which has
no inline fallback and passes only through that retry path.
* Tighten comments in rope scaling fix and guard test
Comment and docstring reduction only; verified code-identical with
scripts/comment_tools.py check --strip-docstrings (AST signature match on
both Python files). All guard tests unchanged: 20 passed with GPU, 5 passed
4 skipped with CUDA hidden.
* Apply repo kwarg-spacing format
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* Stop HF 429 rate limits from sinking the llama.cpp prebuilt path in Studio CI
The Windows Studio API smoke job failed when anonymous huggingface.co
fetches of the tiny GGUF validation model (stories260K.gguf) hit HTTP 429
on the shared runner IP. The installer correctly refused the unvalidated
prebuilt and fell back to a source build, which the prebuilt assert then
flags. Three layers fix this:
1. Installer: auth_headers sends HF_TOKEN (or HUGGING_FACE_HUB_TOKEN) to
huggingface.co hosts, mirroring the existing GH_TOKEN handling for the
GitHub API rate limit. A redirect handler strips Authorization when a
download is redirected off-host (CDN signed URLs reject foreign auth;
urllib forwards headers on redirect, unlike requests/huggingface_hub).
2. Workflows: the HF_HOME prime steps also prefetch the validation model
so the install's hf_hub_download resolves from the local cache even
when the Hub is rate limiting; cache keys bumped v1 to v2 to repopulate.
This also covers fork PRs, which cannot see secrets.
3. Workflows: every Install Studio / update step that already passes
GH_TOKEN now also passes HF_TOKEN, so both the huggingface_hub path and
the direct URL fallback are authenticated.
Tests: tests/studio/install/test_hf_auth.py covers token-to-host routing,
the cross-host redirect strip, and the download_bytes wiring (offline).
Verified live: authenticated download of the validation model through the
new opener (CDN redirect exercised, pinned sha matches) and an offline
hf_hub_download cache hit against an HF_HOME primed by the new step.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Require a found ROCm DLL before forcing BNB_ROCM_VERSION in Studio paths
main.py previously set BNB_ROCM_VERSION=72 whenever HIP_PATH or ROCM_PATH
was set, and the training worker fell back to a blind 72 when DLL
detection found nothing. On a Windows machine with the AMD HIP SDK
installed but CUDA or CPU torch, that forces a ROCm backend onto a
non-ROCm bitsandbytes wheel, which raises at import. Both paths now only
write the override when a libbitsandbytes_rocm DLL actually exists (or a
seeded value is already present), matching the strict gates in
unsloth/import_fixes.py.
Also removes four redundant local import shutil statements in
unsloth/save.py that shadow the module-level import, the same pattern
that caused the UnboundLocalError fixed in #6149.
* Worker: gate the BNB override on a found ROCm DLL, preserving seeded marker
Review follow-ups: track _found_rocm_bnb in the worker like main.py so a
ROCm DLL with an unparsable name still gets the seeded or 72 fallback,
and skip the env write entirely when no DLL exists so a seeded value
keeps its sitecustomize marker and stays redetectable by later import
fixes.
Daniel Han