* Suppress FBGEMM CUTLASS "Arch conditional MMA" stdout spam on Blackwell GPUs
On Blackwell GPUs (B200/B100, SM100), FBGEMM's f8f8bf16_blockwise kernel
is hardcoded to cutlass::arch::Sm90 with no SM100 code path. When
test_has_fbgemm() probes this kernel, it fires 2304 "ERROR : Arch
conditional MMA instruction used without targeting appropriate compute
capability" lines before aborting and returning zeros.
The existing HidePrintMessage filter on sys.stderr (line 109) does not
catch these because CUDA device-side printf writes to stdout fd 1 at the
C level, bypassing Python's sys.stdout/sys.stderr entirely.
Fix: add suppress_cuda_printf() context manager in import_fixes.py that
redirects fd 1 and fd 2 to /dev/null at the OS level, with
torch.cuda.synchronize() and libc fflush before restoring. Wrap the
test_has_fbgemm() call in fp8.py with this context manager.
Tested on B200 with fbgemm-gpu-genai 1.4.0+cu130 and 1.5.0+cu130:
- Before: 2304 warning lines on every import
- After: 0 warning lines
- UNSLOTH_HAS_FBGEMM correctly set to 0 (Triton fallback works)
- Works with both UNSLOTH_ENABLE_LOGGING=0 and =1
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* Guard _libc init and fflush to prevent fd leak on failure
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* Fix VLM processor load degradation and vLLM CUDA version detection
vision.py - Fix VLM processor load for issue #4085:
- Before loading the processor, scan local config files and strip the
_Unsloth_Patched_ prefix. AutoProcessor.from_pretrained silently
degrades to a text-only tokenizer instead of raising an exception
when it encounters the unrecognized class name, so the existing
get_auto_processor fallback never triggers. Sanitizing the configs
before loading fixes backwards compat for old corrupted saves.
- After loading, detect when AutoProcessor returned a text-only
tokenizer for a VLM model (has no image_processor attribute) and
trigger the manual fallback constructor.
import_fixes.py - Fix vLLM CUDA version mismatch detection:
- _is_broken_vllm_error now also matches CUDA shared library errors
(libcudart, libcublas, libnvrtc) with "cannot open shared object
file". Previously it only matched errors containing "vllm._c" in
the message text, which missed cases where the error message was
about the missing CUDA library itself (e.g. vllm built for CUDA 12
on a CUDA 13 system).
- New _get_vllm_cuda_mismatch_message function extracts the CUDA
version from the error, compares to the system CUDA version via
torch.version.cuda, and returns a targeted install command using
the correct GitHub releases wheel URL.
- disable_broken_vllm uses the targeted message when a CUDA mismatch
is detected, falling back to the existing generic message otherwise.
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