Xilinx/brevitas: Release v0.12.1

Highlights The most important changes in this release cycle: (MX)FP quantizers moved out of experimental — floating-point / MX quantizers are now first-class, supported quantizers. (#1488) Experimental vLLM export support — new export path targeting vLLM. (#1444) Learned Round refactor + documentation — reworked learned round in the common examples with dedicated docs. (#1323, #1485) LLM customization plugins — custom trainer support and a custom quantizer plugin to modify the quantized model, plus the ability to pass custom quantizers via the common quantizer API. (#1474, #1508, #1456) GGUF improvements — quantize high-impact layers to high precision and attach metadata to GGUF exports. (#1532, #1527) PeRQ (formerly MixQuant) — initial MixQuant support added, then renamed to PeRQ throughout the codebase and docs. (#1448, #1521, #1525) Python 3.13 support. (#1451) Utility to replace weights with quantized ones. (#1505) Signed scaling — signed scaling stats in core and signed scales in the LLM entry point. (#1393, #1449) Blockwise / block rotations — support for blockwise rotations and the option to disable fused block rotations. (#1434, #1438) New search algorithms for LLM experiments (#1357) Breaking Changes LLM: load as much data as needed — data loading behavior changed in the LLM examples. (#1514) Removed Python 3.9 support. (#1481) Deprecated old Python and Torch versions. (#1392) numpy is now an optional extra — installs no longer pull in numpy by default. (#1403) Minimum transformers version now enforced. (#1510) CLI rename: block_rotation_dim → rotation_block_size. (#1464) Deprecated unused MLIR export in the LLM examples. (#1467) All Commits Features Feat (benchmark): Allow easy specification of different search algorithms within benchmark scripts (#1357) Feat (brevitas_examples/llm): custom trainer support (#1474) Feat (ex/axe): improved implementation with extended support/testing (#1181) Feat (gguf): enabling quantization of high-impact layers to high precision (#1532) Feat (utils): utils to replace weights with quantized ones (#1505) Feat (utils): reducing variance on power_iteration func (#1519) Feat (ex/llm): custom quantizer plugin allows to modify quant model (#1508) Feat (quant/float): move (MX)FP quantizers out of experimental (#1488) Feat (brevitas_examples/llm)!: load as much data as needed (#1514) Feat (llm): enabling narrow_range for inputs in LLM entry point (#1524) Feat (benchmark): Minor tweaks to run_args_bucket_process (#1523) Feat (loss): support for high precision loss (#1496) Feat (docs): Documentation for Learned Round (#1485) Feat (vLLM): experimental support for vLLM export (#1444) Feat (ex/common): learned round refactor (#1323) Feat (brevitas_examples/llm): better dataset handling (#1461) Feat (brevitas_examples/llm): Use dataloader in AWQ (#1489) Feat (ex/llm): Signed scales in LLM entrypoint (#1449) Feat (brevitas_examples/llm): deprecate unused MLIR export (#1467) Feat (cli): rename block_rotation_dim to rotation_block_size (#1464) Feat (brevitas_examples/llm): fineweb support (#1459) Feat (bit_width): generalize restrict_impl with clamping (#1457) Feat (equalize): adding initial support for MixQuant (#1448) Feat (common/quantizer): Enable passing custom quantizers (#1456) Feat (brevitas_examples/llm): compute perplexity at float32 (#1458) Feat (equalize): option to disable fused block rotations (#1438) Feat (optim): decoupling dtype of CayleySGD from params (#1443) Feat (brevitas_examples/llm): Support for batched inputs in GPXQ/Qronos (#1427) Feat (brevitas_examples/llm): better RMSNorm replacement (#1436) Feat (brevitas_examples/common): mse scale for weights with float quant (#1433) Feat (brevitas_examples/llm): support for blockwise rotations (#1434) Feat (graph/equalize): minor refactor (#1432) Feat (core/stats): signed scaling stats (#1393) Feat (core): module for runtime computation of exp bias (#1418) Feat (brevitas_examples/llm): support for distillation loss (#1388) Feat (quant/mx): Added midmax scale rounding option to MX types (#1409) Feat (nn): add HardSwish activation function (#1406) Feat (gpxq): enabling selection of device and dtype (#1405) Feat (loss/bit_width): removable hooks (#1407) Feat (export/onnx): fallback export to fake quantized weights (#1395) Feat (core/float): better max mantissa computation (#1391) Feat (quant/float): configurable float bit-width implementations (#1373) Feat (brevitas_examples/llm): adding test split (#1375) Fixes Fix (stats): Mix MSE for zero-point (#1491) Fix (fx): push support for value_tracer (#1538) Fix (tests/permute): use symbolic_trace instead of dynamo (#1539) Fix (tests/permute): use symbolic_trace instead of dynamo (#1536) Fix (export/onnx): Update ONNX dynamo export for PT2.9 API (#1526) Fix (core/float): better handling of continuous mantissa bit-width (#1528) Fix (brevitas_examples/llm): patch dynamo FX with torch 2.10+ (#1533) Fix (core/stats): typo in variable name in MeanLearnedSigmaStd (#1530) Fix (brevitas_examples/gguf): adding metadata to GGUF export (#1527) Fix (brevitas_examples/llm): correct zero-shot handling of thinking models (#1518) normalization fix and new tests (#1504) Fix: restore model_cache_implementation to model.generation_config (#1516) Fix (stats): Set correct reduce_dim for group_dim<0 (#1512) Fix (brevitas_examples/data): fix evaluation of wikitext2 (#1495) Fix (ex/llm): Allow setting dataset limit for lighteval (#1492) Fix (graph/gpxq): ConvTranspose temporarily unsupported (#1490) Fix (brevitas_examples/llm): enable wikitest test split with fineweb and pile (#1487) Fix (brevitas_examples/llm): remove_hooks after fused_rotation_no_fx (#1480) Fix (graph/equalize): general check for fast_hadamard_transform (#1484) Fix (fx): bump version guard for value tracer (#1482) Fix (rotation): fix extra compile keys in state dict (#1472) Fix (brevitas/quant): Fix MX MSE quantizer (#1468) Fix (brevitas_examples/llm): fix to RMSNorm context manager (#1471) Fix (graph): enable ROCm path in _apply_had_device (#1469) Fix (brevitas_examples/llm): args based BOS for lm_eval (#1462) Fix (brevitas_examples/llm): compile support with merged rotations (#1429) Fix (graph/qronos): Normalize contribution to H and G when buffer is disabled (#1440) Fix (brevitas_examples/llm): fix transformers tests (#1446) Fix (brevitas_examples/quantizers): correct stats for dynamic quants (#1445) Fix (brevitas_examples/llm): more checks for FX-related args (#1441) Fix (brevitas_examples/llm): correct batch size for lm_eval (#1430) Fix (proxy): preserve training state after tensor_quant re-init (#1419) Fix (core): import scaling before zero point to prevent circular import (#1422) Fix (src/brevitas/quant_tensor/base_quant_tensor.py): Added torch.float64 to dict of tolerances (#1417) Fix (brevitas_examples/imagenet/ptq): DataLoader Fix (#1420) Fix (equalize): Fix LayerwiseActivationRotation (#1413) Fix (graph/rotation): small refactor and documentation (#1382) Fix (nn/bias): propagate runtime_shape from QuantScaleBias (#1385) Fix (core/scaling): fix dtype for int threshold (#1404) Fix (Notebooks): Corrected typos/small errors in the text cells with explanations (#1399) Fix (export/onnx): import GLOBALS from correct location depending on torch version (#1398) Fix (ex/llm): Fix integration with Lighteval Python API (#1379) Fix (ex/llm): Recursively unwrap equalized layer (#1390) Fix (paper/expand): Avoid skipping baseline experiment (#1383) Setup & Dependencies Setup: minimum version for transformers (#1510) Setup: support for python 3.13 (#1451) Deps (python): remove python 3.9 support (#1481) Setup: unpin transformers (#1415) Deps (ex/llm): Fixed perf<0.18 to be compatible with transformers==4.50.0 (#1421) Deps (numpy): switched numpy to be an optional extra (#1403) Deps (onnxscript): limit onnxscript<0.5.4 (#1400) Setup: deprecate old python and torch versions (#1392) Setup: pin numexpr version (#1389) Setup: fix requirements for HF packages (#1386) Deps: comment out GH dep Docs Docs: update dev docs (#1531) Docs: update PeRQ and Qronos references in docs (#1525) Docs: renaming MixQuant to PeRQ (#1521) Docs: documentation for MixQuant (#1470) Docs: correct index in Papers section (#1476) Docs: post-training expansion documentation (#1465) Docs: generate dev and v0.12.1 docs Tests & CI Test (ex/llm): remove redundant mock from lighteval tests (#1493) Test (qonnx): Fixes to QONNX export tests when (dynamo=True) (#1473) Test: test ONNX dynamo export with torch >= 2.7 (#1455) Test (brevitas_examples/llm): new lm_eval tests (#1431) Test (brevitas_examples/llm): added test of lighteval with rotation (#1425) Test (graph): restore skipped tests (#1374) Test (diffusers): skip torch 2.1 due to diffusers incompatibility (#1378) CI (periodic): Added periodic tests for the entire suite of supported versions (#1368) New Contributors @surajkarki66 made their first contribution in https://github.com/Xilinx/brevitas/pull/1406 @xkucerak made their first contribution in https://github.com/Xilinx/brevitas/pull/1420 Full Changelog: https://github.com/Xilinx/brevitas/compare/v0.12.1...v0.13.0

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