Highlights Initial support for graph quantization to programmatically generate a quantized model from a floating-point one. ImageNet examples with PTQ can be found here: https://github.com/Xilinx/brevitas/tree/master/src/brevitas_examples/imagenet_classification/ptq . Initial support for QuantMultiheadAttention, which is leveraged for e.g. ViT support above. Various improvements to graph equalization, which are leveraged in the PTQ examples above. New accumulation-aware quantizers, to train for low-precision accumulation, based on our A2Q paper https://arxiv.org/abs/2301.13376 . Experimental support for BatchQuant quantizer, based on https://arxiv.org/abs/2105.08952 , currently still untested. Initial support for learned rounding. Overview of changes Graph quantization Initial graph quantization support by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/549 https://github.com/Xilinx/brevitas/pull/574 https://github.com/Xilinx/brevitas/pull/532 https://github.com/Xilinx/brevitas/pull/579 Quantized layers Initial support for QuantMultiheadAttention https://github.com/Xilinx/brevitas/pull/568 Breaking change: rename Quant(Adaptive)AvgPool to Trunc(Adaptive)AvgPool by @volcacius in https://github.com/Xilinx/brevitas/pull/562 Quantizers Weight normalization-based integer quantizers by @i-colbert in https://github.com/Xilinx/brevitas/pull/559 Accumulator-aware weight quantization by @i-colbert in https://github.com/Xilinx/brevitas/pull/567 BatchQuant quantizers support by @volcacius in https://github.com/Xilinx/brevitas/pull/563 QuantTensor Support to move QuantTensor across devices by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/528 Initial support for interpolate and pixel_shuffle by @volcacius in https://github.com/Xilinx/brevitas/pull/578 PTQ Batch Norm support in graph equalization by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/531 Mul support in graph equalization by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/530 Learned round support by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/573 MultiheadAttention and LayerNorm support in graph equalization by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/555 Fix calibration over large number of batches by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/523 Export Itemize scalar quantize args only in TorchScript QCDQ by @volcacius in https://github.com/Xilinx/brevitas/pull/561 Round avgpool export fixes by @volcacius in https://github.com/Xilinx/brevitas/pull/562 CI, linting Linter isort by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/505 CI: bump isort from 5.10.1 to 5.11.5 by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/540 Test: enable parallelism with pytest-xdist by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/513 GHA workflow improvement by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/507 Add support for yapf by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/511 FX Disable FX backport on 1.8.1+ by @volcacius in https://github.com/Xilinx/brevitas/pull/504 Examples Pretrained Resnet18 example on CIFAR10 targeting FINN by @volcacius in https://github.com/Xilinx/brevitas/pull/577 Graph quantization + PTQ examples and benchmarking scripts by @Giuseppe5 in https://github.com/Xilinx/brevitas/pull/547 https://github.com/Xilinx/brevitas/pull/575 https://github.com/Xilinx/brevitas/pull/576 For the Full Changelog please check : https://github.com/Xilinx/brevitas/compare/v0.8.0...v0.9.0