foxglove 1.0.0

What's Changed

hls4ml v1.0.0 "foxglove" introduces several significant improvements:

• A new QONNX frontend by @jmitrevs introduced in #979
• The ability for hls4ml to automatically infer the precision of data types by @vloncar introduced in #855
• The addition of an experimental backend for Intel oneAPI by @jmitrevs introduced in #955
• The addition of a backend for Siemens Catapult by @dgburnette in #956
• Added support for HGQ proxy models by @calad0i in #914
• An API for hardware-aware optimization by @bo3z in #768 and #809

The full list of other improvements and fixes is:

• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #949
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #953
• hls4ml Optimization API [Part 1] by @bo3z in #768
• QKeras support for RNN layers by @laurilaatu in #856
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #962
• Try to fix sphinx problem by restricting tensorflow-model-optimization by @jmitrevs in #967
• Bump pre-commit/action from 3.0.0 to 3.0.1 by @dependabot in #968
• Change fractional (and others) to be a property, move quantizers by @jmitrevs in #964
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #969
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #971
• vitis backend tarball fix by @calad0i in #972
• remove special vitis version of nnet_dense_resource.h by @jmitrevs in #975
• Allow Vitis synthesis tests by @jmduarte in #927
• Fix cleanup of synthesis tests (leftover from 927) by @vloncar in #989
• Fix sphinx by pinning tensorflow<=2.15 by @jmduarte in #992
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #984
• add clock uncertainty configuration option by @jmitrevs in #870
• Stage initial set of changes for the Catapult backend by @dgburnette in #956
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #999
• fix unwanted tested file change in #956 by @calad0i in #1000
• Fix SR backend synth missing variables by @bo3z in #993
• Upsampling support for PyTorch models by @vloncar in #977
• Split fpga_types into separate files by @vloncar in #998
• Support negative_slope in quantized_relu by @vloncar in #987
• Group more tests per YAML to reduce the number of envs created by @vloncar in #996
• Automatic precision inference by @vloncar in #855
• Remove unnecessary transposes related to conversion to channels_last format by @vloncar in #976
• Update pytest docker image to 0.5.4 by @jmitrevs in #1005
• Fix pre-commit warning and change '.h5' to '.keras' for written output by @jmitrevs in #1006
• Fix extension test for Keras v3 by @vloncar in #1009
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1007
• updated pytest docker image by @jmitrevs in #1017
• SepConv1d/2d for io_parallel with Latency strategy by @vloncar in #1012
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1021
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1023
• Latency Pooling Header Updates by @calad0i in #973
• Make im2col default option for quartus by @calad0i in #1010
• add protection for when kernel_quantizer is None by @jmitrevs in #997
• prevent test directory overwrites for activation by @jmitrevs in #1031
• Update Jenkinsfile to use new Docker image and Python 3.10 environment by @vloncar in #1033
• clean-up test ci yaml generater by @calad0i in #1036
• Add View to layer name map for pytorch parser by @JanFSchulte in #1039
• Add RNN support for Pytorch by @JanFSchulte in #850
• Add Vitis to pytorch API tests by @JanFSchulte in #1040
• clean up mult-dimensional dense by @jmitrevs in #1042
• Add namespaces and optional writer config by @vloncar in #986
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1044
• Add support for HGQ proxy model by @calad0i in #914
• Bug Fix for Operand Shape Mismatch in BatchNorm Fusion (PyTorch) by @sei-rquartiano in #1045
• remove precision settings that make pytest for batchnorm in pytorch fail by @JanFSchulte in #1053
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1047
• rm slow mnist training in test by @calad0i in #1018
• Add an optimizer to replace SeparableConv by Depthwise + Conv (pointwise) by @jmitrevs in #1022
• Add functionality to use granularity option also for pytorch models by @JanFSchulte in #1051
• Update pooling logic for Vivado, Vitis, and Catapult backends by @jmitrevs in #1056
• remove padding attribute by @jmitrevs in #1061
• Run long-running pytests out of the batch by @vloncar in #1062
• Fix tanh activiation in pytorch parser by @JanFSchulte in #1055
• make auto the default for layer config by @jmitrevs in #1016
• remove checks on 'padding' that were missed in previous PR by @jmitrevs in #1064
• Remove extras flow by @vloncar in #1067
• Expose alpha and theta type for parametrized activations by @jmitrevs in #1069
• Raise exception on compile errors by @vloncar in #1068
• update qkeras in Jenkinsfile by @jmitrevs in #1072
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1075
• hls4ml Optimization API [Part 2] by @bo3z in #809
• Hardcore weight txt path by @vloncar in #1089
• quote the ${WEIGHT_DIR} to handle special characters by @jmitrevs in #1091
• Beginnings of the oneAPI backend by @jmitrevs in #955
• update keras activation parsing, especially leaky relu by @jmitrevs in #1085
• Fix softmax parsing in pytorch and add test by @JanFSchulte in #1086
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #1098
• Change indexing in filling result for io_parallel convolutions, Vitis by @jmitrevs in #1102
• Update QONNX parsing for 1.0 by @jmitrevs in #979
• remove incorrect input from Constant nodes by @jmitrevs in #1119
• add max_precision to onnx parser by @jmitrevs in #1113
• Add RF to config templates for "Merge"...

edelweiss 0.8.1

What's Changed

• Fix for #905 by @calad0i in #906
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #921
• Fix logos in README.md by @vloncar in #930
• Fix writer precision when fp bits >= 14 by @calad0i in #909
• Let repack_stream optimizer inheirt original precision by @calad0i in #907
• Update A3D3 grant no. by @schsu in #941
• Add precision inherition for when generating stream clone by @calad0i in #911
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #942
• Quartus multi out with stream fix by @calad0i in #908
• Fix profiling for Keras LSTM layers. by @Landay7 in #940
• Fix for multiple inputs that may get out of order by @jmduarte in #937
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #944
• Bump actions/upload-artifact from 3 to 4 by @dependabot in #943
• better repalce_node fn by @calad0i in #934
• bump to 0.8.1 by @jmitrevs in #945

New Contributors

• @schsu made their first contribution in #941
• @Landay7 made their first contribution in #940

Full Changelog: v0.8.0...v0.8.1

edelweiss 0.8.0

What's Changed

• Decouple pipeline style from strategy by @vloncar in #781
• Don't use reader in ModelGraph and layers by @vloncar in #770
• Remove tf_to_hls by @vloncar in #795
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #796
• Fix parsing of QConv2DBatchnorm weights by @vloncar in #802
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #801
• Discussion - Inlined Conv slows down latency significantly (up to x15 - x20) by @bo3z in #800
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #807
• Fix over-allocation of bits for quantised po2 by @bo3z in #806
• Propagate zeros from Conv layers to multiplication config by @bo3z in #797
• Fix Vitis Conv1D/2D latency strategy by @vloncar in #815
• Improved parsing of pytorch models using torch.FX - Clean by @JanFSchulte in #799
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #816
• Support for parsing nested models by @vloncar in #794
• Fix loading weights in n-dim dense -> 1x1 conv by @vloncar in #821
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #828
• Fix loading weights in GarNetStacked and GarNet internal array precisions by @joshlerner in #827
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #830
• Fix profiling for GRU/LSTM by @drankincms in #833
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #835
• remove obsolete and unused docker directory by @jmitrevs in #836
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #842
• Remove obsolete parameter mapping between pytorch and keras by @JanFSchulte in #847
• Make binary CNN match between Keras and hls4ml by @jmitrevs in #804
• No longer make ExponentPrecisionType and XnorPrecisionType inherit from IntegerPrecisionType by @jmitrevs in #845
• Add support for flattening to the pytorch parser by @JanFSchulte in #852
• Add option to configure IP version by @AdrianAlan in #851
• Bug fix for named nn.Sequential in pytorch parser by @JanFSchulte in #848
• Add QDepthwiseConv2D, DepthwiseConv2D, DepthwiseConv1D support by @jmitrevs in #834
• Symbolic expressions in hls4ml by @vloncar in #660
• Update dependencies, add testing extras by @jmitrevs in #837
• Bump actions/checkout from 3 to 4 by @dependabot in #866
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #869
• try to use new runners for gitlab CI by @jmitrevs in #879
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #880
• Fix weight precision format string by @vloncar in #877
• add acknowledgments by @jmduarte in #862
• Support for quantized SeparableConv1D/2D by @vloncar in #861
• Speed up Keras profiling by @AdrianAlan in #863
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #882
• Fix profiling SeparableConv1D and SeparableConv2D by @qberthet in #891
• Add support for filt_height==1 for streaming quartus conv2d by @jmitrevs in #886
• Fix config structure name in pragma for SeparableConv1D by @qberthet in #884
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #895
• Fix bit overflow with softmax by @calad0i in #887
• bump 0.8.0rc1 by @jmitrevs in #915
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #902
• Add funding acknowledgements by @jmduarte in #918
• Fix fetching models from example-models repo by @vloncar in #919
• add blank line to make rst format correct by @jmitrevs in #923
• Update default FPGA part number from KU115 to VU13P by @jmduarte in #924
• update to 0.8.0 by @jmitrevs in #925

New Contributors

• @pre-commit-ci made their first contribution in #796
• @joshlerner made their first contribution in #827
• @qberthet made their first contribution in #891

Full Changelog: v0.7.1...v0.8.0

edelweiss 0.8.0rc1

What's Changed

• Decouple pipeline style from strategy by @vloncar in #781
• Don't use reader in ModelGraph and layers by @vloncar in #770
• Remove tf_to_hls by @vloncar in #795
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #796
• Fix parsing of QConv2DBatchnorm weights by @vloncar in #802
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #801
• Discussion - Inlined Conv slows down latency significantly (up to x15 - x20) by @bo3z in #800
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #807
• Fix over-allocation of bits for quantised po2 by @bo3z in #806
• Propagate zeros from Conv layers to multiplication config by @bo3z in #797
• Fix Vitis Conv1D/2D latency strategy by @vloncar in #815
• Improved parsing of pytorch models using torch.FX - Clean by @JanFSchulte in #799
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #816
• Support for parsing nested models by @vloncar in #794
• Fix loading weights in n-dim dense -> 1x1 conv by @vloncar in #821
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #828
• Fix loading weights in GarNetStacked and GarNet internal array precisions by @joshlerner in #827
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #830
• Fix profiling for GRU/LSTM by @drankincms in #833
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #835
• remove obsolete and unused docker directory by @jmitrevs in #836
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #842
• Remove obsolete parameter mapping between pytorch and keras by @JanFSchulte in #847
• Make binary CNN match between Keras and hls4ml by @jmitrevs in #804
• No longer make ExponentPrecisionType and XnorPrecisionType inherit from IntegerPrecisionType by @jmitrevs in #845
• Add support for flattening to the pytorch parser by @JanFSchulte in #852
• Add option to configure IP version by @AdrianAlan in #851
• Bug fix for named nn.Sequential in pytorch parser by @JanFSchulte in #848
• Add QDepthwiseConv2D, DepthwiseConv2D, DepthwiseConv1D support by @jmitrevs in #834
• Symbolic expressions in hls4ml by @vloncar in #660
• Update dependencies, add testing extras by @jmitrevs in #837
• Bump actions/checkout from 3 to 4 by @dependabot in #866
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #869
• try to use new runners for gitlab CI by @jmitrevs in #879
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #880
• Fix weight precision format string by @vloncar in #877
• add acknowledgments by @jmduarte in #862
• Support for quantized SeparableConv1D/2D by @vloncar in #861
• Speed up Keras profiling by @AdrianAlan in #863
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #882
• Fix profiling SeparableConv1D and SeparableConv2D by @qberthet in #891
• Add support for filt_height==1 for streaming quartus conv2d by @jmitrevs in #886
• Fix config structure name in pragma for SeparableConv1D by @qberthet in #884
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #895
• Fix bit overflow with softmax by @calad0i in #887
• bump 0.8.0rc1 by @jmitrevs in #915

New Contributors

• @pre-commit-ci made their first contribution in #796
• @joshlerner made their first contribution in #827
• @qberthet made their first contribution in #891

Full Changelog: v0.7.1...v0.8.0rc1

delphinium 0.7.1

What's Changed

• bump version to v0.7.0 by @jmduarte in #778
• Fix for 2D conv layers in the special case of io_parallel with full parallelization by @drankincms in #760
• Fix RNN layers when strategy=resource by @vloncar in #780
• Update Jenkins test environment to avoid dependency hell by @vloncar in #786
• Explicitly set strategy for pointwise conv by @vloncar in #785
• Minor docs fixes for 0.7.1 by @vloncar in #788
• bump 0.7.1 by @jmitrevs in #791

Full Changelog: v0.7.0...v0.7.1

delphinium

What's Changed

• fix conv1d io_parallel resource by @jmitrevs in #403
• Speed up CI tests by @thesps in #407
• Fix GlobalPooling1D Layers by @jmduarte in #399
• Fix batched multiple inputs by @jmduarte in #414
• Fixed 'qkeras_mnist_dense' example build problem #423 by @siorpaes in #424
• Update for pyyaml 6.0 by @thesps in #435
• axi_stream_driver update by @nicologhielmetti in #420
• Reshape fixes: don't repack stream for flatten; remove final reshape by @jmduarte in #443
• Fix Conv2D with io_type = io_parallel & Strategy: Resource by @thesps in #448
• Support applying Softmax over multidimensional tensors by @vloncar in #384
• Disable some unsupported layers by @thesps in #447
• Fixes: quantized_relu & unsigned profiling part II by @thesps in #441
• GarNet and GarNetStack in config.py by @yiiyama in #344
• support ZeroPadding layers by @jmduarte in #480
• New backend development framework by @vloncar in #395
• Register ApplyAlpha layer templates by @thesps in #499
• Parsing extended by @nicologhielmetti in #501
• Remove intermediate casting in product by @jmitrevs in #490
• Add QKeras as a package dependency by @vloncar in #511
• Copy flows from config by @thesps in #510
• VivadoAccelerator backend updates by @thesps in #508
• Optimized look-up table by @nemerchiedde in #527
• Upsampling2D test case by @ChiRuiChen in #520
• Support UpSampling1D by @vloncar in #475
• RNN support (part 1) by @vloncar in #521
• Quartus Custom Matrix Multiplication & Quantization by @bo3z in #523
• Vivado-equivalent implementation of Softmax on Quartus by @bo3z in #540
• Ensure 2 bits for scale in po2 quantizers by @vloncar in #531
• Link update by @bkmgit in #519
• Fix removal of nodes ingested by multiple downstream nodes by @jmduarte in #544
• Enable SeparableConv2d by @jmduarte in #547
• Extension API by @vloncar in #528
• change string ReuseFactor to int by @jmitrevs in #416
• Make the size of bn scale and bias what they really are by @jmitrevs in #532
• Raise runtime error when a layer is named input by @jmduarte in #482
• fix insertion before a node with multiple inputs + support additional broadcasting by @jmduarte in #551
• Pointwise conv1d/2d resource by @jmduarte in #471
• Quartus Embedding Layer by @bo3z in #548
• Fix for QActivations passed as an argument by @AdrianAlan in #553
• Don't override precision directly in the QKeras optimizer by @vloncar in #567
• Remove the in/out size from top function by @vloncar in #559
• Transpose2d, Concatenate2d, and up to 3 Clones for io_stream by @jmduarte in #402
• Remove io_serial as io_stream and add some more info in docs. by @Duchstf in #334
• Update docs for v0.6.0 by @thesps in #453
• Use correct number of args for multiple outputs by @apfusco in #487
• Fixed a few typos in the documentation by @pitmonticone in #467
• returning integer from _compute_n_samples by @JochiSt in #537
• Providing support for Alveo boards by @selwyn96 in #552
• Make layer names case sensitive in config. by @jmitrevs in #577
• Add issue and PR templates by @jmduarte in #582
• Vivado Backend GRU/LSTM support by @drankincms in #560
• Update CI template syntax by @thesps in #593
• Update flow dependencies by @vloncar in #588
• Fix parsing of ZeroPadding layers by @vloncar in #595
• remove cppname by @jmitrevs in #562
• Remove email helpline from the docs by @vloncar in #601
• Fixes for GRU/LSTM in Vivado backend by @drankincms in #598
• Remove io_serial by @vloncar in #609
• Fix test_graph by @vloncar in #611
• Override parent backend optimizer passes with derived backend passes by @thesps in #597
• Enforce function pipelining when using io_parallel with Resource strategy by @vloncar in #605
• FIFO depth optimization by @nicologhielmetti in #509
• Add tracing support for the quartus backend by @jmitrevs in #583
• Quartus streaming support for Activations, Dense & Batch Normalization by @bo3z in #557
• QConv alpha != 1 bug fix by @bo3z in #612
• Quartus Stream Embedding by @bo3z in #625
• change master to main by @jmitrevs in #602
• Edit order of the optimizers in the flow so that BramFactor is followed by @jmitrevs in #621
• Softmax LUT Optimization by @bo3z in #570
• Quartus Synthesis Flow Improvement by @bo3z in #618
• Quartus Extensions by @bo3z in #628
• Quartus GRU by @bo3z in #596
• Quartus Merge layers by @bo3z in #634
• fix nondefault project name handling by @jmitrevs in #626
• Fix parsing of logic synthesis reports by @vloncar in #639
• Fix conv1d stream implementation hls directives by @Jonathan-Shoemaker in #635
• Implementation and optimizations linked to Simple-RNN and LSTM for qu… by @nemerchiedde in #575
• Softsign optimization by @nemerchiedde in #585
• Parallel CNNs, Pooling & Image Layers for Quartus Backend by @bo3z in #561
• Quartus Streaming Softsign (PR #585 contd.) by @bo3z in #655
• Remove final reshapes even for Quartus by @jmitrevs in #661
• Unrolled CNN implementation by @vloncar in #600
• the strategy was not propagated in the pytest by @jmitrevs in #663
• Fix keras model loading issue with loading model with KerasH5 by @calad0i in #664
• append applied_flows container before filling instead of after by @jmitrevs in #641
• set version using setuptools_scm by @jmduarte in #479
• Argmax Softmax by @bo3z in #627
• Fix version extraction in Sphinx config by @vloncar in #669
• Add requested citations to README by @jmduarte in #615
• skip BatchNorm fusion when input/output is used multiple times by @jmduart...

delphinium rc1

What's Changed

• fix conv1d io_parallel resource by @jmitrevs in #403
• Speed up CI tests by @thesps in #407
• Fix GlobalPooling1D Layers by @jmduarte in #399
• Fix batched multiple inputs by @jmduarte in #414
• Fixed 'qkeras_mnist_dense' example build problem #423 by @siorpaes in #424
• Update for pyyaml 6.0 by @thesps in #435
• axi_stream_driver update by @nicologhielmetti in #420
• Reshape fixes: don't repack stream for flatten; remove final reshape by @jmduarte in #443
• Fix Conv2D with io_type = io_parallel & Strategy: Resource by @thesps in #448
• Support applying Softmax over multidimensional tensors by @vloncar in #384
• Disable some unsupported layers by @thesps in #447
• Fixes: quantized_relu & unsigned profiling part II by @thesps in #441
• GarNet and GarNetStack in config.py by @yiiyama in #344
• support ZeroPadding layers by @jmduarte in #480
• New backend development framework by @vloncar in #395
• Register ApplyAlpha layer templates by @thesps in #499
• Parsing extended by @nicologhielmetti in #501
• Remove intermediate casting in product by @jmitrevs in #490
• Add QKeras as a package dependency by @vloncar in #511
• Copy flows from config by @thesps in #510
• VivadoAccelerator backend updates by @thesps in #508
• Optimized look-up table by @nemerchiedde in #527
• Upsampling2D test case by @ChiRuiChen in #520
• Support UpSampling1D by @vloncar in #475
• RNN support (part 1) by @vloncar in #521
• Quartus Custom Matrix Multiplication & Quantization by @bo3z in #523
• Vivado-equivalent implementation of Softmax on Quartus by @bo3z in #540
• Ensure 2 bits for scale in po2 quantizers by @vloncar in #531
• Link update by @bkmgit in #519
• Fix removal of nodes ingested by multiple downstream nodes by @jmduarte in #544
• Enable SeparableConv2d by @jmduarte in #547
• Extension API by @vloncar in #528
• change string ReuseFactor to int by @jmitrevs in #416
• Make the size of bn scale and bias what they really are by @jmitrevs in #532
• Raise runtime error when a layer is named input by @jmduarte in #482
• fix insertion before a node with multiple inputs + support additional broadcasting by @jmduarte in #551
• Pointwise conv1d/2d resource by @jmduarte in #471
• Quartus Embedding Layer by @bo3z in #548
• Fix for QActivations passed as an argument by @AdrianAlan in #553
• Don't override precision directly in the QKeras optimizer by @vloncar in #567
• Remove the in/out size from top function by @vloncar in #559
• Transpose2d, Concatenate2d, and up to 3 Clones for io_stream by @jmduarte in #402
• Remove io_serial as io_stream and add some more info in docs. by @Duchstf in #334
• Update docs for v0.6.0 by @thesps in #453
• Use correct number of args for multiple outputs by @apfusco in #487
• Fixed a few typos in the documentation by @pitmonticone in #467
• returning integer from _compute_n_samples by @JochiSt in #537
• Providing support for Alveo boards by @selwyn96 in #552
• Make layer names case sensitive in config. by @jmitrevs in #577
• Add issue and PR templates by @jmduarte in #582
• Vivado Backend GRU/LSTM support by @drankincms in #560
• Update CI template syntax by @thesps in #593
• Update flow dependencies by @vloncar in #588
• Fix parsing of ZeroPadding layers by @vloncar in #595
• remove cppname by @jmitrevs in #562
• Remove email helpline from the docs by @vloncar in #601
• Fixes for GRU/LSTM in Vivado backend by @drankincms in #598
• Remove io_serial by @vloncar in #609
• Fix test_graph by @vloncar in #611
• Override parent backend optimizer passes with derived backend passes by @thesps in #597
• Enforce function pipelining when using io_parallel with Resource strategy by @vloncar in #605
• FIFO depth optimization by @nicologhielmetti in #509
• Add tracing support for the quartus backend by @jmitrevs in #583
• Quartus streaming support for Activations, Dense & Batch Normalization by @bo3z in #557
• QConv alpha != 1 bug fix by @bo3z in #612
• Quartus Stream Embedding by @bo3z in #625
• change master to main by @jmitrevs in #602
• Edit order of the optimizers in the flow so that BramFactor is followed by @jmitrevs in #621
• Softmax LUT Optimization by @bo3z in #570
• Quartus Synthesis Flow Improvement by @bo3z in #618
• Quartus Extensions by @bo3z in #628
• Quartus GRU by @bo3z in #596
• Quartus Merge layers by @bo3z in #634
• fix nondefault project name handling by @jmitrevs in #626
• Fix parsing of logic synthesis reports by @vloncar in #639
• Fix conv1d stream implementation hls directives by @Jonathan-Shoemaker in #635
• Implementation and optimizations linked to Simple-RNN and LSTM for qu… by @nemerchiedde in #575
• Softsign optimization by @nemerchiedde in #585
• Parallel CNNs, Pooling & Image Layers for Quartus Backend by @bo3z in #561
• Quartus Streaming Softsign (PR #585 contd.) by @bo3z in #655
• Remove final reshapes even for Quartus by @jmitrevs in #661
• Unrolled CNN implementation by @vloncar in #600
• the strategy was not propagated in the pytest by @jmitrevs in #663
• Fix keras model loading issue with loading model with KerasH5 by @calad0i in #664
• append applied_flows container before filling instead of after by @jmitrevs in #641
• set version using setuptools_scm by @jmduarte in #479
• Argmax Softmax by @bo3z in #627
• Fix version extraction in Sphinx config by @vloncar in #669
• Add requested citations to README by @jmduarte in #615
• skip BatchNorm fusion when input/output is used multiple times by @jmduart...

coris

What's Changed

• VivadoAccelerator backend: target pynq-z2 and zcu102 boards directly from hls4ml by @nicologhielmetti
• Updated PyTorch and ONNX converters by @Duchstf
• line_buffer Conv2D implementation for io_stream: reduced resource usage and latency by @Keb-L, @violatingcp, @vloncar
• Support QConv2DBatchnorm layer from QKeras by @nicologhielmetti
• Improved profiling plots - easier to compare original vs hls4ml converted models by @maksgraczyk
• Better derivation of data types for QKeras models by @jmduarte, @thesps
• Improved CI by @thesps
• More support for models with branches, skip connections, Merge and Concatenate layers by @jmduarte, @vloncar
• Support for Dense layers over multi-dimensional tensors by @vloncar
• Overall improvements by @vloncar, @jmduarte, @thesps, @jmitrevs & others

New Contributors

• @siorpaes made their first contribution in #424
• @jmitrevs made their first contribution in #403
• @anders-wind made their first contribution in #302
• @KOVI89alipes made their first contribution in #318
• @maksgraczyk made their first contribution in #323
• @Keb-L made their first contribution in #332
• @ConsVin made their first contribution in #307
• @nicologhielmetti made their first contribution in #298

Full Changelog: v0.5.0...v0.6.0

bartsia

What's new:

• Streaming IO layer implementations, especially of Convolutional layers, accessed through the config with IOType: io_stream. Scales CNN support to much larger models than previously possible (see arXiv:2101.05108)
• New documentation and API reference
• Further optimizations for QKeras / quantization aware training. A 'shift' operation is now used for po2 quantizers
• Allow redefinition of weights directory for standalone project compilation
• profiling for PyTorch models

Deprecated:

• IOType : io_serial is deprecated, and superceded by new IOType: io_stream

Bugfixes:

• Fix to Initiation Interval and different min/max latency for Strategy: Resource
• Fix warnings in hls4ml command line script flow
• Write yml config from Python API - for mixed API / command line flow

v0.5.0-beta

Pre-release of hls4ml version v0.5.0.

What's new:

• Streaming IO layer implementations, especially of Convolutional layers, accessed through the config with io_type: io_stream. Scales CNN support to much larger models than previously possible (see paper)
• New documentation and API reference
• Further optimizations for QKeras / quantization aware training. A 'shift' operation is now used for po2 quantizers
• Allow redefinition of weights directory for standalone project compilation