Bigdl

Highlights

* Continue RNN optimization. We support both LSTM and GRU integration with MKL-DNN which acheives ~3x performance

* ONNX support. We support loading third party framework models via ONNX

* Richer data preprocssing support and segmentation inference pipeline support


Details
* [New Feature] Full MaskRCNN model support with data processing
* [New Feature] Support variable-size Resize
* [New Feature] Support batch input for region proposal
* [New Feature] Support samples of different size in one minibatch
* [New Feature] MAP validation method implementation
* [New Feature] ROILabel enhancement to support both object detection and segmentation
* [New Feature] Grey image support for segmentation
* [New Feature] Add TopBlocks support for Feature Pyramid Networks (FPN)
* [New Feature] GRU integration with MKL-DNN support
* [New Feature] MaskHead support for MaskRCNN
* [New Feature] BoxHead support for MaskRCNN
* [New Feature] RegionalProposal support for MaskRCNN
* [New Feature] Shape operation support for ONNX
* [New Feature] Gemm operation support for ONNX
* [New Feature] Gather operation support for ONNX
* [New Feature] AveragePool operation support for ONNX
* [New Feature] BatchNormalization operation support for ONNX
* [New Feature] Concat operation support for ONNX
* [New Feature] Conv operation support for ONNX
* [New Feature] MaxPool operation support for ONNX
* [New Feature] Reshape operation support for ONNX
* [New Feature] Relu operation support for ONNX
* [New Feature] SoftMax operation support for ONNX
* [New Feature] Sum operation support for ONNX
* [New Feature] Squeeze operation support for ONNX
* [New Feature] Const operation support for ONNX
* [New Feature] ONNX model loader implementation
* [New Feature] RioAlign layer support
* [Enhancement] Align batch normalization layer between mklblas and mkl-dnn
* [Enhancement] Python API enhancement to support nested list input
* [Enhancement] Multi-model training/inference support with MKL-DNN
* [Enhancement] BatchNormalization fusion with Scale
* [Enhancement] SoftMax companion object support no argument initialization
* [Enhancement] Python support for training with MKL-DNN
* [Enhancement] Docs enhancement
* [Bug Fix] Fix model version comparison
* [Bug Fix] Fix graph backward bug for ParallelTable
* [Bug Fix] Fix memory leak for training with MKL-DNN
* [Bug Fix] Fix performance caused by denormal values during training
* [Bug Fix] Fix SoftMax segment fault issue under MKL-DNN
* [Bug Fix] Fix TimeDistributedCriterion python API inconsistent with Scala

Highlights

* Continue VNNI acceleration support, we add optimization for more CNN models including object detection models, enhance model scales generation support for VNNI.

* Add attention based model support, we add Transformer implementation for both lanuage model and translation model.

* RNN optimization, We support LSTM integration with MKL-DNN which acheives ~3x performance speedup.


Details
* [New Feature] Add attention layer support
* [New Feature] Add FeedForwardNetwork layer support
* [New Feature] Add ExpandSize layer support
* [New Feature] Add TableOperation layer to support table calculation with different input sizes
* [New Feature] Add LayerNormalizaiton layer support
* [New Feature] Add Transformer support for both language and translation models
* [New Feature] Add beam search support in Transformer model
* [New Feature] Add Layer-wise adaptve rate scaling optim method
* [New Feature] Add LSTM integration with MKL-DNN support
* [New Feature] Add dilated convolution integration with MKL-DNN support
* [New Feature] Add parameter process for LarsSGD optim method
* [New Feature] Support Affinity binding option with mkl-dnn
* [Enhancement] Document enhancement for configuration and build
* [Enhancement] Reflection enhancement to get default values for constructor parameters
* [Enhhancement] User one AllReducemParameter for multi-optim method training
* [Enhancement] CAddTable layer enhancement to support input expansion along specific dimension
* [Enhancement] Resnet-50 preprocessing pipeline enhancement to replace RandomCropper with CenterCropper
* [Enhancement] Calculate model scales for arbitrary mask
* [Enhancment] Enable global average pooling
* [Enhancement] Check input shape and underlying MKL-DNN layout consistency
* [Enhancement] Threadpool enhancement to throw proper exception at executor runtime
* [Enhancement] Support mkl-dnn format conversion from ntc to tnc
* [Bug Fix] Fix backward graph generation topology ordering issue
* [Bug Fix] Fix MemoryData hash code calculation
* [Bug Fix] Fix log output for BCECriterion
* [Bug Fix] Fix setting mask for container quantization
* [Bug Fix] Fix validation accuracy issue when multi-executor running with the same worker
* [Bug Fix] Fix INT8 layer fusion between conlution with multi-group masks and BatchNormalization
* [Bug Fix] Fix JoinTable scales generation issue
* [Bug Fix] Fix CMul forward issue with special input format
* [Bug Fix] Fix weights change issue after model fusion issue
* [Bug Fix] Fix SpatinalConvolution primitives initializaiton issue