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BigDL v0.10.0 Release Notes

Release Date: 2019-11-05 // about 5 years ago

  • 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

Previous changes from v0.9.0

  • 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
    • 0️⃣ [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