[GitHub] [singa] dcslin edited a comment on issue #784: Preparation for V3.1 release

[GitBox <gi...@apache.org>]

dcslin edited a comment on issue #784:
URL: https://github.com/apache/singa/issues/784#issuecomment-698093681


   * BiLSTM model on [InsuranceQA](https://github.com/shuzi/insuranceQA) example training script. The baseline model is inspired by Tan, Ming, et al. "Lstm-based deep learning models for non-factoid answer selection." arXiv preprint arXiv:1511.04108 (2015).
   
   * Tensor Refactoring and Enhancement
     - Tensor transformation (reshape, transpose) supports up to 6 dimensions.
     - Implemented traverse_unary_transform in Cuda backend, which is similar to CPP backend one.
     - Added tensor operation erf, rounde (round even).
     - Fix Tensor operation Mult on Broadcasting use cases.
     - Gaussian function on Tensor now can run on Tensor with odd size.
   
   * autograd
     - Added some sanity check on autograd input to prevent fatal error caused by unexpected input shape.
     - Updated a testing helper function gradients() in autograd to lookup param gradient by param python object id for testing purpose.


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