SINGA is a distributed deep learning library.
This release includes following changes
Tensor core:
Add new tensor operators into the autograd module, including CosSim, DepthToSpace, Embedding, Erf, Expand, Floor, Pad, Round, Rounde, SpaceToDepth, UpSample, Where. The corresponding ONNX operators are thus supported by SINGA.
Add Embedding and Gemm into the layer module.
Add SGD operators to opt module, including RMSProp, Adam, and AdaGrad.
Extend the sonnx module to support DenseNet121, ShuffleNetv1, ShuffleNetv2, SqueezeNet, VGG19, GPT2, and RoBERTa.
Reconstruct sonnx to
Add one example that trains a BiLSTM model over the InsuranceQA data.
Replace the Travis CI with Github workflow. Add quality and coverage management.
Add compiling and packaging scripts to creat wheel packages for distribution.
Fix bugs