SINGA is a general distributed deep learning platform for training big deep learning models over large datasets.
This release includes following features:
- [SINGA-434] Support tensor broadcasting
- [SINGA-370] Improvement to tensor reshape and various misc. changes related to SINGA-341 and 351
- [SINGA-333] Add support for Open Neural Network Exchange (ONNX) format
- [SINGA-385] Add new python module for optimizers
- [SINGA-394] Improve the CPP operations via Intel MKL DNN lib
- [SINGA-425] Add 3 operators , Abs(), Exp() and leakyrelu(), for Autograd
- [SINGA-410] Add two function, set_params() and get_params(), for Autograd Layer class
- [SINGA-383] Add Separable Convolution for autograd
- [SINGA-388] Develop some RNN layers by calling tiny operations like matmul, addbias.
- [SINGA-382] Implement concat operation for autograd
- [SINGA-378] Implement maxpooling operation and its related functions for autograd
- [SINGA-379] Implement batchnorm operation and its related functions for autograd
Utility functions and CI
- [SINGA-432] Update depdent lib versions in conda-build config
- [SINGA-429] Update docker images for latest cuda and cudnn
- [SINGA-428] Move Docker images under Apache user name
Documentation and usability
- [SINGA-395] Add documentation for autograd APIs
- [SINGA-344] Add a GAN example
- [SINGA-390] Update installation.md
- [SINGA-384] Implement ResNet using autograd API
- [SINGA-352] Complete SINGA documentation in Chinese version
- Bugs fixed
- [SINGA-431] Unit Test failed - Tensor Transpose
- [SINGA-422] ModuleNotFoundError: No module named "_singa_wrap"
- [SINGA-418] Unsupportive type 'long' in python3.
- [SINGA-409] Basic
singa-cpuimport throws error
- [SINGA-408] Unsupportive function definition in python3
- [SINGA-380] Fix bugs from Reshape