SINGA is a distributed deep learning library.
This release includes following changes:
- Add one CNN example for the BloodMnist dataset, a sub set of MedMNIST.
- Add one example for the medical image analysis.
Enhance distributed training
- Add key information printing, e.g., throughput and communication time, for distributed training.
- Optimize printing and logging modules for faster distributed training.
Enhance example code
- Add more datasets and model implementations for the cifar_distributed_cnn example.
- Update the running script for the cifar_distributed_cnn example to include more models.
- Update the dataset path for the largedataset_cnn example for more flexibility.
- Add more model implementations for the largedataset_cnn example.
Enhance the webpage
- Reconstruct the singa webpage to include project features.
- Update the Git web site by deploying it via .asf.yaml.
- Update the Chinese and Vietnamese documentations.
Debug and add assertions for input tensor data types in the opt.py.
Change pointer type to void for generalizing data types.
- Fix the python test error due to operations not implemented for some data types.
- Fix the model of pad from bytes to str.