The Apache SINGA (incubating) team is pleased to announce the release of SINGA 1.1.0.
SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. The release is available at: http://singa.apache.org/en/downloads.html Features implemented in this release include, - Create Docker images (CPU and GPU versions) - Create Amazon AMI for SINGA (CPU version) - Integrate with Jenkins for automatically generating Wheel and Debian packages (for installation), and updating the website. - Enhance the FeedFowardNet, e.g., multiple inputs and verbose mode for debugging - Add Concat and Slice layers - Extend CrossEntropyLoss to accept instance with multiple labels - Add image_tool.py with image augmentation methods - Support model loading and saving via the Snapshot API - Compile SINGA source on Windows - Compile mandatory dependent libraries together with SINGA code - Enable Java binding (basic) for SINGA - Add version ID in checkpointing files - Add Rafiki toolkit for providing RESTFul APIs - Add examples pretrained from Caffe, including GoogleNet See the release notes for more details: http://singa.apache.org/en/releases/RELEASE_NOTES_1.1.0.html We look forward to hearing your feedbacks, suggestions, and contributions to the project (http://singa.apache.org/). Regards, The Apache SINGA (incubating) team ===== *Disclaimer* Apache SINGA is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the name of Apache Incubator PMC. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.