v0.3.0

Added

• Static analysis job (golint and gocyclo) to Go GitHub workflow.
• You can set a limit for concurrent heavyweight Graph computations (e.g. forward and backward steps) - see ml.ag.ConcurrentComputations() (GraphOption) and ml.ag.Graph.ConcurrentComputations(). If no option is specified, by default the limit is set to runtime.NumCPU().
• You can set a limit for concurrent heavyweight computations of ml.optimizers.gd.GradientDescent (e.g. params update step).
• New package utils.processingqueue.
• mat32 package, which operates on float32 data type.
• It's possible to switch between float32 and float64 as default floating-point data type, using the script change-float-type.sh
• Go GitHub workflow has been adapted to run tests using both float32 and float64 as main floating-point data type.
• This CHANGELOG file.
• Pull and convert Hugging Face models automatically if not found locally when starting BERT or BART server.
• Move content from GitHub Wiki to README in related package folders.

Changed

• ml.ag.ConcurrentComputations (GraphOption) expects the maximum number of concurrent computations handled by heavyweight Graph operations (e.g. forward and backward steps).
• ml.nn.linear.Model and ml.nn.convolution.Model read the concurrent computations limit set on the model's Graph, thus SetConcurrentComputations() methods have been removed.
• mat has been renamed to mat64 and some functions have been renamed.
• The whole project now works with float32 floating-point data type by default, by using the package mat32.
• When imported, the new package mat32 is always aliased as mat. Then, explicit usages of float64 type have been replaced with mat.Float. Moreover, bitsize-specific functions have been made more generic (i.e. operating with mat.Float type) or split into separate implementation, in mat32 and mat64. In this way, switching the whole project between float32 and float64 is just a matter of changing all imports, from mat32 to mat64, or vice-versa (see also the new file change-float-type.sh).
• Update internal links to pre-trained NER models to float32 versions.
• nlp.sequencelabeler.Convert() now loads and converts original Flair models, instead of pre-processed dumps.
• Change command line arguments to make them more consistent; please refer to the help messages of each command.
• Update Dockerfile using a new base building image and adding bart server.

Fixed

• Added dedicated package names to different protocol buffers definition files to avoid name conflicts.