1.2-RC3

This is the third release candidate for RedisAI v1.2!

Headlines:

#482 DAG performance enhancement: Auto-batching support for MODELRUN commands inside a DAG Added DAG general timeout.
#489 Execute Redis commands in TorchScript. This capability enables, but not limited, to convert data residing in Redis (or modules) data structures into tensors to be fed to the model as well as store script results in Redis data structures. Scripts can be run in DAG's.
#511, #537, #547, #556 Allow async model, script and DAG run via low-level API. This capability will allow other modules to call RedisAI. For example a module that hold time series data, can call RedisAI directly for anomaly detection.
#723 #682 #680 - New API commands MODELSTORE MODELEXECUTE SCRIPTEXECUTE DAGEXECUTE replacing and deprecating MODELSET MODELRUN SCRIPTRUN DAGRUN for better enterprise cluster support. Note: SCRIPTEXECUTE command structure will be changed in the following release candidates, as well as new command SCRIPTSTORE will be introduced.

Details:

Minor enhancements:

#566 TensorFlow 2.4, Pytorch 1.7, ONNXRuntime 1.6.
#499 Allow setting number of inter/intra op threads in Torch backend.
#529 Expose model definitions for inputs and outputs in MODELGET command.
#530 Expose Redis/RedisAI main thread cpu usage.
#540 Reuse memory in TENSORSET command.
#580 Expose backend version on AI.INFO
#581 Cache tensor length.

Bugfixes:

#488 Handle short reads during RDB load.
#538 Handle binary strings as tensor names.
#462, #553 Handle memory leaks.
#558 Erroneous replies for invalid MODELGET commands.
#748 Model RDB encoding missing properties
#754 AOF-Rewrite logic

Notes:
This is not the GA version of 1.2. The version inside Redis will be 10203 or 1.2.3 in semantic versioning. Since the version of a module in Redis is numeric, we could not add an RC3 flag.