The next RC development starts with 2.3.0, and
the hotfixes for 2022 releases will be kept in 2.2.y.
2.1.1 -> 2.2.0
- This is NNStreamer 2.2.0 Tizen 7.0 M2 release.
- NNStreamer-Edge.
- Edge-AI (Among-Device AI) implementation is moved to nnstreamer-edge so that non-nnstreamer/gstreamer systems can connect to nnstreamer pipelines.
- NNStreamer-Edge provides inter-pipeline stream connections with various protocols transparently.
- NNStreamer-Edge does not depend on gstreamer/nnstreamer; thus, non-gstreamer systems may connect to nnstreamer/gstreamer pipelines via nnstreamer-edge.
- The "MQTT-Hybrid" protocol for high bandwidth communication w/ mqtt features included.
- ML-Service API phase 2 is completed and released via api.git
- Major features
- tensor-query-client, tensor-query-serversrc/sink use nnstreamer-edge. Protocols are handled at nnstreamer-edge and it now support aitt as one of its backends.
- Float16 (FP16) tensor stream support.
- Rank limit of tensor stream increased: 4 --> 8 (experimental. with known issues)
- Error messages, exception handling, and documentations are improved for application / pipeline writers.
- Minor features
- Added several workarounds for glitches of Qualcomm-SNPE's libraries.
- Support additional .ini file for subplugin configuration. Required by clients who want to separate permissions for controlling user-installable subplugins and system-installable core files.
- Ability to run multiple instances of unit tests in a single machine.
- Add gcc >= 11 support
- Fixed multithreading error in tensor_filter::python
- Python2 dropped. Only Python3 is supported.
- Refactored to increase SAM score (architecture quality assessment).
- Query, GRPC: added minor features requested by users.
- A lot of test cases and fixes introduced.
- Ubuntu 22.04 published.
- Python >= 3.10 support.
- Tensor-decoder::bounding-box. ssd-mobilenet v3 support
- Experimental features
- edgesrc, edgesink. stream pub/sub elements based on nnstreamer-edge
- Known issues
- Multithreading errors in tensor_decoder::python and tensor_converter::python
- FP16 in x64/x86 is not tested. (tested in armv7l/aarch64 only)
- Rank > 4 support is not activated by default. Dimension properties of GSTCAP is not fully backward compatible (to be fixed).
Signed-off-by: MyungJoo Ham <email address hidden>
This patch fixes transform transpose rank to 4.
Increasing NNS_TENSOR_RANK_LIMIT will affect transform transpose.
It should be fixed to 4 until transform transpose supports rank N.
