You can not select more than 25 topics
Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.
2.0 kB
2.0 kB
MindSpore Serving 1.2.0
MindSpore Serving 1.2.0 Release Notes
Major Features and Improvements
- [STABLE] Support distributed inference, it needs to cooperate with distributed training to export distributed models for super-large-scale neural network parameters(Ascend 910).
- [STABLE] Support GPU platform, Serving worker nodes can be deployer on Nvidia GPU, Ascend 310 and Ascend 910.
- This release is based on MindSpore version 1.2.0
- Support Python 3.8 and 3.9.
API Change
API Incompatible Change
Python API
Support deployment of distributed model, refer to distributed inference tutorial for related API.
Deprecations
Python API
Bug Fixes
Contributors
Thanks goes to these wonderful people:
chenweifeng, qinzheng, xujincai, xuyongfei, zhangyinxia, zhoufeng.
Contributions of any kind are welcome!
MindSpore Serving 1.1.1 Release Notes
Major Features and Improvements
- Adapts new C++ inference interface for MindSpore version 1.1.1.
Bug fixes
- [BUGFIX] Fix bug in transforming result of type int16 in python Client.
- [BUGFIX] Fix bytes type misidentified as str type after python preprocess and postprocess.
- [BUGFIX] Fix bug releasing C++ tensor data when it's wrapped as numpy object sometimes.
- [BUGFIX] Update RuntimeError to warning log when check Ascend environment failed.
MindSpore Serving 1.1.0 Release Notes
Major Features and Improvements
- [STABLE] Support gRPC and RESTful API.
- [STABLE] Support simple Python API for Client and Server.
- [STABLE] Support Model configuration，User can customize preprocessing & postprocessing for model.
- [STABLE] Support multiple models，Multiple models can run simultaneously.
- [STABLE] Support Model batching，Multiple instances will be split and combined to meet the batch size requirements of the model.
- This release is based on MindSpore version 1.1.0