Intelligent Engine Release Notes¶

This page lists the Release Notes for Intelligent Engine, so that you can learn its evolution path and feature changes.

2024-05-30¶

Added Support for adding Tensorboard analysis dashboard when creating tasks with baizectl.
Added Support for binding Job to custom environments created in Environment Management.
Added Optimizations for custom environment configuration updates and improvements to the Python version selector in Environment Management.
Added Support for viewing resource monitoring dashboards in the details of Inference Service.
Added Support for binding Inference Service to custom environments created in Environment Management.

Fix the issue where Python version prompts permission problems in certain cases within environment management.
Fix the issue where the inference service does not support stopping during exceptions.

Added Notebook now supports local SSH access, compatible with various development tools such as Pycharm, VS Code, etc.
Added Upgrade Notebook image to support the built-in CLI tool baizectl, for command-line task submission and management.
Added Notebook adds affinity scheduling strategy configuration.
Added Distributed training tasks can now configure SHM size through the UI.
Added One-click restart function for training tasks.
Added Model training tasks support custom cluster scheduler specification.
Added Training task analysis tool Tensorboard support, can be launched with one click in Notebook and training tasks.
Added When editing queue quotas, hints are provided for the shared resource configuration of the current workspace.
Added Upgrade and adapt Kueue version v0.6.2.

Fixed Occasional sync anomaly issue with Notebook CRD.
Fixed The query interface for Notebook affinity configuration parameters did not return.

Added the Notebooks module, supporting development tools like Jupyter Notebook.
Added the Job Center module, supporting the training of jobs with various mainstream development frameworks such as Pytorch, Tensorflow, and Paddle.
Added the Model Inference module, supporting rapid deployment of Model Serving, compatible with any model algorithm and large language models.
Added the Data Management module, supporting the integration of mainstream data sources such as S3, NFS, HTTP, and Git, with support for automatic data preheating.