Intelligent Engine Release Notes¶
This page lists the Release Notes for Intelligent Engine, so that you can learn its evolution path and feature changes.
2024-07-31¶
v0.7.0¶
Features¶
- Added support for
Datasets
to query preheating progress after dataset creation, along with a quick debug entry. - Added support for
Training Tasks
to create both single-machine and distributed tasks withMxNet
. - Added support for
Training Tasks
to createMPI
distributed tasks. - Added support for
Training Tasks
to use a default image, standardizing the use of base images. - Added support for
Training Tasks
to configure the startup command directly with a startup script. - Added support for
Training Tasks
to specify the working directory location for run parameters. - Added support for
Inference Tasks
to display example documentation forAPI
calls in the details. - Improved the
Env Management
list to show the package managers andPython
versions available in the environment.
2024-07-10¶
v0.6.1¶
Fixes¶
- Fixed an issue where
Inference
create services using theTriton
framework lacked thevLLM
option.
2024-06-30¶
v0.6.0¶
Features¶
- Added support for creating
Code
typeNotebook
, providing a nativeVS Code
development experience. - Added support for quickly copying
Notebook
. - Added when selecting a worker cluster, display the cluster's status information, making it unselectable if it is disconnected or offline.
- Added support for using
vLLM
as the inference engine, exposing nativevLLM
capabilities when creating inference services. - Added
vLLM
supports configuringLora
inference parameters when creating inference services.
Optimization¶
- Optimized the default queue priority to
High
when creating aNotebook
.
Fixes¶
- Fixed an issue with minimum resource limits for
Tensorboard
to prevent startup failures due to insufficient resources. - Fixed an issue with the Chinese descriptions of task statuses to avoid misunderstandings caused by unclear status descriptions.
2024-05-30¶
v0.5.0¶
Features¶
- Added support for adding
Tensorboard
analysis dashboard when creating tasks withbaizectl
. - Added support for binding
Job
to custom environments created inEnvironment Management
. - Added optimizations for custom environment configuration updates and improvements to the
Python
version selector inEnvironment Management
. - Added support for viewing resource monitoring dashboards in the details of
Inference Service
. - Added support for binding
Inference Service
to custom environments created inEnvironment Management
.
Fixes¶
- Fixed an issue where
Python
version prompts permission problems in certain cases within environment management. - Fixed an issue where the inference service does not support stopping during exceptions.
2024-04-30¶
v0.4.0¶
Features¶
- Added
Notebook
now supports local SSH access, compatible with various development tools such as Pycharm, and VS Code. - Added upgrade
Notebook
image to support the built-inCLI
toolbaizectl
, for command-line task submission and management. - Added
Notebook
adds affinity scheduling policy 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 inNotebook
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 to
v0.6.2
.
Fixes¶
- Fixed an occasional sync anomaly issue with
Notebook
CRD
. - Fixed an issue where the query interface for
Notebook
affinity configuration parameters did not return.
2024-04-01¶
v0.3.0¶
Features¶
- 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
, andPaddle
. - 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
, andGit
, with support for automatic data preheating.