Accelerated Data Science 2.6.8 and 2.6.9 are released

The following changes were made in ADS 2.6.8 and ADS 2.6.7.

2.6.8

• Fixed a bug in ads.dataset.helper to support Python 3.8 and Python 3.9.

2.6.7

• Fixed a bug in PyTorchModel. The score.py failed when torch.Tensor was used as input data.
• Fixed a bug in ads opctl conda publish command.
• Added support for flexible shapes for Data Flow Jobs.
• Loading a model from Model Catalog (GenericModel.from_model_catalog()) and Model Deployment (GenericModel.from_model_deployment()) no longer requires a model file name.
• Switched from using cx_Oracle interface to the oracledb driver to connect to Oracle Databases.
• Added support for image attribute for the PyTorchModel.predict() and TensorFlowModel.predict() methods. Images can now be directly passed to the model Deployment predict.

The following APIs are deprecated:

• OracleAutoMLProvider

For more information, see Data Science, ADS SDK, and ocifs SDK. Take a look at our Data Science blog.