Generate External Initializers with OML4Py

You can generate ONNX models with external initializers and their metadata using OML4Py.

You can import those ONNX models into your database. OML4Py also creates a metadata file that describes each initializer, making it easy for the ONNX runtime or Oracle AI Database to work with your model. See Support For Large ONNX Format Model Support on using OML4Py external initializers.

OML4Py enables importing or exporting models with external initializers using the following structure:

• A .onnx file that holds the ONNX model referencing external data.
• One or more .dat files containing raw tensor data values.
• A single .json file describing the metadata of the external initializers. This JSON file includes the name, shape, offset, type, and size for each initializer.

See Also:

• See IMPORT_ONNX_MODEL Procedure to import such models.

• View model details by querying DM$VX<model_name> and DM$VG<model_name>. See Model Detail Views for ONNX Models for more details.