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To implement the import/export functionality in MXNet, I propose to expose a MXNet python module to do the model conversion:

• “serde”(serialization/deserialization - name taken from Apache Hive project) which can be called as (mx.serde.import/ mx.serde.export)
• OR It can also go under contrib. MXNet contrib is used to add experimental features which can be later moved outside. This can qualify as an experimental feature as there is a gap in operator implementation. (See Appendix)

 mx.contrib.serde.import/ mx.contrib.serde.export

This wrapper serialization/deserialization module should have following methods supporting different formats:

Import model into mxnet.

sym, params = mx.serde.import(input_file, in_format=‘onnx’, out_format=’gluon’)

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• sym : model definition
• module : mxnet module object
• gluon_model : model definition (HybridBlock)
• params : weights
• format : onnx, coreml
• filename_prefix: a filename prefix to be used to model save files. E.g., for onnx, a binary protobuf will be written to output file with “.onnx” extension.

In addition to this core format conversion module(`serde`), I think implementing a wrapper according to the different namespace will be more user friendly.

For example,

•  Gluon

mx.gluon.import_from(input_file)

mx.gluon.export_to(format=’onnx’, filename_prefix=”model_name”)

If any pre-processing/post-processing logic is required for gluon specific models, it can go under this gluon wrapper. These functions will internally call `serde` module APIs.

•  For Symbolic interface

sym, params = mx.mod.Module.import_from(input_file, in_format=‘onnx’)

mx.mod.Module.export_to(format=‘onnx’, filename_prefix=”model_name”)

This function will directly save the file called “model_name.onnx” on disk.

Implementation Implementation approaches

There are two approaches which can be taken to import/export onnx model.

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