Overview¶

ONNX is an open format to represent deep learning models. With ONNX as an intermediate representation, it is easier to move models between state-of-the-art tools and frameworks for training and inference.

The mxnet.contrib.onnx package refers to the APIs and interfaces that implement ONNX model format support for Apache MXNet.

With ONNX format support for MXNet, developers can build and train models with a variety of deep learning frameworks, and import these models into MXNet to run them for inference and training using MXNet’s highly optimized engine.

ONNX Tutorials¶

ONNX Examples¶

• Face Recognition with ArcFace
• Image Classification with MobileNet, ResNet, SqueezeNet, VGG

API Reference¶

Functions for importing ONNX models to MXNet and for checking metadata

mxnet.contrib.onnx.onnx2mx.import_model.import_model(model_file)[source]¶

Imports the ONNX model file, passed as a parameter, into MXNet symbol and parameters. Operator support and coverage - https://cwiki.apache.org/confluence/display/MXNET/MXNet-ONNX+Integration

Parameters:	model_file (str) – ONNX model file name
Returns:	sym (Symbol) – MXNet symbol object arg_params (dict of str to NDArray) – Dict of converted parameters stored in mxnet.ndarray.NDArray format aux_params (dict of str to NDArray) – Dict of converted parameters stored in mxnet.ndarray.NDArray format

Notes

This method is available when you import mxnet.contrib.onnx

mxnet.contrib.onnx.onnx2mx.import_model.get_model_metadata(model_file)[source]¶

Returns the name and shape information of input and output tensors of the given ONNX model file.

Notes

This method is available when you import mxnet.contrib.onnx

Parameters:	model_file (str) – ONNX model file name
Returns:	model_metadata – A dictionary object mapping various metadata to its corresponding value. The dictionary will have the following template: 'input_tensor_data' : list of tuples representing the shape of the input paramters 'output_tensor_data' : list of tuples representing the shape of the output of the model
Return type:	dict

Import ONNX model to gluon interface

mxnet.contrib.onnx.onnx2mx.import_to_gluon.import_to_gluon(model_file, ctx)[source]¶

Imports the ONNX model files, passed as a parameter, into Gluon SymbolBlock object.

Parameters:	model_file (str) – ONNX model file name ctx (Context or list of Context) – Loads the model into one or many context(s).
Returns:	sym_block – A SymbolBlock object representing the given model file.
Return type:	SymbolBlock

Notes

This method is available when you import mxnet.contrib.onnx

Exports an MXNet model to the ONNX model format

mxnet.contrib.onnx.mx2onnx.export_model.export_model(sym, params, input_shape, input_type=, onnx_file_path=u'model.onnx', verbose=False)[source]¶

Exports the MXNet model file, passed as a parameter, into ONNX model. Accepts both symbol,parameter objects as well as json and params filepaths as input. Operator support and coverage - https://cwiki.apache.org/confluence/display/MXNET/MXNet-ONNX+Integration

Parameters:	sym (str or symbol object) – Path to the json file or Symbol object params (str or symbol object) – Path to the params file or params dictionary. (Including both arg_params and aux_params) input_shape (List of tuple) – Input shape of the model e.g [(1,3,224,224)] input_type (data type) – Input data type e.g. np.float32 onnx_file_path (str) – Path where to save the generated onnx file verbose (Boolean) – If true will print logs of the model conversion
Returns:	onnx_file_path – Onnx file path
Return type:	str

Notes

This method is available when you import mxnet.contrib.onnx