Update ONNX API docs references

docs/api/python/contrib/onnx.md

@@ -22,18 +22,17 @@ This document describes all the ONNX-MXNet APIs.
 .. autosummary::
     :nosignatures:
 
-    mxnet.contrib.onnx.import_model
-    mxnet.contrib.onnx.get_model_metadata
-    mxnet.contrib.onnx.import_to_gluon
-    mxnet.contrib.onnx.export_model
+    mxnet.contrib.onnx.onnx2mx.import_model
+    mxnet.contrib.onnx.onnx2mx.import_to_gluon
+    mxnet.contrib.onnx.mx2onnx.export_model
 ```
 
 ## ONNX Tutorials
 
 ```eval_rst
 .. toctree::
    :maxdepth: 1
-   
+
    /tutorials/onnx/super_resolution.md
    /tutorials/onnx/inference_on_onnx_model.md
    /tutorials/onnx/fine_tuning_gluon.md
@@ -42,19 +41,20 @@ This document describes all the ONNX-MXNet APIs.
 ## ONNX Examples
 
 * Face Recognition with [ArcFace](https://github.com/onnx/models/tree/master/models/face_recognition/ArcFace)
-* Image Classification with [MobileNet](https://github.com/onnx/models/tree/master/models/image_classification/mobilenet), [ResNet](https://github.com/onnx/models/tree/master/models/image_classification/resnet), [SqueezeNet](https://github.com/onnx/models/tree/master/models/image_classification/squeezenet), [VGG](https://github.com/onnx/models/tree/master/models/image_classification/vgg) 
+* Image Classification with [MobileNet](https://github.com/onnx/models/tree/master/models/image_classification/mobilenet), [ResNet](https://github.com/onnx/models/tree/master/models/image_classification/resnet), [SqueezeNet](https://github.com/onnx/models/tree/master/models/image_classification/squeezenet), [VGG](https://github.com/onnx/models/tree/master/models/image_classification/vgg)
 
 ## API Reference
 
 <script type="text/javascript" src='../../../_static/js/auto_module_index.js'></script>
 
 ```eval_rst
 
-.. automodule:: mxnet.contrib.onnx.import_model
-.. automodule:: mxnet.contrib.onnx.get_model_metadata
-.. automodule:: mxnet.contrib.onnx.import_to_gluon
-.. automodule:: mxnet.contrib.onnx.export_model
-
+.. automodule:: mxnet.contrib.onnx.onnx2mx.import_model
+    :members: import_model, get_model_metadata
+.. automodule:: mxnet.contrib.onnx.onnx2mx.import_to_gluon
+    :members: import_to_gluon
+.. automodule:: mxnet.contrib.onnx.mx2onnx.export_model
+    :members: export_model
 ```
 
 <script>auto_index("api-reference");</script>

python/mxnet/contrib/onnx/mx2onnx/export_model.py

@@ -18,7 +18,7 @@
 # coding: utf-8
 #pylint: disable-msg=too-many-arguments
 
-"""export function"""
+"""Exports an MXNet model to the ONNX model format"""
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function

python/mxnet/contrib/onnx/onnx2mx/import_model.py

@@ -16,7 +16,7 @@
 # under the License.
 
 # coding: utf-8
-"""import function"""
+"""Functions for importing ONNX models to MXNet and for checking metadata"""
 # pylint: disable=no-member
 
 from .import_onnx import GraphProto
@@ -72,6 +72,7 @@ def get_model_metadata(model_file):
             'output_tensor_data' : <list of tuples representing the shape of the output
                                     of the model>
         }
+
     """
     graph = GraphProto()
     try: