Added a tutorial for serving ONNX model with MXNet Model Server

[lupesko]

An example showing how to take a pre-trained ONNX model (Squeezenet) and serve it for inference with MXNet Model Server.

[CLAassistant]

All committers have signed the CLA.

[lupesko]

@jspisak @dzhulgakov please take a look.

[jspisak]

Hi Hagay, thanks for putting this together. I think this is a really good tutorial but a few things would make it even better:

1. I would suggest using Netron or something else to visualize the onnx model. the .json isnt that pretty.
2. Maybe suppress some of the synset? right now it is trying to render all 1000 category sets and i actually can't see the end of the tutorial because of this. Maybe just render the first 20 or 30?

Once you fix the synset issue I can then take a look at the rest of the tutorial.

[lupesko]

Thanks for reviewing and suggesting improvements @jspisak , addressed your comments:

• Removed the network print altogether, the important part there was to check the validity
• Updated the synset print to only show top 10 lines

[jspisak]

@lupesko - overall looks fine (although I havent tried it myself). is there a reason not to use Netron or some other lib to do a quick visualization of the net? If you dont want to use Netron, there is the one that James Reed wrote here

I can merge if you don't want to add this.

[lupesko]

@jspisak let's merge for now. I can look into other visualization options later.
I like Netron, but it still does not have Jupyter notebook support (see this issue)

[jspisak]

Got it, merging.. :)