[MXNET-352] Document behavior of mx.initializer.Constant

[ThomasDelteil]

Description

As I was looking for a way to initialize the value of my weights to a given specific value, I couldn't find any straightforward way to do that without hacking into the parameters and setting the value directly.
Turns out you can use the mx.initializer.Constant, even though the documentation stated that it can only accept scalar. If you give a NDArray of the right shape, you can initialize your weights using the Constant initializer, which is much cleaner than setting the data directly since you don't have to play around the names of the layers and parameters.

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

• The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant JIRA issue created (except PRs with tiny changes)
• Changes are complete (i.e. I finished coding on this PR)
• Code is well-documented:
• For user-facing API changes, API doc string has been updated.
• For new C++ functions in header files, their functionalities and arguments are documented.
• For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
• Check the API doc at http:https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
• To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

[piiswrong]

Gluon specific tutorial shouldn't be put here. In gluon it's more convenient to use set_data.

[ThomasDelteil]

There are several module API specific examples in this file, I can switch the example to a module one if you prefer.
However I have to say that I disagree that using set_data is more convenient. My opinion is that for a new user, the first place to go when wanting to initialize the weights of a layer to a specific value would be the weight_initializer parameter, rather than calling layer.collect_params()['dense0_weight'].set_data()