[Feature] Add Dropout to MLP module

[BY571]

Description

Adds the option to use dropout in the MLP layer module and changes the order when normalization classes are applied.

Motivation and Context

The option to add dropout to the MLP module wasn't there yet. I also changed the order of when normalization classes are applied. It is now done directly after the layer and before the activation function as done in the batch norm paper.

These changes open up the opportunity to create DroQ algorithm which is an improvement over REDQ and applies Dropout + LayerNorm in the Critic networks which makes it possible to have a high update-to-data ratio without the need of big ensemble sizes. Thus, DroQ is sample efficient as REDQ and computationally efficient as SAC which makes it very interesting for application in the real world e.g. robots.

• I have raised an issue to propose this change (required for new features and bug fixes)

Types of changes

What types of changes does your code introduce? Remove all that do not apply:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds core functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation (update in the documentation)
• Example (update in the folder of examples)

Checklist

Go over all the following points, and put an x in all the boxes that apply.
If you are unsure about any of these, don't hesitate to ask. We are here to help!

• I have read the CONTRIBUTION guide (required)
• My change requires a change to the documentation.
• I have updated the tests accordingly (required for a bug fix or a new feature).
• I have updated the documentation accordingly.

[vmoens]

LGTM