This Pull Request is for HacktoberFest 2020

Description of Change

Checklist

• Added description

What would you like to be added: As title

Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.

**Without this feature, how does current nni

Tick-Tack-Toe game is not working for exception part

Description

Else part on line 247 takes you to infinite loop on getting any char value as input for position.

Expected Behavior

Spark is really inconsistent in how it handles some values like -0.0 vs 0.0 and the various NaN values that are possible. I don't expect cuDF to be aware of any of this, but I would like the ability to work around it in some cases by treating the floating point value as if it were just a bunch of bits. To me logical_cast feels like the right place to do this, but floating point values are

https://igel.readthedocs.io/en/latest/_sources/readme.rst.txt includes a link to the assets/igel-help.gif, but that path is broken on readthedocs.

readme.rst is included as ../readme.rst in the sphinx build.
The gifs are in asses/igel-help.gif

The sphinx build needs to point to the asset directory, absolutely:

.. image:: /assets/igel-help.gif

I haven't made a patch, because I haven't

Is your feature request related to a problem? Please describe.
While porting some code from SKL to cuML, I have noticed the following:

SKL:
from sklearn.model_selection import train_test_split
cuML:
from cuml.preprocessing.model_selection import train_test_split

If I try to do from cuml.model_selection import train_test_split, the following error is displayed:
`ModuleNotFoundE

I'm sorry if I missed this functionality, but CLI version hasn't it for sure (I saw the related code only in generate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.

Of course, piping is a solution, but not for development in Jupyter Notebook, for example.

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually