Promote datasets from experimental to stable

[nv-rliu]

This PR moves the datasets API from experimental to stable. Users can now do:

from cugraph.datasets import karate

G = karate.get_graph()

The promoted_experimental_warning_wrapper() has been added to the existing experimental.datasets package.

closes #3675

[rlratzel]

Thanks for working on this! Here's a partial review, I'll add more feedback later.

Some other general feedback is to add unit tests. It would be nice if the meta-data was tested/verified too (eg. the resulting graphs have the same number of vertices and edges as reported in the yaml files) as well as a test to ensure the new warning exceptions are being raised.

[nv-rliu]

Update on unit test coverage suggestions by @rlratzel

• test_dataset.py::test_node_and_edge_count creates a Graph using cugraph.datasets and checks that the number of nodes and edges in the resulting object is the same as the metadata files.
• test_dataset.py::test_is_directed creates a Graph and checks if was correctly constructed with directed edges by comparing with the metadata file.

[rlratzel]

Looking better, thanks! We should also figure out how to refactor the tests that still need the various karate derivatives, or do something else so we can stop importing from experimental.

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[acostadon]

Looks great !
Not required, but a short README on how to add a new dataset might help users.

[nv-rliu]

The changes in this PR branch have been merged into #3712