[Doc] Unify the minimal versions required for PyTorch/TensorFlow/MXNet

[yaox12]

Description

This resolves #4179 by unifying the minimal PyTorch/TensorFlow/MXNet versions we are supporting:

• PyTorch 1.9.0+
• MXNet 1.6+
• TensorFlow 2.3.0+

python/dgl/_dataloading/pytorch/dataloader.py is legacy code so I leave it untouched.

Checklist

Please feel free to remove inapplicable items for your PR.

• The PR title starts with [$CATEGORY] (such as [NN], [Model], [Doc], [Feature]])
• Changes are complete (i.e. I finished coding on this PR)
• To the best of my knowledge, examples are either not affected by this change,
  or have been fixed to be compatible with this change
• Related issue is referred in this PR

[dgl-bot]

To trigger regression tests:

• @dgl-bot run [instance-type] [which tests] [compare-with-branch];
  For example: @dgl-bot run g4dn.4xlarge all dmlc/master or @dgl-bot run c5.9xlarge kernel,api dmlc/master

[jermainewang]

@BarclayII Could you also take a look at this update?

[yaox12]

Seems we need to upgrade TensorFlow to 2.3.0 in the CI docker images. cc @Rhett-Ying

[Rhett-Ying]

@jermainewang have we decided to add below version constraints ? If so, we need to update CI image and Jenkinsfile first so that this PR could test and pass.

PyTorch 1.9.0+
MXNet 1.6+
TensorFlow 2.3.0+

[jermainewang]

Yes, please go ahead upgrade CI image.

[dgl-bot]

Commit ID: 2d41d50

Build ID: 4

Status: ✅ CI test succeeded

Report path: link

Full logs path: link