[Sparse] Add a graphSAGE example

[xiangyuzhi]

Description

A sparse graphSAGE example.
Run example:

$ python examples/sparse/graphsage.py
Training in gpu mode.
Loading data
Training...
[W TensorAdvancedIndexing.cpp:1615] Warning: scatter_reduce() is in beta and the API may change at any time. (function operator())
Epoch 00000 | Loss 2.0963 | Accuracy 0.7756 
Epoch 00001 | Loss 0.8108 | Accuracy 0.8443 
Epoch 00002 | Loss 0.6264 | Accuracy 0.8593 
Epoch 00003 | Loss 0.5662 | Accuracy 0.8675 
Epoch 00004 | Loss 0.5311 | Accuracy 0.8721 
Epoch 00005 | Loss 0.5047 | Accuracy 0.8744 
Epoch 00006 | Loss 0.4846 | Accuracy 0.8759 
Epoch 00007 | Loss 0.4766 | Accuracy 0.8756 
Epoch 00008 | Loss 0.4674 | Accuracy 0.8796 
Epoch 00009 | Loss 0.4528 | Accuracy 0.8799 
Testing...
Test accuracy 0.7216

Checklist

Please feel free to remove inapplicable items for your PR.

• The PR title starts with [$CATEGORY] (such as [NN], [Model], [Doc], [Feature]])
• I've leverage the tools to beautify the python and c++ code.
• The PR is complete and small, read the Google eng practice (CL equals to PR) to understand more about small PR. In DGL, we consider PRs with less than 200 lines of core code change are small (example, test and documentation could be exempted).
• All changes have test coverage
• Code is well-documented
• 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
• If the PR is for a new model/paper, I've updated the example index here.

Changes

[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

[dgl-bot]

Commit ID: d426263f8e759366aab80b486033a939d10ad04e

Build ID: 1

Status: ✅ CI test succeeded.

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[dgl-bot]

Commit ID: c930fd0e02292d7c4e9edb856b2e8b2d4c2637f7

Build ID: 2

Status: ❌ CI test failed in Stage [Torch GPU Unit test].

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[xiangyuzhi]

@dgl-bot

[dgl-bot]

Commit ID: 77d8be953322cfb7ed14bb28bbbdcd80d620d213

Build ID: 3

Status: ✅ CI test succeeded.

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[czkkkkkk]

This should serve as a sampling-based training example, illustrating how sparse APIs support sampling. Let's have a chat tomorrow to discuss how to implement these changes.

[dgl-bot]

Commit ID: 7f2f74b623954199831445b81b79704bebe5f836

Build ID: 4

Status: ⚪️ CI test cancelled due to overrun.

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Commit ID: f4c1cf9a2263547f580188ffc32023b64a92dcb9

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Commit ID: e5afbe9b22165ea84a36d3c88a905c2b4dd711b6

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[dgl-bot]

Commit ID: 64412c2bb24a3941ac45aaaac5b16a0273a943bb

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[czkkkkkk]

LGTM

[dgl-bot]

Commit ID: a9ef2eed3c011da9ff2b6698e44ecba6a7764ec4

Build ID: 8

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[dgl-bot]

Commit ID: bfaf79a50a6480d0243404c0e13eab9725e908f8

Build ID: 9

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[dgl-bot]

Commit ID: 14402b3d18c7fa3d54829c08730cc67d4769bc45

Build ID: 10

Status: ✅ CI test succeeded.

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[czkkkkkk]

LGTM