Context pred GNN Modular

[tonydavis629]

Description

Implements the context prediction task for GNNModular from Strategies for Pretraining Graph Neural Networks by Hu et al 2020.

Context prediction is the task of predicting the surrounding nodes and edges of a chosen root node. Empirical results show better performance over masking nodes or edges.

Type of change

Please check the option that is related to your PR.

• [] Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • In this case, we recommend to discuss your modification on GitHub issues before creating the PR
• Documentations (modification for documents)

Checklist

• My code follows the style guidelines of this project
• Run yapf -i <modified file> and check no errors (yapf version must be 0.32.0)
• Run mypy -p deepchem and check no errors
• Run flake8 <modified file> --count and check no errors
• Run python -m doctest <modified file> and check no errors
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• New unit tests pass locally with my changes
• I have checked my code and corrected any misspellings

[rbharath]

Let's break out the graphdata changes into their own smaller PR for simplicity

[rbharath]

LGTM