Neuralogic

Additions:
- `neuralogic.initialize` now exposes more global settings
- Datasets now contains Samples, which are tuples of examples and queries
- New GINEConv module
- New GENConv module
- GCNConv now supports normalization

Changes
- Template is now subscriptable (allows set, delete, get by index)
- Default rule aggregation exposed via `Settings`
- `duplicate_groundings` are now present in `Metadata.__str__`
- Global setter for the graphviz path
- Split dataset building into two steps - groundings can now be rendered
- Alternative way to define rule bodies using `&` (e.g, `R.a <= R.b & R.c`)
- Calling `.draw()` now display the image (if `show=True` and no path has been provided)

Changes:
- The `Rule` can be imported from `neuralogic.core`
- The NeuraLogic backend has been updated
- Added `__repr__` methods for relations, metadata, rules, and templates
- Simplified accessing samples' target values (`sample.target`)
- Added a `model` parameter to the `template.draw` method to draw template with given weights

Additions:
- It is now possible to decode one-hot encoded features of edge attributes into a class-specific predicate (For Tensor Dataset)

Bug Fixes

- Fix CSV Dataset Terms Getter - CSV Dataset kept terms capitalized, resulting in changing their meaning from constants to variables.

Bug fixes

- Negation is now supported also for body literals referencing other rule's head
- Fixed serialization issues on some JVMs
- Fixed the direction of arrows in visualizations