v6.2.0: Improve API and introduce overloaded operators

✨ Major features and improvements

• NEW: Model now has define_operators() classmethod to overload operators for a given block.
• Add chain(), clone() and concatenate() functions for use with overloaded operators.
• Add describe module which provides class decorators for defining new layers.
• Allow layers to calculate input and output sizes based on training data.

Together, these features allow very concise model definitions:

with Model.define_operators({'**': clone, '>>': chain}):
    model = BatchNorm(ReLu(width)) ** depth >> Softmax()

⚠️ Backwards incompatibilities

• Major revisions to previously undocumented neural network APIs (see above).

📋 Tests

• Reorganise and improve tests for neural network functions.
• Reach 100% coverage over the current neural network classes.