feat: add abstractify helper function to core.operator module

[andrijapau]

Context:

We wish to have a helper function that can "abstractify" various types of data. Specfically, this is useful for abstractifying operators for integration with graph decomposition.

Description of the Change:

This PR,

• add abstractify dispatcher function
• registers various types for the abstractify function

from pennylane.core.operator import Operator2
from pennylane.core.operator.utils import abstractify

class SimpleOp(Operator2):
    
    dynamic_argnames= ("a",)
    
    def __init__(self, a, wires) -> None:
        super().__init__(a, wires)

op = SimpleOp(1.5, wires=[0])

so,

>>> abstractify(op)
SimpleOp(a=AbstractArray((), float64, weak_type=True), wires=AbstractWires(1))

Benefits: Utility function is created.

Possible Drawbacks: None identified.

[sc-122587]

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 99.46%. Comparing base (e035045) to head (18effe1).

Additional details and impacted files

@@                           Coverage Diff                           @@
##           fix/skip-child-constructor-if-abstract    #9694   +/-   ##
=======================================================================
  Coverage                                   99.46%   99.46%           
=======================================================================
  Files                                         629      630    +1     
  Lines                                       69071    69112   +41     
=======================================================================
+ Hits                                        68700    68742   +42     
+ Misses                                        371      370    -1     

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[andrijapau]

Using the metaclass for dispatch seems to work. Anything subtle I'm missing?

[mudit2812]

This can be reverted very soon

[andrijapau]

Should this go in typing.py? Only issue there is we pick up a dependency for typing to core.operator.