[WIP][Return-types #7] QNode integration with custom gradient and autograd

[rmoyard]

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[sc-25813]

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[codecov[bot]]

Codecov Report

Merging #3041 (26d8324) into master (37a4024) will increase coverage by 0.00%. The diff coverage is 100.00%.

@@           Coverage Diff            @@
##           master    #3041    +/-   ##
========================================
  Coverage   99.69%   99.69%            
========================================
  Files         275      275            
  Lines       24012    24170   +158     
========================================
+ Hits        23938    24097   +159     
+ Misses         74       73     -1     

Impacted Files	Coverage Δ
pennylane/_grad.py	100.00% <ø> (ø)
pennylane/gradients/__init__.py	100.00% <100.00%> (ø)
pennylane/gradients/finite_difference.py	100.00% <100.00%> (ø)
pennylane/gradients/parameter_shift.py	100.00% <100.00%> (ø)
pennylane/gradients/vjp.py	100.00% <100.00%> (ø)
pennylane/interfaces/autograd.py	100.00% <100.00%> (ø)
pennylane/interfaces/execution.py	100.00% <100.00%> (ø)
pennylane/qnode.py	100.00% <100.00%> (ø)
pennylane/math/utils.py	100.00% <0.00%> (+0.88%)	:arrow_up:

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[rmoyard]

@eddddddy @antalszava It is ready for a new round of reviews!

Two things I could not solve is:

1. @antalszava Why numpy array with shape () are converted to float, single measurment and single params. I would appreciate your input here.
2. @eddddddy The sum with axis 0 is not working with ArrayBox and differentiation, see my comment above. I could not simplify compute_vjp more.

Also pls go through the open comments and close the one where my answer was sufficient.

[rmoyard]

[sc-28429]