remove redundant attributes_check

[aaarrti]

Description

• We have a function, attributes_check, which is used as a decorator, but it is not a decorator.
• Moreover, it does nothing, and therefore is completely redundant, so let's remove it.

Implemented changes

• Removed @attributes_check

To illustrate, what the problem is, let's look at the following example.

def attributes_check(metric):
    attr = metric.__dict__
    print(attr)

class A:
 @attributes_check
    def __init__(self, a=1, *, b=2):
        self.a = a
        self.b = b

1. Running it, we get {} printed out, the moment class definition is loaded. Because the function does not implement decorator patter (does not return a function), and metric is actually a type.
2. We get {} because __dict__ stores instance attributes, which will only be defined after __init__ (unless class is slotted).

[codecov-commenter]

Codecov Report

Merging #287 (4ced200) into main (f5f5805) will decrease coverage by 0.08%.
The diff coverage is n/a.

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@@            Coverage Diff             @@
##             main     #287      +/-   ##
==========================================
- Coverage   93.37%   93.29%   -0.08%     
==========================================
  Files          62       62              
  Lines        3471     3430      -41     
==========================================
- Hits         3241     3200      -41     
  Misses        230      230              

Files Changed	Coverage Δ
quantus/metrics/axiomatic/completeness.py	95.00% <ø> (-0.13%)	⬇️
quantus/metrics/axiomatic/input_invariance.py	100.00% <ø> (ø)
quantus/metrics/axiomatic/non_sensitivity.py	100.00% <ø> (ø)
quantus/metrics/base_batched.py	87.17% <ø> (-0.33%)	⬇️
quantus/metrics/base_perturbed.py	93.10% <ø> (-0.23%)	⬇️
quantus/metrics/complexity/complexity.py	100.00% <ø> (ø)
quantus/metrics/complexity/effective_complexity.py	100.00% <ø> (ø)
quantus/metrics/complexity/sparseness.py	100.00% <ø> (ø)
...s/metrics/faithfulness/faithfulness_correlation.py	96.22% <ø> (-0.07%)	⬇️
...ntus/metrics/faithfulness/faithfulness_estimate.py	98.14% <ø> (-0.04%)	⬇️
... and 27 more

[annahedstroem]

OK, thanks for this attention to detail!