Refactor symbolic resource decomposition methods for resource estimation

[austingmhuang]

Context:
In pennylane/estimator/estimate.py, when we call _update_counts_from_compressed_op, we get our decomposition function using _get_decomposition, which returns the symbolic class's resource_decomp method. Rather than use that, we should to "cut out the middle man" -- instead of pointing to the symbolic's resource_decomp method, and having that point to the base class's symbolic_resource_decomp method, we can just point directly to the base class's symbolic_resource_decomp method.

Description of the Change:
Update _get_decomposition and _update_counts_from_compressed_op in pennylane/estimator/estimate.py to just call the base class's symbolic resource decomp method with the appropriate params and kwargs.

Now fully supports this UI:

def custom_adj_RZ(target_resource_params):
    return [qre.GateCount(qre.resource_rep(qre.Z))]

rc = qre.ResourceConfig()
rc.set_decomp(qre.RZ, custom_adj_RZ, decomp_type="adj")

res = qre.estimate(
    qre.Adjoint(qre.RZ()),
    config=rc
)

Benefits:
Simplifies the pipeline, improving readability and maintainability.

Possible Drawbacks:
The symbolic classes resource decomp method remains, which can be a source of confusion. A set of code comments is provided.

Related GitHub Issues:
[sc-103387]
[sc-103956]

[github-actions]

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[ddhawan11]

Thanks @austingmhuang. I think we should also add tests to make sure that the bug is fixed.

[ddhawan11]

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