[FEA] Support args= in cudf.Series.apply

[brandon-b-miller]

Is your feature request related to a problem? Please describe.
As a follow up to https://github.com/rapidsai/cudf/pull/9514/files we should support functions that accept scalar (non column) arguments in cudf.Series.apply, similar to pandas. Right now, cudf.Series.apply works by turning the series into a full dataframe and wrapping the incoming function as a row function in a lambda, as seen here. This is all fine and good as long as the UDF always accepts one argument, but breaks down if we want args. As a note functions written for pandas.Series.apply are not row udfs and are written in scalar form:

def f(x):
    return x + 2

vs the row version, which would work on a single column dataframe

def f(x):
    x = row['x']
    return x + 2

Describe the solution you'd like
We want this to work, so we either need to:

1. come up with a more general mechanism to transform the scalar UDF into a row UDF and then play the same game of promoting the series to a dataframe/ forwarding to cudf.DataFrame.apply
2. write a separate kernel that works for series and reuses as much of the row compilation machinery as possible.

Ultimately though we want to be able to use UDFs that look like this on Series objects:

def f(x, c):
    return x + c

sr.apply(f, args=(42,))

Describe alternatives you've considered
One can always just promote the series to a single column dataframe and write a row UDF instead as a workaround, but that is rather suboptimal and clumsy for the user.

Additional context
N/A

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