Passing invalid conditions when using constraints produces unreadable errors

[fealho]

Currently, using invalid conditions when using constraints produces unreadable errors. Instead, it would make more sense to validate the inputs and produce more meaningful error messages.

For example, if we use the UniqueCombination constraint and condition on the two constraint columns being different (which is an invalid condition) it produces a ValueError: No objects to concatenate, which doesn't provide much feedback about where the error is.

import pandas as pd
from sdv.constraints import *
from sdv.tabular import *

zero_to_nine = [i for i in range(10)]
data = pd.DataFrame({
    'a': zero_to_nine,
    'b': zero_to_nine,
    'c': zero_to_nine
})

constraint = UniqueCombinations(
    columns=['a', 'b'],
)

model = CTGAN(constraints=[constraint])
model.fit(data)
samples = model.sample(10, conditions={'a': 0, 'b': 1})