I'm a bit confused on a minor point that I'm trying to discern due to a cross-validation strategy I've come across in my work that creates k-folds but the folds are not of equal length (for example some folds are of size 17, another 18, on up to 24). Is k-folds cross validation constrained to folds of equal length? Arbitrary choices of training data length and fold count can yield fractional numbers of course where one fold will draw the short stick but would it be accurate to say k-fold attempts to make roughly equal fold sizes?
In particular I'm hearing contradictory messages from in this question
Matt Krause "divided into different, mutually-exclusive 'folds'"
a Data Head "k-fold cross-validation (kFCV) divides the N data points into k mutually exclusive subsets of equal size."