What is the purpose of shuffling the validation set?

What is the purpose of shuffling the validation set during training of an artificial neural network? I understand why this makes sense for the training set, so that each minibatch has a different composition every time, but doesn't the ANN evaluate the whole validation set every epoch?

[robinho robinho]

what difference will it make to the trainning if the training set is shuffled?

Answer 1

[Greg Heath]

To impose and verify a consistent GENERALIZED path to convergence by avoiding repetitive anomalies.

Hope this helps

Greg

[Cynthia]

I'm sorry, but I think I am asking a different question than the one you are answering. It is my fault for being unclear. At the most basic level, I need to understand which validation set it is that is being shuffled. Is it the one I specify in trainingOptions? Or is it a validation set that is invisible to me, made from the training set?

[Kody Law]

I agree the answer does not help and it is not clear what this is about.

[Nicolò Viviani]

I also do not understand this Shuffling on validation data. I try to reformulate the question:

What the 'Shuffle' name-value pair of trainingOption does with validation data? I mean, what is the point of shuffling validation data?