Why is epoch_length required by iterable dataset?

I noticed that in version 0.4.0, epoch_length is mandatory for iterable dataset. I am curious about the rational behind it, since very often we don’t know the length of an iterable dataset beforehand and that’s why we use them.

[Yura52]

The concept of “epoch” can usually be applied only to the training phase. And literally one hour ago I ran into a situation when my validation loader was a finite iterator and I wanted to run validation over this loader just “until it is exhausted”. In fact I had to calculate the exact number of batches (and I can think of situations when I couldn’t do it, what would I do then?) just in order to make the run method happy. This was inconvenient. However, I don’t have a good suggestion how to fix this. Probably, one may support something like epoch_length='inf'.

[snie2012]

Essentially, the current implementation loses the information/control of how many times the data is actually iterated over. IMO, as @vfdev-5 mentioned, getting epoch_length automatically on the first StopIteration would be an ideal solution, since epoch_length can be helpful for purposes like visualization, but getting that length without iterating through it is challenging. Hope ignite can have that function!