Hello. I’m quite new here, so kind explanation will be really appreciated.
I have a data set that consists of two smaller data sets.
Set A : A_1, A_2, … , A_n
Set B : B_1, B_2, … , B_m
Here, m is larger than n.
I’m trying to hire torch.utils.data.DataLoader() to make one-size mini-batches from above data.
What I want is, each mini-batch be as follows.
(A_1, B_1)
(A_2, B_2)
…
(A_n, B_n)
(A_1, B_n+1)
…
(A_whatever, B_m)
When I run it, the order of A is perfect.
But problem is, the order of B be random.
Only options I used are mini-batch size and number of threads.
(And of course, these do not effects to my problem, right?)
I do not add any options: sampler, shuffle, etc.
How can I maintain the order of original data sets?