Build tensorflow dataset iterator that produce batches with special structure

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Build tensorflow dataset iterator that produce batches with special structure



As I mentioned in the title I need batches with special structure:


1111
5555
2222



Each digit represent feature-vector. So there are N=4 vectors of each classes {1,2,5} (M=3) and batch size is NxM=12.


N=4


{1,2,5}


M=3


NxM=12



To accomplish this task I'm using Tensorflow Dataset API and tfrecords:


M


N



My concern is that I have hundreds (and maybe thousands in the feature) of classes and storing iterator for each class doesn't look good (from memory and performance perspective).



Is there a better way?









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