I'm interested in learning a joint classification/regression network.
I have a lmdb with 2 million+ images and labels. Additionally I have regression target data in a hdf5 file with data shape (2000000,84,1,1) and label shape (2000000,1).
The labels in both the lmdb and hdf5 file are redundant.
I created the lmdb using the tools/convert_imageset executable and forced shuffle to false to maintain order with the hdf5.
To verify if the order is maintained, I've concatenated the labels from both the lmdb and hdf5 and stored using a HDF5_OUTPUT layer.
The order of the lmdb labels appears to have somehow changed.
Is there some shuffling going on in the batch train or test process?
I can't find any info on the order samples are selected -- I have assumed they are sequential.
What is the best way of ensuring data selected from two separate data layers are selected such that the batches keep in sync with the correct order?