INFO:2022-10-13 03:35:54,807:[predict.py:841 -        predict_main() ] Loading /project/model/ENCSR000DZD_split000.h5
INFO:2022-10-13 03:35:59,022:[predict.py:399 -             predict() ] SEQGEN Class Name: MBPNetSequenceGenerator
INFO:2022-10-13 03:35:59,043:[generators.py:508 -        _pad_samples() ] mode 'test': Data size (after padding 1009 samples) - 1024
INFO:2022-10-13 03:35:59,046:[predict.py:454 -             predict() ] Writing predictions to /project/predictions_and_metrics/ENCSR000DZD_split000_predictions.h5
DEBUG:2022-10-13 03:35:59,054:[generators.py:804 -          _epoch_run() ] test spawning process 0, df size (1024, 3) sum(num_batches) 1
DEBUG:2022-10-13 03:35:59,073:[generators.py:830 -          _epoch_run() ] test num_batches list [1]
DEBUG:2022-10-13 03:35:59,074:[generators.py:843 -          _epoch_run() ] test starting stealer thread 0 [1] 
DEBUG:2022-10-13 03:36:00,992:[generators.py:725 -        _proc_target() ] test process 0 put 1 batches into mpq
DEBUG:2022-10-13 03:36:01,484:[generators.py:749 -            _stealer() ] test stealer thread 0 got 1 batches from mpq
DEBUG:2022-10-13 03:36:05,563:[generators.py:887 -                 gen() ] test waiting to join process 0
DEBUG:2022-10-13 03:36:05,564:[generators.py:892 -                 gen() ] test waiting to join thread 0
DEBUG:2022-10-13 03:36:05,564:[generators.py:896 -                 gen() ] test join complete for process 0
DEBUG:2022-10-13 03:36:05,564:[generators.py:899 -                 gen() ] test Finished join for epoch
DEBUG:2022-10-13 03:36:05,564:[generators.py:901 -                 gen() ] test Ready for next epoch
INFO:2022-10-13 03:36:05,565:[predict.py:658 -             predict() ] Writing to h5 file ...
INFO:2022-10-13 03:36:05,585:[predict.py:674 -             predict() ] Elapsed Time: 6.536613702774048 secs
INFO:2022-10-13 03:36:05,585:[predict.py:678 -             predict() ] Generating predicted profile bigWigs ...
INFO:2022-10-13 03:36:05,585:[predict.py:680 -             predict() ] predictions shape - (15, 1000, 2)
INFO:2022-10-13 03:36:05,591:[predict.py:702 -             predict() ] bigWig HEADER - [('chr1', 248956422), ('chr10', 133797422), ('chr11', 135086622), ('chr12', 133275309), ('chr13', 114364328), ('chr14', 107043718), ('chr15', 101991189), ('chr16', 90338345), ('chr17', 83257441), ('chr18', 80373285), ('chr19', 58617616), ('chr2', 242193529), ('chr20', 64444167), ('chr21', 46709983), ('chr22', 50818468), ('chr3', 198295559), ('chr4', 190214555), ('chr5', 181538259), ('chr6', 170805979), ('chr7', 159345973), ('chr8', 145138636), ('chr9', 138394717), ('chrM', 16569), ('chrX', 156040895), ('chrY', 57227415)]
INFO:2022-10-13 03:36:05,663:[predict.py:728 -             predict() ] 		min		max		median
INFO:2022-10-13 03:36:05,664:[predict.py:733 -             predict() ] mnll		0.717		1.000		0.992
INFO:2022-10-13 03:36:05,664:[predict.py:738 -             predict() ] cross_entropy	0.717		1.000		0.992
INFO:2022-10-13 03:36:05,664:[predict.py:743 -             predict() ] jsd		0.531		0.998		0.721
INFO:2022-10-13 03:36:05,665:[predict.py:748 -             predict() ] spearman	-0.079		0.701		0.222
INFO:2022-10-13 03:36:05,665:[predict.py:753 -             predict() ] pearson		-0.219		0.507		0.178
INFO:2022-10-13 03:36:05,665:[predict.py:758 -             predict() ] mse		18.462		2243.582		177.834
INFO:2022-10-13 03:36:05,665:[predict.py:760 -             predict() ] ==============================================
INFO:2022-10-13 03:36:05,671:[predict.py:775 -             predict() ] counts pearson: [0.80915396 0.81344766]
INFO:2022-10-13 03:36:05,671:[predict.py:776 -             predict() ] counts spearman: [0.79642857 0.84285714]