INFO:2022-10-13 03:36:10,986:[predict.py:841 -        predict_main() ] Loading /project/model/ENCSR000DYG_split000.h5
INFO:2022-10-13 03:36:15,245:[predict.py:399 -             predict() ] SEQGEN Class Name: MBPNetSequenceGenerator
INFO:2022-10-13 03:36:15,266:[generators.py:508 -        _pad_samples() ] mode 'test': Data size (after padding 1009 samples) - 1024
INFO:2022-10-13 03:36:15,269:[predict.py:454 -             predict() ] Writing predictions to /project/predictions_and_metrics/ENCSR000DYG_split000_predictions.h5
DEBUG:2022-10-13 03:36:15,278:[generators.py:804 -          _epoch_run() ] test spawning process 0, df size (1024, 3) sum(num_batches) 1
DEBUG:2022-10-13 03:36:15,296:[generators.py:830 -          _epoch_run() ] test num_batches list [1]
DEBUG:2022-10-13 03:36:15,297:[generators.py:843 -          _epoch_run() ] test starting stealer thread 0 [1] 
DEBUG:2022-10-13 03:36:17,206:[generators.py:725 -        _proc_target() ] test process 0 put 1 batches into mpq
DEBUG:2022-10-13 03:36:17,694:[generators.py:749 -            _stealer() ] test stealer thread 0 got 1 batches from mpq
DEBUG:2022-10-13 03:36:21,716:[generators.py:887 -                 gen() ] test waiting to join process 0
DEBUG:2022-10-13 03:36:21,716:[generators.py:892 -                 gen() ] test waiting to join thread 0
DEBUG:2022-10-13 03:36:21,716:[generators.py:896 -                 gen() ] test join complete for process 0
DEBUG:2022-10-13 03:36:21,716:[generators.py:899 -                 gen() ] test Finished join for epoch
DEBUG:2022-10-13 03:36:21,717:[generators.py:901 -                 gen() ] test Ready for next epoch
INFO:2022-10-13 03:36:21,717:[predict.py:658 -             predict() ] Writing to h5 file ...
INFO:2022-10-13 03:36:21,738:[predict.py:674 -             predict() ] Elapsed Time: 6.466385126113892 secs
INFO:2022-10-13 03:36:21,738:[predict.py:678 -             predict() ] Generating predicted profile bigWigs ...
INFO:2022-10-13 03:36:21,739:[predict.py:680 -             predict() ] predictions shape - (15, 1000, 2)
INFO:2022-10-13 03:36:21,744:[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 03:36:21,816:[predict.py:728 -             predict() ] 		min		max		median
INFO:2022-10-13 03:36:21,816:[predict.py:733 -             predict() ] mnll		0.524		1.000		0.747
INFO:2022-10-13 03:36:21,817:[predict.py:738 -             predict() ] cross_entropy	0.524		1.000		0.747
INFO:2022-10-13 03:36:21,817:[predict.py:743 -             predict() ] jsd		0.617		1.000		0.700
INFO:2022-10-13 03:36:21,818:[predict.py:748 -             predict() ] spearman	0.245		0.745		0.535
INFO:2022-10-13 03:36:21,818:[predict.py:753 -             predict() ] pearson		0.360		0.803		0.605
INFO:2022-10-13 03:36:21,818:[predict.py:758 -             predict() ] mse		27.341		1862.512		158.080
INFO:2022-10-13 03:36:21,818:[predict.py:760 -             predict() ] ==============================================
INFO:2022-10-13 03:36:21,823:[predict.py:775 -             predict() ] counts pearson: [0.94171895 0.9560656 ]
INFO:2022-10-13 03:36:21,823:[predict.py:776 -             predict() ] counts spearman: [0.93571429 0.96785714]