INFO:2022-10-13 03:36:58,059:[predict.py:841 -        predict_main() ] Loading /project/model/ENCSR822CCM_split000.h5
INFO:2022-10-13 03:37:02,355:[predict.py:399 -             predict() ] SEQGEN Class Name: MBPNetSequenceGenerator
INFO:2022-10-13 03:37:02,375:[generators.py:508 -        _pad_samples() ] mode 'test': Data size (after padding 1009 samples) - 1024
INFO:2022-10-13 03:37:02,378:[predict.py:454 -             predict() ] Writing predictions to /project/predictions_and_metrics/ENCSR822CCM_split000_predictions.h5
DEBUG:2022-10-13 03:37:02,386:[generators.py:804 -          _epoch_run() ] test spawning process 0, df size (1024, 3) sum(num_batches) 1
DEBUG:2022-10-13 03:37:02,404:[generators.py:830 -          _epoch_run() ] test num_batches list [1]
DEBUG:2022-10-13 03:37:02,405:[generators.py:843 -          _epoch_run() ] test starting stealer thread 0 [1] 
DEBUG:2022-10-13 03:37:04,482:[generators.py:725 -        _proc_target() ] test process 0 put 1 batches into mpq
DEBUG:2022-10-13 03:37:05,000:[generators.py:749 -            _stealer() ] test stealer thread 0 got 1 batches from mpq
DEBUG:2022-10-13 03:37:09,010:[generators.py:887 -                 gen() ] test waiting to join process 0
DEBUG:2022-10-13 03:37:09,011:[generators.py:892 -                 gen() ] test waiting to join thread 0
DEBUG:2022-10-13 03:37:09,011:[generators.py:896 -                 gen() ] test join complete for process 0
DEBUG:2022-10-13 03:37:09,011:[generators.py:899 -                 gen() ] test Finished join for epoch
DEBUG:2022-10-13 03:37:09,011:[generators.py:901 -                 gen() ] test Ready for next epoch
INFO:2022-10-13 03:37:09,012:[predict.py:658 -             predict() ] Writing to h5 file ...
INFO:2022-10-13 03:37:09,034:[predict.py:674 -             predict() ] Elapsed Time: 6.652977228164673 secs
INFO:2022-10-13 03:37:09,034:[predict.py:678 -             predict() ] Generating predicted profile bigWigs ...
INFO:2022-10-13 03:37:09,034:[predict.py:680 -             predict() ] predictions shape - (15, 1000, 2)
INFO:2022-10-13 03:37:09,039:[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 03:37:09,109:[predict.py:728 -             predict() ] 		min		max		median
INFO:2022-10-13 03:37:09,110:[predict.py:733 -             predict() ] mnll		1.000		1.000		1.000
INFO:2022-10-13 03:37:09,110:[predict.py:738 -             predict() ] cross_entropy	1.000		1.000		1.000
INFO:2022-10-13 03:37:09,110:[predict.py:743 -             predict() ] jsd		1.000		1.000		1.000
INFO:2022-10-13 03:37:09,111:[predict.py:748 -             predict() ] spearman	0.018		0.314		0.092
INFO:2022-10-13 03:37:09,111:[predict.py:753 -             predict() ] pearson		0.230		0.942		0.821
INFO:2022-10-13 03:37:09,111:[predict.py:758 -             predict() ] mse		214.786		11844061447.214		227927560.855
INFO:2022-10-13 03:37:09,112:[predict.py:760 -             predict() ] ==============================================
INFO:2022-10-13 03:37:09,116:[predict.py:775 -             predict() ] counts pearson: [0.31256621 0.70490103]
INFO:2022-10-13 03:37:09,117:[predict.py:776 -             predict() ] counts spearman: [0.53928571 0.50357143]