diff --git "a/fold_0/logs.models.fold_0.ENCSR372IGW/logfile.modelling.fold_0.ENCSR372IGW.stdout_v1.txt" "b/fold_0/logs.models.fold_0.ENCSR372IGW/logfile.modelling.fold_0.ENCSR372IGW.stdout_v1.txt"
new file mode 100644--- /dev/null
+++ "b/fold_0/logs.models.fold_0.ENCSR372IGW/logfile.modelling.fold_0.ENCSR372IGW.stdout_v1.txt"
@@ -0,0 +1,456 @@
+2022-03-24_13-52-56: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/helpers/hyperparameters/find_chrombpnet_hyperparams.py \
+       --genome=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+       --bigwig=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/bigWigs/ENCSR372IGW.bigWig \
+       --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/downloads/peaks.bed.gz \
+       --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//negatives_data/negatives_with_summit.bed \
+       --outlier_threshold=0.99 \
+       --chr_fold_path=/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json \
+       --negative_sampling_ratio=0.1 \
+       --inputlen=2114 \
+       --outputlen=1000 \
+       --max_jitter=500 \
+       --filters=512 \
+       --n_dilation_layers=8 \
+       --bias_model_path=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/k562_atac_bias_new.h5 \
+       --output_dir=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/ 
+evaluating hyperparameters on the following chromosomes ['chr2', 'chr4', 'chr5', 'chr7', 'chr9', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15', 'chr16', 'chr17', 'chr18', 'chr19', 'chr21', 'chr22', 'chrX', 'chrY', 'chr8', 'chr20']
+Number of peaks input:  156125
+Number of peaks filtered because the input/output is on the edge:  0
+Number of peaks being used:  156125
+Number of peaks input:  46309
+Number of peaks filtered because the input/output is on the edge:  0
+Number of peaks being used:  46309
+Number of non peaks input:  156125
+Number of non peaks filtered because the input/output is on the edge:  0
+Number of non peaks being used:  156125
+Number of non peaks input:  46308
+Number of non peaks filtered because the input/output is on the edge:  0
+Number of non peaks being used:  46308
+Number of peaks after removing outliers:  154407
+Number of nonpeaks after removing outliers:  136132
+got the model
+Model: "functional_1"
+__________________________________________________________________________________________________
+Layer (type)                    Output Shape         Param #     Connected to                     
+==================================================================================================
+sequence (InputLayer)           [(None, 2114, 4)]    0                                            
+__________________________________________________________________________________________________
+bpnet_1st_conv (Conv1D)         (None, 2094, 128)    10880       sequence[0][0]                   
+__________________________________________________________________________________________________
+bpnet_1conv (Conv1D)            (None, 2090, 128)    49280       bpnet_1st_conv[0][0]             
+__________________________________________________________________________________________________
+bpnet_1crop (Cropping1D)        (None, 2090, 128)    0           bpnet_1st_conv[0][0]             
+__________________________________________________________________________________________________
+add (Add)                       (None, 2090, 128)    0           bpnet_1conv[0][0]                
+                                                                 bpnet_1crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_2conv (Conv1D)            (None, 2082, 128)    49280       add[0][0]                        
+__________________________________________________________________________________________________
+bpnet_2crop (Cropping1D)        (None, 2082, 128)    0           add[0][0]                        
+__________________________________________________________________________________________________
+add_1 (Add)                     (None, 2082, 128)    0           bpnet_2conv[0][0]                
+                                                                 bpnet_2crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_3conv (Conv1D)            (None, 2066, 128)    49280       add_1[0][0]                      
+__________________________________________________________________________________________________
+bpnet_3crop (Cropping1D)        (None, 2066, 128)    0           add_1[0][0]                      
+__________________________________________________________________________________________________
+add_2 (Add)                     (None, 2066, 128)    0           bpnet_3conv[0][0]                
+                                                                 bpnet_3crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_4conv (Conv1D)            (None, 2034, 128)    49280       add_2[0][0]                      
+__________________________________________________________________________________________________
+bpnet_4crop (Cropping1D)        (None, 2034, 128)    0           add_2[0][0]                      
+__________________________________________________________________________________________________
+add_3 (Add)                     (None, 2034, 128)    0           bpnet_4conv[0][0]                
+                                                                 bpnet_4crop[0][0]                
+__________________________________________________________________________________________________
+prof_out_precrop (Conv1D)       (None, 1960, 1)      9601        add_3[0][0]                      
+__________________________________________________________________________________________________
+logits_profile_predictions_pref (None, 1000, 1)      0           prof_out_precrop[0][0]           
+__________________________________________________________________________________________________
+gap (GlobalAveragePooling1D)    (None, 128)          0           add_3[0][0]                      
+__________________________________________________________________________________________________
+logits_profile_predictions (Fla (None, 1000)         0           logits_profile_predictions_prefla
+__________________________________________________________________________________________________
+logcount_predictions (Dense)    (None, 1)            129         gap[0][0]                        
+==================================================================================================
+Total params: 217,730
+Trainable params: 217,730
+Non-trainable params: 0
+__________________________________________________________________________________________________
+Predicting within adjust counts
+
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+2022-03-24_14-00-00: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/train.py \
+       --genome=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+       --bigwig=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/bigWigs/ENCSR372IGW.bigWig \
+       --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.peaks.bed \
+       --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+       --params=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet_model_params.tsv \
+       --output_prefix=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet \
+       --chr_fold_path=/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json \
+       --batch_size=64 \
+       --architecture_from_file=/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py \
+       --trackables logcount_predictions_loss loss logits_profile_predictions_loss val_logcount_predictions_loss val_loss val_logits_profile_predictions_loss
+{'counts_loss_weight': '16.0', 'filters': '512', 'n_dil_layers': '8', 'bias_model_path': '/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/bias_model_scaled.h5', 'inputlen': '2114', 'outputlen': '1000', 'max_jitter': '500', 'chr_fold_path': '/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json', 'negative_sampling_ratio': '0.1'}
+got the model
+loading peaks...
+got split:train for bed regions:(139997, 10)
+loading nonpeaks...
+got split:train for bed regions:(123153, 10)
+loading peaks...
+got split:valid for bed regions:(14410, 10)
+loading nonpeaks...
+got split:valid for bed regions:(12979, 10)
+Epoch 1/50
+
   1/2407 [..............................] - ETA: 6:50:16 - loss: 500.7814 - logits_profile_predictions_loss: 426.1954 - logcount_predictions_loss: 4.6616
   2/2407 [..............................] - ETA: 22:43 - loss: 521.0633 - logits_profile_predictions_loss: 411.3070 - logcount_predictions_loss: 6.8598  
   3/2407 [..............................] - ETA: 22:40 - loss: 511.4525 - logits_profile_predictions_loss: 399.7852 - logcount_predictions_loss: 6.9792
   4/2407 [..............................] - ETA: 22:39 - loss: 510.2178 - logits_profile_predictions_loss: 399.2950 - logcount_predictions_loss: 6.9327
   5/2407 [..............................] - ETA: 22:38 - loss: 508.6639 - logits_profile_predictions_loss: 399.5043 - logcount_predictions_loss: 6.8225
   6/2407 [..............................] - ETA: 22:37 - loss: 508.5493 - logits_profile_predictions_loss: 400.9641 - logcount_predictions_loss: 6.7241
   7/2407 [..............................] - ETA: 22:37 - loss: 508.3177 - logits_profile_predictions_loss: 402.2852 - logcount_predictions_loss: 6.6270
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1962/2407 [=======================>......] - ETA: 4:11 - loss: 439.5912 - logits_profile_predictions_loss: 383.7924 - logcount_predictions_loss: 3.4874
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1966/2407 [=======================>......] - ETA: 4:09 - loss: 439.5234 - logits_profile_predictions_loss: 383.7705 - logcount_predictions_loss: 3.4845
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1969/2407 [=======================>......] - ETA: 4:07 - loss: 439.4727 - logits_profile_predictions_loss: 383.7542 - logcount_predictions_loss: 3.4824
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1971/2407 [=======================>......] - ETA: 4:06 - loss: 439.4390 - logits_profile_predictions_loss: 383.7433 - logcount_predictions_loss: 3.4810
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2012/2407 [========================>.....] - ETA: 3:43 - loss: 438.7571 - logits_profile_predictions_loss: 383.5245 - logcount_predictions_loss: 3.4520
2013/2407 [========================>.....] - ETA: 3:42 - loss: 438.7407 - logits_profile_predictions_loss: 383.5193 - logcount_predictions_loss: 3.4513
2014/2407 [========================>.....] - ETA: 3:42 - loss: 438.7243 - logits_profile_predictions_loss: 383.5140 - logcount_predictions_loss: 3.4506
2015/2407 [========================>.....] - ETA: 3:41 - loss: 438.7078 - logits_profile_predictions_loss: 383.5087 - logcount_predictions_loss: 3.4499
2016/2407 [========================>.....] - ETA: 3:41 - loss: 438.6914 - logits_profile_predictions_loss: 383.5035 - logcount_predictions_loss: 3.4492
2017/2407 [========================>.....] - ETA: 3:40 - loss: 438.6750 - logits_profile_predictions_loss: 383.4982 - logcount_predictions_loss: 3.4485
2018/2407 [========================>.....] - ETA: 3:40 - loss: 438.6587 - logits_profile_predictions_loss: 383.4930 - logcount_predictions_loss: 3.4478
2019/2407 [========================>.....] - ETA: 3:39 - loss: 438.6423 - logits_profile_predictions_loss: 383.4878 - logcount_predictions_loss: 3.4471
2020/2407 [========================>.....] - ETA: 3:38 - loss: 438.6259 - logits_profile_predictions_loss: 383.4825 - logcount_predictions_loss: 3.4465
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2402/2407 [============================>.] - ETA: 2s - loss: 432.9189 - logits_profile_predictions_loss: 381.6291 - logcount_predictions_loss: 3.2056
2403/2407 [============================>.] - ETA: 2s - loss: 432.9052 - logits_profile_predictions_loss: 381.6245 - logcount_predictions_loss: 3.2050
2404/2407 [============================>.] - ETA: 1s - loss: 432.8915 - logits_profile_predictions_loss: 381.6200 - logcount_predictions_loss: 3.2045
2405/2407 [============================>.] - ETA: 1s - loss: 432.8779 - logits_profile_predictions_loss: 381.6154 - logcount_predictions_loss: 3.2039
2406/2407 [============================>.] - ETA: 0s - loss: 432.8642 - logits_profile_predictions_loss: 381.6109 - logcount_predictions_loss: 3.2033
2407/2407 [==============================] - ETA: 0s - loss: 432.8506 - logits_profile_predictions_loss: 381.6064 - logcount_predictions_loss: 3.2027
2407/2407 [==============================] - 1424s 588ms/step - loss: 432.8370 - logits_profile_predictions_loss: 381.6018 - logcount_predictions_loss: 3.2022 - val_loss: 392.9085 - val_logits_profile_predictions_loss: 381.1862 - val_logcount_predictions_loss: 0.7326
+
+Epoch 00001: val_loss improved from inf to 392.90848, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 2/50
+
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2407/2407 [==============================] - ETA: 0s - loss: 366.1554 - logits_profile_predictions_loss: 354.6201 - logcount_predictions_loss: 0.7210
2407/2407 [==============================] - 1410s 586ms/step - loss: 366.1548 - logits_profile_predictions_loss: 354.6196 - logcount_predictions_loss: 0.7210 - val_loss: 385.1435 - val_logits_profile_predictions_loss: 374.4642 - val_logcount_predictions_loss: 0.6675
+
+Epoch 00002: val_loss improved from 392.90848 to 385.14346, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 3/50
+
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2018/2407 [========================>.....] - ETA: 3:39 - loss: 359.8259 - logits_profile_predictions_loss: 349.3900 - logcount_predictions_loss: 0.6523
2019/2407 [========================>.....] - ETA: 3:39 - loss: 359.8255 - logits_profile_predictions_loss: 349.3897 - logcount_predictions_loss: 0.6523
2020/2407 [========================>.....] - ETA: 3:38 - loss: 359.8251 - logits_profile_predictions_loss: 349.3894 - logcount_predictions_loss: 0.6523
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2407/2407 [==============================] - 1411s 586ms/step - loss: 359.6539 - logits_profile_predictions_loss: 349.2491 - logcount_predictions_loss: 0.6503 - val_loss: 381.4310 - val_logits_profile_predictions_loss: 371.5085 - val_logcount_predictions_loss: 0.6202
+
+Epoch 00003: val_loss improved from 385.14346 to 381.43103, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 4/50
+
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2015/2407 [========================>.....] - ETA: 3:41 - loss: 354.1433 - logits_profile_predictions_loss: 344.5398 - logcount_predictions_loss: 0.6002
2016/2407 [========================>.....] - ETA: 3:40 - loss: 354.1434 - logits_profile_predictions_loss: 344.5400 - logcount_predictions_loss: 0.6002
2017/2407 [========================>.....] - ETA: 3:40 - loss: 354.1436 - logits_profile_predictions_loss: 344.5402 - logcount_predictions_loss: 0.6002
2018/2407 [========================>.....] - ETA: 3:39 - loss: 354.1438 - logits_profile_predictions_loss: 344.5404 - logcount_predictions_loss: 0.6002
2019/2407 [========================>.....] - ETA: 3:39 - loss: 354.1439 - logits_profile_predictions_loss: 344.5406 - logcount_predictions_loss: 0.6002
2020/2407 [========================>.....] - ETA: 3:38 - loss: 354.1440 - logits_profile_predictions_loss: 344.5408 - logcount_predictions_loss: 0.6002
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2407/2407 [==============================] - ETA: 0s - loss: 354.1710 - logits_profile_predictions_loss: 344.5840 - logcount_predictions_loss: 0.5992
2407/2407 [==============================] - 1411s 586ms/step - loss: 354.1710 - logits_profile_predictions_loss: 344.5840 - logcount_predictions_loss: 0.5992 - val_loss: 381.9931 - val_logits_profile_predictions_loss: 371.3797 - val_logcount_predictions_loss: 0.6633
+
+Epoch 00004: val_loss did not improve from 381.43103
+Epoch 5/50
+
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2402/2407 [============================>.] - ETA: 2s - loss: 351.4496 - logits_profile_predictions_loss: 342.3816 - logcount_predictions_loss: 0.5667
2403/2407 [============================>.] - ETA: 2s - loss: 351.4493 - logits_profile_predictions_loss: 342.3813 - logcount_predictions_loss: 0.5667
2404/2407 [============================>.] - ETA: 1s - loss: 351.4490 - logits_profile_predictions_loss: 342.3810 - logcount_predictions_loss: 0.5667
2405/2407 [============================>.] - ETA: 1s - loss: 351.4486 - logits_profile_predictions_loss: 342.3806 - logcount_predictions_loss: 0.5667
2406/2407 [============================>.] - ETA: 0s - loss: 351.4483 - logits_profile_predictions_loss: 342.3803 - logcount_predictions_loss: 0.5667
2407/2407 [==============================] - ETA: 0s - loss: 351.4479 - logits_profile_predictions_loss: 342.3800 - logcount_predictions_loss: 0.5667
2407/2407 [==============================] - 1411s 586ms/step - loss: 351.4476 - logits_profile_predictions_loss: 342.3796 - logcount_predictions_loss: 0.5667 - val_loss: 381.6173 - val_logits_profile_predictions_loss: 371.4456 - val_logcount_predictions_loss: 0.6357
+
+Epoch 00005: val_loss did not improve from 381.43103
+Epoch 6/50
+
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2015/2407 [========================>.....] - ETA: 3:41 - loss: 348.0041 - logits_profile_predictions_loss: 339.5054 - logcount_predictions_loss: 0.5312
2016/2407 [========================>.....] - ETA: 3:41 - loss: 348.0044 - logits_profile_predictions_loss: 339.5056 - logcount_predictions_loss: 0.5312
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2018/2407 [========================>.....] - ETA: 3:39 - loss: 348.0049 - logits_profile_predictions_loss: 339.5061 - logcount_predictions_loss: 0.5312
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2020/2407 [========================>.....] - ETA: 3:38 - loss: 348.0054 - logits_profile_predictions_loss: 339.5066 - logcount_predictions_loss: 0.5312
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2407/2407 [==============================] - ETA: 0s - loss: 348.0715 - logits_profile_predictions_loss: 339.5677 - logcount_predictions_loss: 0.5315
2407/2407 [==============================] - 1412s 587ms/step - loss: 348.0716 - logits_profile_predictions_loss: 339.5678 - logcount_predictions_loss: 0.5315 - val_loss: 382.2980 - val_logits_profile_predictions_loss: 371.3376 - val_logcount_predictions_loss: 0.6850
+
+Epoch 00006: val_loss did not improve from 381.43103
+Epoch 7/50
+
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2011/2407 [========================>.....] - ETA: 3:43 - loss: 343.7494 - logits_profile_predictions_loss: 336.2798 - logcount_predictions_loss: 0.4669
2012/2407 [========================>.....] - ETA: 3:43 - loss: 343.7489 - logits_profile_predictions_loss: 336.2793 - logcount_predictions_loss: 0.4668
2013/2407 [========================>.....] - ETA: 3:42 - loss: 343.7483 - logits_profile_predictions_loss: 336.2788 - logcount_predictions_loss: 0.4668
2014/2407 [========================>.....] - ETA: 3:42 - loss: 343.7477 - logits_profile_predictions_loss: 336.2783 - logcount_predictions_loss: 0.4668
2015/2407 [========================>.....] - ETA: 3:41 - loss: 343.7472 - logits_profile_predictions_loss: 336.2778 - logcount_predictions_loss: 0.4668
2016/2407 [========================>.....] - ETA: 3:40 - loss: 343.7466 - logits_profile_predictions_loss: 336.2773 - logcount_predictions_loss: 0.4668
2017/2407 [========================>.....] - ETA: 3:40 - loss: 343.7460 - logits_profile_predictions_loss: 336.2768 - logcount_predictions_loss: 0.4668
2018/2407 [========================>.....] - ETA: 3:39 - loss: 343.7454 - logits_profile_predictions_loss: 336.2763 - logcount_predictions_loss: 0.4668
2019/2407 [========================>.....] - ETA: 3:39 - loss: 343.7448 - logits_profile_predictions_loss: 336.2758 - logcount_predictions_loss: 0.4668
2020/2407 [========================>.....] - ETA: 3:38 - loss: 343.7442 - logits_profile_predictions_loss: 336.2753 - logcount_predictions_loss: 0.4668
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2407/2407 [==============================] - ETA: 0s - loss: 343.5168 - logits_profile_predictions_loss: 336.0777 - logcount_predictions_loss: 0.4650
2407/2407 [==============================] - 1411s 586ms/step - loss: 343.5163 - logits_profile_predictions_loss: 336.0772 - logcount_predictions_loss: 0.4649 - val_loss: 379.6790 - val_logits_profile_predictions_loss: 370.2482 - val_logcount_predictions_loss: 0.5894
+
+Epoch 00007: val_loss improved from 381.43103 to 379.67899, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 8/50
+
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2015/2407 [========================>.....] - ETA: 3:41 - loss: 340.4489 - logits_profile_predictions_loss: 333.7366 - logcount_predictions_loss: 0.4195
2016/2407 [========================>.....] - ETA: 3:40 - loss: 340.4482 - logits_profile_predictions_loss: 333.7360 - logcount_predictions_loss: 0.4195
2017/2407 [========================>.....] - ETA: 3:40 - loss: 340.4475 - logits_profile_predictions_loss: 333.7353 - logcount_predictions_loss: 0.4195
2018/2407 [========================>.....] - ETA: 3:39 - loss: 340.4468 - logits_profile_predictions_loss: 333.7347 - logcount_predictions_loss: 0.4195
2019/2407 [========================>.....] - ETA: 3:38 - loss: 340.4462 - logits_profile_predictions_loss: 333.7340 - logcount_predictions_loss: 0.4195
2020/2407 [========================>.....] - ETA: 3:38 - loss: 340.4455 - logits_profile_predictions_loss: 333.7333 - logcount_predictions_loss: 0.4195
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2407/2407 [==============================] - ETA: 0s - loss: 340.2364 - logits_profile_predictions_loss: 333.5416 - logcount_predictions_loss: 0.4184
2407/2407 [==============================] - 1409s 585ms/step - loss: 340.2359 - logits_profile_predictions_loss: 333.5412 - logcount_predictions_loss: 0.4184 - val_loss: 380.7909 - val_logits_profile_predictions_loss: 371.1165 - val_logcount_predictions_loss: 0.6046
+
+Epoch 00008: val_loss did not improve from 379.67899
+Epoch 9/50
+
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2013/2407 [========================>.....] - ETA: 3:42 - loss: 337.9634 - logits_profile_predictions_loss: 331.8249 - logcount_predictions_loss: 0.3837
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2015/2407 [========================>.....] - ETA: 3:41 - loss: 337.9625 - logits_profile_predictions_loss: 331.8240 - logcount_predictions_loss: 0.3837
2016/2407 [========================>.....] - ETA: 3:41 - loss: 337.9620 - logits_profile_predictions_loss: 331.8236 - logcount_predictions_loss: 0.3837
2017/2407 [========================>.....] - ETA: 3:40 - loss: 337.9615 - logits_profile_predictions_loss: 331.8231 - logcount_predictions_loss: 0.3836
2018/2407 [========================>.....] - ETA: 3:39 - loss: 337.9610 - logits_profile_predictions_loss: 331.8227 - logcount_predictions_loss: 0.3836
2019/2407 [========================>.....] - ETA: 3:39 - loss: 337.9605 - logits_profile_predictions_loss: 331.8222 - logcount_predictions_loss: 0.3836
2020/2407 [========================>.....] - ETA: 3:38 - loss: 337.9600 - logits_profile_predictions_loss: 331.8218 - logcount_predictions_loss: 0.3836
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2390/2407 [============================>.] - ETA: 9s - loss: 337.7996 - logits_profile_predictions_loss: 331.6740 - logcount_predictions_loss: 0.3828 
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2392/2407 [============================>.] - ETA: 8s - loss: 337.7989 - logits_profile_predictions_loss: 331.6734 - logcount_predictions_loss: 0.3828
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2394/2407 [============================>.] - ETA: 7s - loss: 337.7981 - logits_profile_predictions_loss: 331.6727 - logcount_predictions_loss: 0.3828
2395/2407 [============================>.] - ETA: 6s - loss: 337.7978 - logits_profile_predictions_loss: 331.6724 - logcount_predictions_loss: 0.3828
2396/2407 [============================>.] - ETA: 6s - loss: 337.7974 - logits_profile_predictions_loss: 331.6720 - logcount_predictions_loss: 0.3828
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2398/2407 [============================>.] - ETA: 5s - loss: 337.7967 - logits_profile_predictions_loss: 331.6714 - logcount_predictions_loss: 0.3828
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2401/2407 [============================>.] - ETA: 3s - loss: 337.7957 - logits_profile_predictions_loss: 331.6704 - logcount_predictions_loss: 0.3828
2402/2407 [============================>.] - ETA: 2s - loss: 337.7953 - logits_profile_predictions_loss: 331.6701 - logcount_predictions_loss: 0.3828
2403/2407 [============================>.] - ETA: 2s - loss: 337.7950 - logits_profile_predictions_loss: 331.6698 - logcount_predictions_loss: 0.3828
2404/2407 [============================>.] - ETA: 1s - loss: 337.7946 - logits_profile_predictions_loss: 331.6695 - logcount_predictions_loss: 0.3828
2405/2407 [============================>.] - ETA: 1s - loss: 337.7943 - logits_profile_predictions_loss: 331.6692 - logcount_predictions_loss: 0.3828
2406/2407 [============================>.] - ETA: 0s - loss: 337.7939 - logits_profile_predictions_loss: 331.6689 - logcount_predictions_loss: 0.3828
2407/2407 [==============================] - ETA: 0s - loss: 337.7936 - logits_profile_predictions_loss: 331.6686 - logcount_predictions_loss: 0.3828
2407/2407 [==============================] - 1412s 586ms/step - loss: 337.7933 - logits_profile_predictions_loss: 331.6683 - logcount_predictions_loss: 0.3828 - val_loss: 382.2128 - val_logits_profile_predictions_loss: 371.7258 - val_logcount_predictions_loss: 0.6554
+
+Epoch 00009: val_loss did not improve from 379.67899
+Epoch 10/50
+
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2407/2407 [==============================] - ETA: 0s - loss: 335.3700 - logits_profile_predictions_loss: 329.8320 - logcount_predictions_loss: 0.3461
2407/2407 [==============================] - 1411s 586ms/step - loss: 335.3699 - logits_profile_predictions_loss: 329.8320 - logcount_predictions_loss: 0.3461 - val_loss: 385.3400 - val_logits_profile_predictions_loss: 372.3350 - val_logcount_predictions_loss: 0.8128
+
+Epoch 00010: val_loss did not improve from 379.67899
+Epoch 11/50
+
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2014/2407 [========================>.....] - ETA: 3:41 - loss: 330.3676 - logits_profile_predictions_loss: 325.6466 - logcount_predictions_loss: 0.2951
2015/2407 [========================>.....] - ETA: 3:41 - loss: 330.3682 - logits_profile_predictions_loss: 325.6472 - logcount_predictions_loss: 0.2951
2016/2407 [========================>.....] - ETA: 3:40 - loss: 330.3689 - logits_profile_predictions_loss: 325.6479 - logcount_predictions_loss: 0.2951
2017/2407 [========================>.....] - ETA: 3:40 - loss: 330.3695 - logits_profile_predictions_loss: 325.6485 - logcount_predictions_loss: 0.2951
2018/2407 [========================>.....] - ETA: 3:39 - loss: 330.3701 - logits_profile_predictions_loss: 325.6491 - logcount_predictions_loss: 0.2951
2019/2407 [========================>.....] - ETA: 3:39 - loss: 330.3707 - logits_profile_predictions_loss: 325.6498 - logcount_predictions_loss: 0.2951
2020/2407 [========================>.....] - ETA: 3:38 - loss: 330.3713 - logits_profile_predictions_loss: 325.6504 - logcount_predictions_loss: 0.2951
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2407/2407 [==============================] - ETA: 0s - loss: 330.5568 - logits_profile_predictions_loss: 325.8481 - logcount_predictions_loss: 0.2943
2407/2407 [==============================] - 1409s 586ms/step - loss: 330.5571 - logits_profile_predictions_loss: 325.8485 - logcount_predictions_loss: 0.2943 - val_loss: 382.5602 - val_logits_profile_predictions_loss: 372.5100 - val_logcount_predictions_loss: 0.6281
+
+Epoch 00011: val_loss did not improve from 379.67899
+Epoch 12/50
+
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2407/2407 [==============================] - 1410s 586ms/step - loss: 329.7876 - logits_profile_predictions_loss: 325.4322 - logcount_predictions_loss: 0.2722 - val_loss: 385.1347 - val_logits_profile_predictions_loss: 373.6760 - val_logcount_predictions_loss: 0.7162
+
+Epoch 00012: val_loss did not improve from 379.67899
+Restoring model weights from the end of the best epoch.
+Epoch 00012: early stopping
+save model
+save model without bias
+2022-03-24_18-52-05: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/predict.py \
+        --genome=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+        --bigwig=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/bigWigs/ENCSR372IGW.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        --chr_fold_path=/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json \
+        --inputlen=2114 \
+        --outputlen=1000 \
+        --output_prefix=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet.h5
+got the model
+loading peaks...
+got split:test for bed regions:(46309, 10)
+loading nonpeaks...
+got split:test for bed regions:(46308, 10)
+0/362
+100/362
+200/362
+300/362
+2022-03-24_19-00-55: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/predict.py \
+        --genome=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+        --bigwig=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/bigWigs/ENCSR372IGW.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        --chr_fold_path=/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json \
+        --inputlen=2114 \
+        --outputlen=1000 \
+        --output_prefix=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet_wo_bias \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet_wo_bias.h5 
+got the model
+loading peaks...
+got split:test for bed regions:(46309, 10)
+loading nonpeaks...
+got split:test for bed regions:(46308, 10)
+0/362
+100/362
+200/362
+300/362
+2022-03-24_19-08-48: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/predict.py \
+        --genome=/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+        --bigwig=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//preprocessing/bigWigs/ENCSR372IGW.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        --chr_fold_path=/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json \
+        --inputlen=2114 \
+        --outputlen=1000 \
+        --output_prefix=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//bias \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//bias_model_scaled.h5
+got the model
+loading peaks...
+got split:test for bed regions:(46309, 10)
+loading nonpeaks...
+got split:test for bed regions:(46308, 10)
+0/362
+100/362
+200/362
+300/362
+2022-03-24_19-12-34: mkdir /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//footprints
+2022-03-24_19-12-34: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/evaluation/marginal_footprints/marginal_footprinting.py \
+        -g /scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+        -r /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        -chr chr1 \
+        -m /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//chrombpnet_wo_bias.h5 \
+        -bs 512 \
+        -o /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//footprints/corrected \
+        -pwm_f src/evaluation/marginal_footprints/motif_to_pwm.tsv \
+        -mo tn5_1,tn5_2,tn5_3,tn5_4,tn5_5
+    MOTIF_NAME            MOTIF_PWM_FWD
+0        tn5_1         GCACAGTACAGAGCTG
+1        tn5_2  GTGCACAGTTCTAGAGTGTGCAG
+2        tn5_3       CCTCTACACTGTGCAGAA
+3        tn5_4    GCACAGTTCTAGACTGTGCAG
+4        tn5_5    CTGCACAGTGTAGAGTTGTGC
+5      dnase_1             TTTACAAGTCCA
+6      dnase_2             TGTACTTACGAA
+7         NRF1               GCGCATGCGC
+8          AP1         CGATATGACTCATCCC
+9         CTCF    TTGGCCACTAGGGGGCGCTAT
+10         ETS     CCGAAAGCGGAAGTGAGAC 
+11         SP1        AAGGGGGCGGGGCCTAA
+12        RUNX          CCCTAACCACAGCCC
+13        NFKB      GCAAGGGAAATTCCCCAGG
+14    GATA+TAL  GGCTGGGGGGGGCAGATAAGGCC
+15         TAL                  GGCTGGG
+16        NFYB          CCAGCCAATCAGAGC
+17       GABPA         GAAACCGGAAGTGGCC
+18  BACH1+MAFK       AACTGCTGAGTCATCCCG
+19        NRF1      CCCCGCGCATGCGCAGTGC
+20       HNF4G     CCGTTGGACTTTGGACCCTG
+got the model
+Model: "model_1"
+__________________________________________________________________________________________________
+Layer (type)                    Output Shape         Param #     Connected to                     
+==================================================================================================
+sequence (InputLayer)           [(None, 2114, 4)]    0                                            
+__________________________________________________________________________________________________
+wo_bias_bpnet_1st_conv (Conv1D) (None, 2094, 512)    43520       sequence[0][0]                   
+__________________________________________________________________________________________________
+wo_bias_bpnet_1conv (Conv1D)    (None, 2090, 512)    786944      wo_bias_bpnet_1st_conv[0][0]     
+__________________________________________________________________________________________________
+wo_bias_bpnet_1crop (Cropping1D (None, 2090, 512)    0           wo_bias_bpnet_1st_conv[0][0]     
+__________________________________________________________________________________________________
+add (Add)                       (None, 2090, 512)    0           wo_bias_bpnet_1conv[0][0]        
+                                                                 wo_bias_bpnet_1crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_2conv (Conv1D)    (None, 2082, 512)    786944      add[0][0]                        
+__________________________________________________________________________________________________
+wo_bias_bpnet_2crop (Cropping1D (None, 2082, 512)    0           add[0][0]                        
+__________________________________________________________________________________________________
+add_1 (Add)                     (None, 2082, 512)    0           wo_bias_bpnet_2conv[0][0]        
+                                                                 wo_bias_bpnet_2crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_3conv (Conv1D)    (None, 2066, 512)    786944      add_1[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_3crop (Cropping1D (None, 2066, 512)    0           add_1[0][0]                      
+__________________________________________________________________________________________________
+add_2 (Add)                     (None, 2066, 512)    0           wo_bias_bpnet_3conv[0][0]        
+                                                                 wo_bias_bpnet_3crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_4conv (Conv1D)    (None, 2034, 512)    786944      add_2[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_4crop (Cropping1D (None, 2034, 512)    0           add_2[0][0]                      
+__________________________________________________________________________________________________
+add_3 (Add)                     (None, 2034, 512)    0           wo_bias_bpnet_4conv[0][0]        
+                                                                 wo_bias_bpnet_4crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_5conv (Conv1D)    (None, 1970, 512)    786944      add_3[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_5crop (Cropping1D (None, 1970, 512)    0           add_3[0][0]                      
+__________________________________________________________________________________________________
+add_4 (Add)                     (None, 1970, 512)    0           wo_bias_bpnet_5conv[0][0]        
+                                                                 wo_bias_bpnet_5crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_6conv (Conv1D)    (None, 1842, 512)    786944      add_4[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_6crop (Cropping1D (None, 1842, 512)    0           add_4[0][0]                      
+__________________________________________________________________________________________________
+add_5 (Add)                     (None, 1842, 512)    0           wo_bias_bpnet_6conv[0][0]        
+                                                                 wo_bias_bpnet_6crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_7conv (Conv1D)    (None, 1586, 512)    786944      add_5[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_7crop (Cropping1D (None, 1586, 512)    0           add_5[0][0]                      
+__________________________________________________________________________________________________
+add_6 (Add)                     (None, 1586, 512)    0           wo_bias_bpnet_7conv[0][0]        
+                                                                 wo_bias_bpnet_7crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_8conv (Conv1D)    (None, 1074, 512)    786944      add_6[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_8crop (Cropping1D (None, 1074, 512)    0           add_6[0][0]                      
+__________________________________________________________________________________________________
+add_7 (Add)                     (None, 1074, 512)    0           wo_bias_bpnet_8conv[0][0]        
+                                                                 wo_bias_bpnet_8crop[0][0]        
+__________________________________________________________________________________________________
+wo_bias_bpnet_prof_out_precrop  (None, 1000, 1)      38401       add_7[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_logitt_before_fla (None, 1000, 1)      0           wo_bias_bpnet_prof_out_precrop[0]
+__________________________________________________________________________________________________
+gap (GlobalAveragePooling1D)    (None, 512)          0           add_7[0][0]                      
+__________________________________________________________________________________________________
+wo_bias_bpnet_logits_profile_pr (None, 1000)         0           wo_bias_bpnet_logitt_before_flatt
+__________________________________________________________________________________________________
+wo_bias_bpnet_logcount_predicti (None, 1)            513         gap[0][0]                        
+==================================================================================================
+Total params: 6,377,986
+Trainable params: 6,377,986
+Non-trainable params: 0
+__________________________________________________________________________________________________
+inferred model inputlen:  2114
+inferred model outputlen:  1000
+inserting motif:  tn5_1
+GCACAGTACAGAGCTG
+
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+
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+inserting motif:  tn5_2
+GTGCACAGTTCTAGAGTGTGCAG
+
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+
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+inserting motif:  tn5_3
+CCTCTACACTGTGCAGAA
+
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+
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+inserting motif:  tn5_4
+GCACAGTTCTAGACTGTGCAG
+
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+
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41/41 [==============================] - 65s 2s/step
+inserting motif:  tn5_5
+CTGCACAGTGTAGAGTTGTGC
+
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+
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+Saving marginal footprints
+2022-03-24_19-24-09: mkdir /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//footprints
+2022-03-24_19-24-09: python /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/evaluation/marginal_footprints/marginal_footprinting.py \
+        -g /scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa \
+        -r /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        -chr chr1 \
+        -m /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//bias_model_scaled.h5 \
+        -bs 512 \
+        -o /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR372IGW//chrombpnet_model_feb15//footprints/bias \
+        -pwm_f src/evaluation/marginal_footprints/motif_to_pwm.tsv \
+        -mo tn5_1,tn5_2,tn5_3,tn5_4,tn5_5
+    MOTIF_NAME            MOTIF_PWM_FWD
+0        tn5_1         GCACAGTACAGAGCTG
+1        tn5_2  GTGCACAGTTCTAGAGTGTGCAG
+2        tn5_3       CCTCTACACTGTGCAGAA
+3        tn5_4    GCACAGTTCTAGACTGTGCAG
+4        tn5_5    CTGCACAGTGTAGAGTTGTGC
+5      dnase_1             TTTACAAGTCCA
+6      dnase_2             TGTACTTACGAA
+7         NRF1               GCGCATGCGC
+8          AP1         CGATATGACTCATCCC
+9         CTCF    TTGGCCACTAGGGGGCGCTAT
+10         ETS     CCGAAAGCGGAAGTGAGAC 
+11         SP1        AAGGGGGCGGGGCCTAA
+12        RUNX          CCCTAACCACAGCCC
+13        NFKB      GCAAGGGAAATTCCCCAGG
+14    GATA+TAL  GGCTGGGGGGGGCAGATAAGGCC
+15         TAL                  GGCTGGG
+16        NFYB          CCAGCCAATCAGAGC
+17       GABPA         GAAACCGGAAGTGGCC
+18  BACH1+MAFK       AACTGCTGAGTCATCCCG
+19        NRF1      CCCCGCGCATGCGCAGTGC
+20       HNF4G     CCGTTGGACTTTGGACCCTG
+got the model
+Model: "functional_1"
+__________________________________________________________________________________________________
+Layer (type)                    Output Shape         Param #     Connected to                     
+==================================================================================================
+sequence (InputLayer)           [(None, 2114, 4)]    0                                            
+__________________________________________________________________________________________________
+bpnet_1st_conv (Conv1D)         (None, 2094, 128)    10880       sequence[0][0]                   
+__________________________________________________________________________________________________
+bpnet_1conv (Conv1D)            (None, 2090, 128)    49280       bpnet_1st_conv[0][0]             
+__________________________________________________________________________________________________
+bpnet_1crop (Cropping1D)        (None, 2090, 128)    0           bpnet_1st_conv[0][0]             
+__________________________________________________________________________________________________
+add (Add)                       (None, 2090, 128)    0           bpnet_1conv[0][0]                
+                                                                 bpnet_1crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_2conv (Conv1D)            (None, 2082, 128)    49280       add[0][0]                        
+__________________________________________________________________________________________________
+bpnet_2crop (Cropping1D)        (None, 2082, 128)    0           add[0][0]                        
+__________________________________________________________________________________________________
+add_1 (Add)                     (None, 2082, 128)    0           bpnet_2conv[0][0]                
+                                                                 bpnet_2crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_3conv (Conv1D)            (None, 2066, 128)    49280       add_1[0][0]                      
+__________________________________________________________________________________________________
+bpnet_3crop (Cropping1D)        (None, 2066, 128)    0           add_1[0][0]                      
+__________________________________________________________________________________________________
+add_2 (Add)                     (None, 2066, 128)    0           bpnet_3conv[0][0]                
+                                                                 bpnet_3crop[0][0]                
+__________________________________________________________________________________________________
+bpnet_4conv (Conv1D)            (None, 2034, 128)    49280       add_2[0][0]                      
+__________________________________________________________________________________________________
+bpnet_4crop (Cropping1D)        (None, 2034, 128)    0           add_2[0][0]                      
+__________________________________________________________________________________________________
+add_3 (Add)                     (None, 2034, 128)    0           bpnet_4conv[0][0]                
+                                                                 bpnet_4crop[0][0]                
+__________________________________________________________________________________________________
+prof_out_precrop (Conv1D)       (None, 1960, 1)      9601        add_3[0][0]                      
+__________________________________________________________________________________________________
+logits_profile_predictions_pref (None, 1000, 1)      0           prof_out_precrop[0][0]           
+__________________________________________________________________________________________________
+gap (GlobalAveragePooling1D)    (None, 128)          0           add_3[0][0]                      
+__________________________________________________________________________________________________
+logits_profile_predictions (Fla (None, 1000)         0           logits_profile_predictions_prefla
+__________________________________________________________________________________________________
+logcount_predictions (Dense)    (None, 1)            129         gap[0][0]                        
+==================================================================================================
+Total params: 217,730
+Trainable params: 217,730
+Non-trainable params: 0
+__________________________________________________________________________________________________
+inferred model inputlen:  2114
+inferred model outputlen:  1000
+inserting motif:  tn5_1
+GCACAGTACAGAGCTG
+
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+inserting motif:  tn5_2
+GTGCACAGTTCTAGAGTGTGCAG
+
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+
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+inserting motif:  tn5_3
+CCTCTACACTGTGCAGAA
+
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+
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41/41 [==============================] - ETA: 0s
41/41 [==============================] - 5s 128ms/step
+inserting motif:  tn5_4
+GCACAGTTCTAGACTGTGCAG
+
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41/41 [==============================] - ETA: 0s
41/41 [==============================] - 5s 128ms/step
+
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39/41 [===========================>..] - ETA: 0s
40/41 [============================>.] - ETA: 0s
41/41 [==============================] - ETA: 0s
41/41 [==============================] - 5s 128ms/step
+inserting motif:  tn5_5
+CTGCACAGTGTAGAGTTGTGC
+
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39/41 [===========================>..] - ETA: 0s
40/41 [============================>.] - ETA: 0s
41/41 [==============================] - ETA: 0s
41/41 [==============================] - 5s 128ms/step
+
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40/41 [============================>.] - ETA: 0s
41/41 [==============================] - ETA: 0s
41/41 [==============================] - 5s 128ms/step
+Saving marginal footprints