diff --git "a/fold_0/logs.models.fold_0.ENCSR775KMA/logfile.modelling.fold_0.ENCSR775KMA.stdout_v1.txt" "b/fold_0/logs.models.fold_0.ENCSR775KMA/logfile.modelling.fold_0.ENCSR775KMA.stdout_v1.txt"
new file mode 100644--- /dev/null
+++ "b/fold_0/logs.models.fold_0.ENCSR775KMA/logfile.modelling.fold_0.ENCSR775KMA.stdout_v1.txt"
@@ -0,0 +1,462 @@
+2022-02-15_19-40-02: 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/ENCSR775KMA//preprocessing/bigWigs/ENCSR775KMA.bigWig \
+       --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//preprocessing/downloads/peaks.bed.gz \
+       --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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/ENCSR775KMA//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:  78000
+Number of peaks filtered because the input/output is on the edge:  0
+Number of peaks being used:  78000
+Number of peaks input:  21952
+Number of peaks filtered because the input/output is on the edge:  0
+Number of peaks being used:  21952
+Number of non peaks input:  78000
+Number of non peaks filtered because the input/output is on the edge:  0
+Number of non peaks being used:  78000
+Number of non peaks input:  21951
+Number of non peaks filtered because the input/output is on the edge:  0
+Number of non peaks being used:  21951
+Number of peaks after removing outliers:  77140
+Number of nonpeaks after removing outliers:  68631
+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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+2022-02-15_19-43-21: 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/ENCSR775KMA//preprocessing/bigWigs/ENCSR775KMA.bigWig \
+       --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//filtered.peaks.bed \
+       --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+       --params=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet_model_params.tsv \
+       --output_prefix=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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': '11.9', 'filters': '512', 'n_dil_layers': '8', 'bias_model_path': '/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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:(70621, 10)
+loading nonpeaks...
+got split:train for bed regions:(62717, 10)
+loading peaks...
+got split:valid for bed regions:(6519, 10)
+loading nonpeaks...
+got split:valid for bed regions:(5914, 10)
+Epoch 1/50
+
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1212/1214 [============================>.] - ETA: 0s - loss: 530.7694 - logits_profile_predictions_loss: 354.7925 - logcount_predictions_loss: 14.7880
1213/1214 [============================>.] - ETA: 0s - loss: 530.6527 - logits_profile_predictions_loss: 354.7859 - logcount_predictions_loss: 14.7787
1214/1214 [==============================] - ETA: 0s - loss: 530.5362 - logits_profile_predictions_loss: 354.7794 - logcount_predictions_loss: 14.7695
1214/1214 [==============================] - 206s 162ms/step - loss: 530.4199 - logits_profile_predictions_loss: 354.7728 - logcount_predictions_loss: 14.7603 - val_loss: 355.4843 - val_logits_profile_predictions_loss: 344.7894 - val_logcount_predictions_loss: 0.8987
+
+Epoch 00001: val_loss improved from inf to 355.48431, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 2/50
+
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1208/1214 [============================>.] - ETA: 0s - loss: 342.6673 - logits_profile_predictions_loss: 330.9783 - logcount_predictions_loss: 0.9823
1209/1214 [============================>.] - ETA: 0s - loss: 342.6617 - logits_profile_predictions_loss: 330.9731 - logcount_predictions_loss: 0.9822
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1212/1214 [============================>.] - ETA: 0s - loss: 342.6449 - logits_profile_predictions_loss: 330.9573 - logcount_predictions_loss: 0.9821
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1214/1214 [==============================] - ETA: 0s - loss: 342.6337 - logits_profile_predictions_loss: 330.9469 - logcount_predictions_loss: 0.9821
1214/1214 [==============================] - 194s 160ms/step - loss: 342.6281 - logits_profile_predictions_loss: 330.9416 - logcount_predictions_loss: 0.9821 - val_loss: 340.7029 - val_logits_profile_predictions_loss: 331.2177 - val_logcount_predictions_loss: 0.7971
+
+Epoch 00002: val_loss improved from 355.48431 to 340.70288, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 3/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 325.6556 - logits_profile_predictions_loss: 315.0557 - logcount_predictions_loss: 0.8907
1214/1214 [==============================] - 194s 160ms/step - loss: 325.6552 - logits_profile_predictions_loss: 315.0555 - logcount_predictions_loss: 0.8907 - val_loss: 336.6872 - val_logits_profile_predictions_loss: 327.4124 - val_logcount_predictions_loss: 0.7794
+
+Epoch 00003: val_loss improved from 340.70288 to 336.68719, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 4/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 318.9579 - logits_profile_predictions_loss: 309.3436 - logcount_predictions_loss: 0.8079
1214/1214 [==============================] - 194s 159ms/step - loss: 318.9582 - logits_profile_predictions_loss: 309.3440 - logcount_predictions_loss: 0.8079 - val_loss: 333.5605 - val_logits_profile_predictions_loss: 324.4782 - val_logcount_predictions_loss: 0.7632
+
+Epoch 00004: val_loss improved from 336.68719 to 333.56052, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 5/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 314.4442 - logits_profile_predictions_loss: 305.2580 - logcount_predictions_loss: 0.7720
1214/1214 [==============================] - 194s 160ms/step - loss: 314.4448 - logits_profile_predictions_loss: 305.2588 - logcount_predictions_loss: 0.7719 - val_loss: 330.3925 - val_logits_profile_predictions_loss: 322.1917 - val_logcount_predictions_loss: 0.6891
+
+Epoch 00005: val_loss improved from 333.56052 to 330.39252, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 6/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 312.1839 - logits_profile_predictions_loss: 303.3783 - logcount_predictions_loss: 0.7400
1214/1214 [==============================] - 194s 160ms/step - loss: 312.1831 - logits_profile_predictions_loss: 303.3776 - logcount_predictions_loss: 0.7399 - val_loss: 328.8000 - val_logits_profile_predictions_loss: 320.9679 - val_logcount_predictions_loss: 0.6582
+
+Epoch 00006: val_loss improved from 330.39252 to 328.79996, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 7/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 306.9343 - logits_profile_predictions_loss: 298.5294 - logcount_predictions_loss: 0.7063
1214/1214 [==============================] - 194s 159ms/step - loss: 306.9350 - logits_profile_predictions_loss: 298.5303 - logcount_predictions_loss: 0.7063 - val_loss: 330.7902 - val_logits_profile_predictions_loss: 322.7734 - val_logcount_predictions_loss: 0.6737
+
+Epoch 00007: val_loss did not improve from 328.79996
+Epoch 8/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 303.7782 - logits_profile_predictions_loss: 295.8555 - logcount_predictions_loss: 0.6658
1214/1214 [==============================] - 194s 160ms/step - loss: 303.7783 - logits_profile_predictions_loss: 295.8556 - logcount_predictions_loss: 0.6658 - val_loss: 328.8490 - val_logits_profile_predictions_loss: 321.0135 - val_logcount_predictions_loss: 0.6585
+
+Epoch 00008: val_loss did not improve from 328.79996
+Epoch 9/50
+
   1/1214 [..............................] - ETA: 3:45 - loss: 313.8264 - logits_profile_predictions_loss: 305.0468 - logcount_predictions_loss: 0.7378
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1204/1214 [============================>.] - ETA: 1s - loss: 301.9614 - logits_profile_predictions_loss: 294.2446 - logcount_predictions_loss: 0.6485
1205/1214 [============================>.] - ETA: 1s - loss: 301.9611 - logits_profile_predictions_loss: 294.2444 - logcount_predictions_loss: 0.6485
1206/1214 [============================>.] - ETA: 1s - loss: 301.9609 - logits_profile_predictions_loss: 294.2442 - logcount_predictions_loss: 0.6485
1207/1214 [============================>.] - ETA: 1s - loss: 301.9606 - logits_profile_predictions_loss: 294.2440 - logcount_predictions_loss: 0.6485
1208/1214 [============================>.] - ETA: 0s - loss: 301.9603 - logits_profile_predictions_loss: 294.2439 - logcount_predictions_loss: 0.6484
1209/1214 [============================>.] - ETA: 0s - loss: 301.9601 - logits_profile_predictions_loss: 294.2437 - logcount_predictions_loss: 0.6484
1210/1214 [============================>.] - ETA: 0s - loss: 301.9599 - logits_profile_predictions_loss: 294.2436 - logcount_predictions_loss: 0.6484
1211/1214 [============================>.] - ETA: 0s - loss: 301.9596 - logits_profile_predictions_loss: 294.2435 - logcount_predictions_loss: 0.6484
1212/1214 [============================>.] - ETA: 0s - loss: 301.9594 - logits_profile_predictions_loss: 294.2433 - logcount_predictions_loss: 0.6484
1213/1214 [============================>.] - ETA: 0s - loss: 301.9592 - logits_profile_predictions_loss: 294.2432 - logcount_predictions_loss: 0.6484
1214/1214 [==============================] - ETA: 0s - loss: 301.9590 - logits_profile_predictions_loss: 294.2431 - logcount_predictions_loss: 0.6484
1214/1214 [==============================] - 194s 160ms/step - loss: 301.9588 - logits_profile_predictions_loss: 294.2430 - logcount_predictions_loss: 0.6484 - val_loss: 330.1174 - val_logits_profile_predictions_loss: 322.1743 - val_logcount_predictions_loss: 0.6675
+
+Epoch 00009: val_loss did not improve from 328.79996
+Epoch 10/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 294.6553 - logits_profile_predictions_loss: 287.9057 - logcount_predictions_loss: 0.5672
1214/1214 [==============================] - 194s 160ms/step - loss: 294.6545 - logits_profile_predictions_loss: 287.9050 - logcount_predictions_loss: 0.5672 - val_loss: 328.1320 - val_logits_profile_predictions_loss: 320.4731 - val_logcount_predictions_loss: 0.6436
+
+Epoch 00010: val_loss improved from 328.79996 to 328.13199, saving model to /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15/chrombpnet.h5
+Epoch 11/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 289.4563 - logits_profile_predictions_loss: 283.2530 - logcount_predictions_loss: 0.5213
1214/1214 [==============================] - 194s 160ms/step - loss: 289.4566 - logits_profile_predictions_loss: 283.2533 - logcount_predictions_loss: 0.5213 - val_loss: 331.0307 - val_logits_profile_predictions_loss: 322.2111 - val_logcount_predictions_loss: 0.7411
+
+Epoch 00011: val_loss did not improve from 328.13199
+Epoch 12/50
+
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1208/1214 [============================>.] - ETA: 0s - loss: 285.9026 - logits_profile_predictions_loss: 280.1238 - logcount_predictions_loss: 0.4856
1209/1214 [============================>.] - ETA: 0s - loss: 285.9030 - logits_profile_predictions_loss: 280.1242 - logcount_predictions_loss: 0.4856
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1213/1214 [============================>.] - ETA: 0s - loss: 285.9045 - logits_profile_predictions_loss: 280.1259 - logcount_predictions_loss: 0.4856
1214/1214 [==============================] - ETA: 0s - loss: 285.9048 - logits_profile_predictions_loss: 280.1263 - logcount_predictions_loss: 0.4856
1214/1214 [==============================] - 194s 160ms/step - loss: 285.9052 - logits_profile_predictions_loss: 280.1267 - logcount_predictions_loss: 0.4856 - val_loss: 330.2439 - val_logits_profile_predictions_loss: 322.3008 - val_logcount_predictions_loss: 0.6675
+
+Epoch 00012: val_loss did not improve from 328.13199
+Epoch 13/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 283.6308 - logits_profile_predictions_loss: 278.2318 - logcount_predictions_loss: 0.4537
1214/1214 [==============================] - 194s 160ms/step - loss: 283.6304 - logits_profile_predictions_loss: 278.2314 - logcount_predictions_loss: 0.4537 - val_loss: 332.2378 - val_logits_profile_predictions_loss: 324.2818 - val_logcount_predictions_loss: 0.6686
+
+Epoch 00013: val_loss did not improve from 328.13199
+Epoch 14/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 278.9360 - logits_profile_predictions_loss: 274.2679 - logcount_predictions_loss: 0.3923
1214/1214 [==============================] - 194s 160ms/step - loss: 278.9360 - logits_profile_predictions_loss: 274.2679 - logcount_predictions_loss: 0.3923 - val_loss: 332.5148 - val_logits_profile_predictions_loss: 324.6239 - val_logcount_predictions_loss: 0.6631
+
+Epoch 00014: val_loss did not improve from 328.13199
+Epoch 15/50
+
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1214/1214 [==============================] - ETA: 0s - loss: 277.1101 - logits_profile_predictions_loss: 272.7800 - logcount_predictions_loss: 0.3639
1214/1214 [==============================] - 194s 160ms/step - loss: 277.1090 - logits_profile_predictions_loss: 272.7789 - logcount_predictions_loss: 0.3639 - val_loss: 333.7732 - val_logits_profile_predictions_loss: 325.8232 - val_logcount_predictions_loss: 0.6681
+
+Epoch 00015: val_loss did not improve from 328.13199
+Restoring model weights from the end of the best epoch.
+Epoch 00015: early stopping
+save model
+save model without bias
+2022-02-15_20-36-45: 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/ENCSR775KMA//preprocessing/bigWigs/ENCSR775KMA.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet.h5
+got the model
+loading peaks...
+got split:test for bed regions:(21952, 10)
+loading nonpeaks...
+got split:test for bed regions:(21951, 10)
+0/172
+100/172
+2022-02-15_20-39-17: 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/ENCSR775KMA//preprocessing/bigWigs/ENCSR775KMA.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet_wo_bias \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet_wo_bias.h5 
+got the model
+loading peaks...
+got split:test for bed regions:(21952, 10)
+loading nonpeaks...
+got split:test for bed regions:(21951, 10)
+0/172
+100/172
+2022-02-15_20-41-38: 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/ENCSR775KMA//preprocessing/bigWigs/ENCSR775KMA.bigWig \
+        --peaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//filtered.peaks.bed \
+        --nonpeaks=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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/ENCSR775KMA//chrombpnet_model_feb15//bias \
+        --batch_size=256 \
+        --model_h5=/scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//bias_model_scaled.h5
+got the model
+loading peaks...
+got split:test for bed regions:(21952, 10)
+loading nonpeaks...
+got split:test for bed regions:(21951, 10)
+0/172
+100/172
+2022-02-15_20-43-26: mkdir /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//footprints
+2022-02-15_20-43-26: 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/ENCSR775KMA//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        -chr chr1 \
+        -m /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//chrombpnet_wo_bias.h5 \
+        -bs 512 \
+        -o /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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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+inserting motif:  tn5_5
+CTGCACAGTGTAGAGTTGTGC
+
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+
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22/22 [==============================] - 14s 675ms/step
+Saving marginal footprints
+2022-02-15_20-46-18: mkdir /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//footprints
+2022-02-15_20-46-19: 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/ENCSR775KMA//chrombpnet_model_feb15//filtered.nonpeaks.bed \
+        -chr chr1 \
+        -m /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//chrombpnet_model_feb15//bias_model_scaled.h5 \
+        -bs 512 \
+        -o /scratch/groups/akundaje/anusri/chromatin_atlas/ATAC/ENCSR775KMA//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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22/22 [==============================] - 6s 78ms/step
+
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22/22 [==============================] - 1s 59ms/step
+inserting motif:  tn5_2
+GTGCACAGTTCTAGAGTGTGCAG
+
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22/22 [==============================] - 1s 60ms/step
+
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22/22 [==============================] - 1s 59ms/step
+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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+inserting motif:  tn5_5
+CTGCACAGTGTAGAGTTGTGC
+
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+
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+Saving marginal footprints