Hugging Face's logo

kundajelab
/
encode-chrombpnet-DNASE-right-cardiac-atrium-ENCSR622HTS-ENCSR193CJS

chrombpnet
encode
chromatin-accessibility
DNASE
atrium
hg38
Model card Files
xet
 Community
chang-m-yun commited on
Commit
22926d1
·
verified ·
1 Parent(s): c036c12

Add files using upload-large-folder tool

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +10 -0
  2. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.args.json +23 -0
  3. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.batch_loss.tsv +0 -0
  4. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.bias_formatting.stderr.txt +38 -0
  5. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.bias_formatting.stdout.txt +1 -0
  6. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet.params.json +11 -0
  7. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_data_params.tsv +3 -0
  8. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_formatting.stderr.txt +40 -0
  9. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_formatting.stdout.txt +1 -0
  10. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_model_params.tsv +9 -0
  11. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  12. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  13. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.epoch_loss.csv +20 -0
  14. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stderr.txt +328 -0
  15. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout.txt +3 -0
  16. fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout_v1.txt +3 -0
  17. fold_0/model.bias_scaled.fold_0.ENCSR622HTS.h5 +3 -0
  18. fold_0/model.bias_scaled.fold_0.ENCSR622HTS.tar +3 -0
  19. fold_0/model.chrombpnet.fold_0.ENCSR622HTS.h5 +3 -0
  20. fold_0/model.chrombpnet.fold_0.ENCSR622HTS.tar +3 -0
  21. fold_0/model.chrombpnet_nobias.fold_0.ENCSR622HTS.h5 +3 -0
  22. fold_0/model.chrombpnet_nobias.fold_0.ENCSR622HTS.tar +3 -0
  23. fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout.txt +3 -0
  24. fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout_v1.txt +3 -0
  25. fold_1/model.bias_scaled.fold_1.ENCSR622HTS.h5 +3 -0
  26. fold_1/model.bias_scaled.fold_1.ENCSR622HTS.tar +3 -0
  27. fold_1/model.chrombpnet.fold_1.ENCSR622HTS.h5 +3 -0
  28. fold_1/model.chrombpnet.fold_1.ENCSR622HTS.tar +3 -0
  29. fold_1/model.chrombpnet_nobias.fold_1.ENCSR622HTS.h5 +3 -0
  30. fold_1/model.chrombpnet_nobias.fold_1.ENCSR622HTS.tar +3 -0
  31. fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.args.json +23 -0
  32. fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  34. fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout.txt +3 -0
  35. fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout_v1.txt +3 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR622HTS.h5 +3 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR622HTS.tar +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR622HTS.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR622HTS.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR622HTS.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR622HTS.tar +3 -0
  42. fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout.txt +3 -0
  43. fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout_v1.txt +3 -0
  44. fold_3/model.bias_scaled.fold_3.ENCSR622HTS.h5 +3 -0
  45. fold_3/model.bias_scaled.fold_3.ENCSR622HTS.tar +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR622HTS.h5 +3 -0
  47. fold_3/model.chrombpnet.fold_3.ENCSR622HTS.tar +3 -0
  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR622HTS.h5 +3 -0
  49. fold_3/model.chrombpnet_nobias.fold_3.ENCSR622HTS.tar +3 -0
  50. fold_4/logs.models.fold_4.ENCSR622HTS/logfile.modelling.fold_4.ENCSR622HTS.stdout.txt +3 -0
.gitattributes CHANGED
@@ -33,3 +33,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout.txt filter=lfs diff=lfs merge=lfs -text
37
+ fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout.txt filter=lfs diff=lfs merge=lfs -text
38
+ fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
39
+ fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
40
+ fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout.txt filter=lfs diff=lfs merge=lfs -text
41
+ fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
42
+ fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout.txt filter=lfs diff=lfs merge=lfs -text
43
+ fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
44
+ fold_4/logs.models.fold_4.ENCSR622HTS/logfile.modelling.fold_4.ENCSR622HTS.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
45
+ fold_4/logs.models.fold_4.ENCSR622HTS/logfile.modelling.fold_4.ENCSR622HTS.stdout.txt filter=lfs diff=lfs merge=lfs -text
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.args.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
3
+ "bigwig": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//preprocessing/bigWigs/ENCSR622HTS.bigWig",
4
+ "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias//filtered.peaks.bed",
5
+ "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias//filtered.nonpeaks.bed",
6
+ "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias//chrombpnet",
7
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
8
+ "trackables": [
9
+ "logcount_predictions_loss",
10
+ "loss",
11
+ "logits_profile_predictions_loss",
12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
15
+ ],
16
+ "epochs": 50,
17
+ "early_stop": 5,
18
+ "batch_size": 64,
19
+ "learning_rate": 0.001,
20
+ "params": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias//chrombpnet_model_params.tsv",
21
+ "seed": 1234,
22
+ "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
+ }
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 02:24:33.880227: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 02:24:36.819198: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-15 02:24:36.824628: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-15 02:24:36.859973: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
8
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
9
+ 2023-07-15 02:24:36.860055: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 02:24:36.889101: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-15 02:24:36.889169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-15 02:24:36.903043: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-15 02:24:36.909159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 02:24:36.931691: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 02:24:36.937090: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 02:24:36.938242: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 02:24:36.947923: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 02:24:36.948290: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 02:24:36.949156: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 02:24:36.949415: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
24
+ 2023-07-15 02:24:36.949446: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 02:24:36.949472: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-15 02:24:36.949494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-15 02:24:36.949516: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 02:24:36.949537: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 02:24:36.949559: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-15 02:24:36.949580: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-15 02:24:36.949602: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-15 02:24:36.949976: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 02:24:36.951318: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 02:24:38.745722: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 02:24:38.745822: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 02:24:38.745840: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 02:24:38.748812: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14957 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:83:00.0, compute capability: 6.0)
38
+ 2023-07-15 02:24:39.592142: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/new_model_formats/bias_model_scaled
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "20.6",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5",
6
+ "inputlen": "2114",
7
+ "outputlen": "1000",
8
+ "max_jitter": "500",
9
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 4.0
2
+ counts_sum_max_thresh 6362.48
3
+ trainings_pts_post_thresh 170760
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 01:20:13.762982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 01:20:16.161236: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-15 01:20:16.165012: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-15 01:20:17.338218: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-15 01:20:17.338319: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 01:20:17.356578: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-15 01:20:17.356717: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-15 01:20:17.366275: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-15 01:20:17.370966: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 01:20:17.386646: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 01:20:17.390789: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 01:20:17.391698: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 01:20:17.406819: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 01:20:17.407207: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 01:20:17.408398: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 01:20:17.430084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-15 01:20:17.430114: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 01:20:17.430134: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-15 01:20:17.430149: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-15 01:20:17.430163: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 01:20:17.430176: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 01:20:17.430188: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-15 01:20:17.430200: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-15 01:20:17.430213: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-15 01:20:17.472546: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 01:20:17.473865: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 01:20:19.777216: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 01:20:19.777387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 01:20:19.777400: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 01:20:19.871282: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:07:00.0, compute capability: 8.0)
38
+ 2023-07-15 01:20:22.279934: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
39
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
40
+ , UserWarning)
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 20.6
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5
5
+ inputlen 2114
6
+ outputlen 1000
7
+ max_jitter 500
8
+ chr_fold_path /scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json
9
+ negative_sampling_ratio 0.1
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_no_bias_formatting.stderr.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.chrombpnet_no_bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.epoch_loss.csv ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,3.007693290710449,842.727783203125,904.6864013671875,0.8334112763404846,786.574462890625,803.74267578125
3
+ 1,0.8227980136871338,778.1151123046875,795.0650024414062,0.7304946184158325,764.9931030273438,780.0409545898438
4
+ 2,0.7502110004425049,761.330810546875,776.7850952148438,0.6677016615867615,750.3544311523438,764.109619140625
5
+ 3,0.7048489451408386,752.5178833007812,767.038330078125,0.6758238673210144,752.1743774414062,766.0961303710938
6
+ 4,0.6693955063819885,745.4822387695312,759.2711791992188,0.6246047616004944,748.4168090820312,761.283935546875
7
+ 5,0.6376872062683105,738.2029418945312,751.3397827148438,0.562009871006012,747.6002197265625,759.1774291992188
8
+ 6,0.6143935322761536,733.5409545898438,746.1971435546875,0.6088924407958984,739.8034057617188,752.3462524414062
9
+ 7,0.5954197645187378,730.1849365234375,742.4503173828125,0.6120826601982117,744.8975830078125,757.506591796875
10
+ 8,0.5821287631988525,725.0712890625,737.0619506835938,0.5537213087081909,745.1658325195312,756.5720825195312
11
+ 9,0.5632614493370056,721.4506225585938,733.0538940429688,0.5547593832015991,737.7760009765625,749.2039794921875
12
+ 10,0.5501141548156738,720.0061645507812,731.3387451171875,0.5491799712181091,740.6593627929688,751.9721069335938
13
+ 11,0.5430052280426025,717.202880859375,728.38916015625,0.5680010318756104,745.7555541992188,757.4566040039062
14
+ 12,0.5235801339149475,713.8707885742188,724.6550903320312,0.5688911080360413,746.2537841796875,757.9725341796875
15
+ 13,0.48242977261543274,701.0297241210938,710.9675903320312,0.5226465463638306,737.020751953125,747.7872924804688
16
+ 14,0.46213996410369873,693.9562377929688,703.4769897460938,0.5214941501617432,742.6201782226562,753.3624877929688
17
+ 15,0.44867628812789917,688.89794921875,698.1398315429688,0.5970543026924133,741.0379028320312,753.337646484375
18
+ 16,0.4337303340435028,686.6624755859375,695.5971069335938,0.5259267687797546,743.0822143554688,753.9161376953125
19
+ 17,0.41040557622909546,678.6127319335938,687.066162109375,0.5241705179214478,744.9776000976562,755.7755126953125
20
+ 18,0.39812371134757996,674.9517822265625,683.1533203125,0.5378451943397522,746.9336547851562,758.0137329101562
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stderr.txt ADDED
@@ -0,0 +1,328 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-03-23 18:48:46.332785: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2
+ 2022-03-23 18:54:26.441283: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
3
+ 2022-03-23 18:54:26.443582: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
4
+ 2022-03-23 18:54:26.902258: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
5
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
6
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
7
+ 2022-03-23 18:54:26.902385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
8
+ 2022-03-23 18:54:26.927469: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
9
+ 2022-03-23 18:54:26.927640: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
10
+ 2022-03-23 18:54:26.941457: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
11
+ 2022-03-23 18:54:26.947728: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
12
+ 2022-03-23 18:54:26.969724: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
13
+ 2022-03-23 18:54:26.976065: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
14
+ 2022-03-23 18:54:26.977525: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
15
+ 2022-03-23 18:54:26.983810: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
16
+ 2022-03-23 18:54:26.984181: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
17
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
18
+ 2022-03-23 18:54:26.984261: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
19
+ 2022-03-23 18:54:26.986603: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
20
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
21
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
22
+ 2022-03-23 18:54:26.986634: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
23
+ 2022-03-23 18:54:26.986655: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
24
+ 2022-03-23 18:54:26.986671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
25
+ 2022-03-23 18:54:26.986686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
26
+ 2022-03-23 18:54:26.986699: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
27
+ 2022-03-23 18:54:26.986713: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
28
+ 2022-03-23 18:54:26.986726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
29
+ 2022-03-23 18:54:26.986740: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
30
+ 2022-03-23 18:54:26.991742: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
31
+ 2022-03-23 18:54:26.993380: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
32
+ 2022-03-23 18:54:28.743934: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
33
+ 2022-03-23 18:54:28.744061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
34
+ 2022-03-23 18:54:28.744073: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
35
+ 2022-03-23 18:54:28.753021: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
36
+ 2022-03-23 18:54:30.024677: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
37
+ 2022-03-23 18:54:30.033695: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
38
+ 2022-03-23 18:54:30.220359: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
39
+ 2022-03-23 18:54:31.863279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
40
+ 2022-03-23 18:54:31.872794: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
41
+ 2022-03-23 18:55:04.102723: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
42
+ 2022-03-23 18:55:05.777406: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
43
+ 2022-03-23 18:55:05.778444: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
44
+ 2022-03-23 18:55:06.077808: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
45
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
46
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
47
+ 2022-03-23 18:55:06.077952: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
48
+ 2022-03-23 18:55:06.080067: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
49
+ 2022-03-23 18:55:06.080128: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
50
+ 2022-03-23 18:55:06.081100: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
51
+ 2022-03-23 18:55:06.081281: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
52
+ 2022-03-23 18:55:06.083477: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
53
+ 2022-03-23 18:55:06.083986: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
54
+ 2022-03-23 18:55:06.084115: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
55
+ 2022-03-23 18:55:06.086846: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
56
+ 2022-03-23 18:55:06.087176: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
57
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
58
+ 2022-03-23 18:55:06.087254: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
59
+ 2022-03-23 18:55:06.088586: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
60
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
61
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
62
+ 2022-03-23 18:55:06.088634: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
63
+ 2022-03-23 18:55:06.088653: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
64
+ 2022-03-23 18:55:06.088667: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
65
+ 2022-03-23 18:55:06.088680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
66
+ 2022-03-23 18:55:06.088693: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
67
+ 2022-03-23 18:55:06.088707: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
68
+ 2022-03-23 18:55:06.088720: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
69
+ 2022-03-23 18:55:06.088733: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
70
+ 2022-03-23 18:55:06.091302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
71
+ 2022-03-23 18:55:06.091339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
72
+ 2022-03-23 18:55:06.591334: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
73
+ 2022-03-23 18:55:06.591470: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
74
+ 2022-03-23 18:55:06.591481: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
75
+ 2022-03-23 18:55:06.595870: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
76
+ 2022-03-23 19:00:20.268691: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
77
+ 2022-03-23 19:00:20.269189: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
78
+ 2022-03-23 19:00:21.754767: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
79
+ 2022-03-23 19:00:22.275985: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
80
+ 2022-03-23 19:00:22.323458: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
81
+ 2022-03-23 19:00:25.359376: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
82
+ 2022-03-23 21:07:22.979769: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
83
+ 2022-03-23 21:07:25.617893: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
84
+ 2022-03-23 21:07:25.618951: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
85
+ 2022-03-23 21:07:26.050314: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
86
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
87
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
88
+ 2022-03-23 21:07:26.050441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
89
+ 2022-03-23 21:07:26.052536: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
90
+ 2022-03-23 21:07:26.052606: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
91
+ 2022-03-23 21:07:26.053582: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
92
+ 2022-03-23 21:07:26.053766: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
93
+ 2022-03-23 21:07:26.055865: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
94
+ 2022-03-23 21:07:26.056343: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
95
+ 2022-03-23 21:07:26.056474: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
96
+ 2022-03-23 21:07:26.060726: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
97
+ 2022-03-23 21:07:26.061099: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
98
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
99
+ 2022-03-23 21:07:26.061188: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
100
+ 2022-03-23 21:07:26.063333: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
101
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
102
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
103
+ 2022-03-23 21:07:26.063366: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
104
+ 2022-03-23 21:07:26.063397: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
105
+ 2022-03-23 21:07:26.063413: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
106
+ 2022-03-23 21:07:26.063428: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
107
+ 2022-03-23 21:07:26.063443: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
108
+ 2022-03-23 21:07:26.063457: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
109
+ 2022-03-23 21:07:26.063470: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
110
+ 2022-03-23 21:07:26.063485: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
111
+ 2022-03-23 21:07:26.067511: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
112
+ 2022-03-23 21:07:26.067546: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
113
+ 2022-03-23 21:07:26.580938: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
114
+ 2022-03-23 21:07:26.581074: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
115
+ 2022-03-23 21:07:26.581086: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
116
+ 2022-03-23 21:07:26.586185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
117
+ 2022-03-23 21:08:55.485267: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
118
+ 2022-03-23 21:08:55.488902: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
119
+ 2022-03-23 21:08:55.577220: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
120
+ 2022-03-23 21:08:56.103418: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
121
+ 2022-03-23 21:08:56.105976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
122
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
123
+ , UserWarning)
124
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
125
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
126
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
127
+ profile_prob = profile / np.sum(profile)
128
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
129
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
130
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
131
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
132
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
133
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
134
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
135
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
136
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
137
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
138
+ 2022-03-23 21:11:25.448003: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
139
+ 2022-03-23 21:11:27.864976: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
140
+ 2022-03-23 21:11:27.866050: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
141
+ 2022-03-23 21:11:28.170967: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
142
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
143
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
144
+ 2022-03-23 21:11:28.171091: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
145
+ 2022-03-23 21:11:28.173178: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
146
+ 2022-03-23 21:11:28.173240: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
147
+ 2022-03-23 21:11:28.174183: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
148
+ 2022-03-23 21:11:28.174358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
149
+ 2022-03-23 21:11:28.176501: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
150
+ 2022-03-23 21:11:28.176979: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
151
+ 2022-03-23 21:11:28.177115: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
152
+ 2022-03-23 21:11:28.180344: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
153
+ 2022-03-23 21:11:28.180678: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
154
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
155
+ 2022-03-23 21:11:28.180781: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
156
+ 2022-03-23 21:11:28.182403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
157
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
158
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
159
+ 2022-03-23 21:11:28.182428: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
160
+ 2022-03-23 21:11:28.182446: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
161
+ 2022-03-23 21:11:28.182460: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
162
+ 2022-03-23 21:11:28.182474: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
163
+ 2022-03-23 21:11:28.182487: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
164
+ 2022-03-23 21:11:28.182508: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
165
+ 2022-03-23 21:11:28.182521: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
166
+ 2022-03-23 21:11:28.182534: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
167
+ 2022-03-23 21:11:28.185579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
168
+ 2022-03-23 21:11:28.185609: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
169
+ 2022-03-23 21:11:28.700331: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
170
+ 2022-03-23 21:11:28.700459: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
171
+ 2022-03-23 21:11:28.700471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
172
+ 2022-03-23 21:11:28.705699: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
173
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
174
+ 2022-03-23 21:12:52.742026: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
175
+ 2022-03-23 21:12:52.744533: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
176
+ 2022-03-23 21:12:52.803388: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
177
+ 2022-03-23 21:12:53.293244: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
178
+ 2022-03-23 21:12:53.295151: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
179
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
180
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
181
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
182
+ profile_prob = profile / np.sum(profile)
183
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
184
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
185
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
186
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
187
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
188
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
189
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
190
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
191
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
192
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
193
+ 2022-03-23 21:15:12.876907: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
194
+ 2022-03-23 21:15:15.314663: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
195
+ 2022-03-23 21:15:15.315742: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
196
+ 2022-03-23 21:15:15.631354: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
197
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
198
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
199
+ 2022-03-23 21:15:15.631504: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
200
+ 2022-03-23 21:15:15.633590: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
201
+ 2022-03-23 21:15:15.633654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
202
+ 2022-03-23 21:15:15.634600: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
203
+ 2022-03-23 21:15:15.634783: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
204
+ 2022-03-23 21:15:15.636949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
205
+ 2022-03-23 21:15:15.637441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
206
+ 2022-03-23 21:15:15.637583: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
207
+ 2022-03-23 21:15:15.640803: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
208
+ 2022-03-23 21:15:15.641130: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
209
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
210
+ 2022-03-23 21:15:15.641204: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
211
+ 2022-03-23 21:15:15.642828: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
212
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
213
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
214
+ 2022-03-23 21:15:15.642856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
215
+ 2022-03-23 21:15:15.642878: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
216
+ 2022-03-23 21:15:15.642894: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
217
+ 2022-03-23 21:15:15.642934: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
218
+ 2022-03-23 21:15:15.642951: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
219
+ 2022-03-23 21:15:15.642966: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
220
+ 2022-03-23 21:15:15.642981: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
221
+ 2022-03-23 21:15:15.642996: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
222
+ 2022-03-23 21:15:15.646034: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
223
+ 2022-03-23 21:15:15.646064: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
224
+ 2022-03-23 21:15:16.155545: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
225
+ 2022-03-23 21:15:16.155679: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
226
+ 2022-03-23 21:15:16.155690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
227
+ 2022-03-23 21:15:16.160836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
228
+ 2022-03-23 21:16:37.986399: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
229
+ 2022-03-23 21:16:37.988242: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
230
+ 2022-03-23 21:16:38.027663: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
231
+ 2022-03-23 21:16:38.532251: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
232
+ 2022-03-23 21:16:38.534194: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
233
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
234
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
235
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
236
+ profile_prob = profile / np.sum(profile)
237
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
238
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
239
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
240
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
241
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
242
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
243
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
244
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
245
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
246
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
247
+ 2022-03-23 21:17:53.910671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
248
+ 2022-03-23 21:17:55.103267: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
249
+ 2022-03-23 21:17:55.104342: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
250
+ 2022-03-23 21:17:55.406922: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
251
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
252
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
253
+ 2022-03-23 21:17:55.407055: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
254
+ 2022-03-23 21:17:55.409222: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
255
+ 2022-03-23 21:17:55.409275: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
256
+ 2022-03-23 21:17:55.410270: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
257
+ 2022-03-23 21:17:55.410460: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
258
+ 2022-03-23 21:17:55.412661: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
259
+ 2022-03-23 21:17:55.413138: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
260
+ 2022-03-23 21:17:55.413265: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
261
+ 2022-03-23 21:17:55.416061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
262
+ 2022-03-23 21:17:55.416393: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
263
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
264
+ 2022-03-23 21:17:55.416466: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
265
+ 2022-03-23 21:17:55.418965: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
266
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
267
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
268
+ 2022-03-23 21:17:55.418993: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
269
+ 2022-03-23 21:17:55.419009: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
270
+ 2022-03-23 21:17:55.419024: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
271
+ 2022-03-23 21:17:55.419037: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
272
+ 2022-03-23 21:17:55.419051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
273
+ 2022-03-23 21:17:55.419064: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
274
+ 2022-03-23 21:17:55.419077: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
275
+ 2022-03-23 21:17:55.419091: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
276
+ 2022-03-23 21:17:55.421752: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
277
+ 2022-03-23 21:17:55.421788: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
278
+ 2022-03-23 21:17:55.922869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
279
+ 2022-03-23 21:17:55.923028: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
280
+ 2022-03-23 21:17:55.923040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
281
+ 2022-03-23 21:17:55.928123: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
282
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
283
+ 2022-03-23 21:18:10.837775: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
284
+ 2022-03-23 21:18:10.838394: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
285
+ 2022-03-23 21:18:11.080076: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
286
+ 2022-03-23 21:18:11.728968: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
287
+ 2022-03-23 21:18:11.731339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
288
+ mkdir: cannot create directory ‘/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombpnet_model_encsr880cub_bias//footprints’: File exists
289
+ 2022-03-23 21:20:11.526000: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
290
+ 2022-03-23 21:20:12.703430: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
291
+ 2022-03-23 21:20:12.704530: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
292
+ 2022-03-23 21:20:13.002374: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
293
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
294
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
295
+ 2022-03-23 21:20:13.002510: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
296
+ 2022-03-23 21:20:13.004694: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
297
+ 2022-03-23 21:20:13.004757: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
298
+ 2022-03-23 21:20:13.005743: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
299
+ 2022-03-23 21:20:13.005930: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
300
+ 2022-03-23 21:20:13.008132: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
301
+ 2022-03-23 21:20:13.008615: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
302
+ 2022-03-23 21:20:13.008745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
303
+ 2022-03-23 21:20:13.011477: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
304
+ 2022-03-23 21:20:13.011819: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
305
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
306
+ 2022-03-23 21:20:13.011893: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
307
+ 2022-03-23 21:20:13.013226: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
308
+ pciBusID: 0000:8d:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
309
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s
310
+ 2022-03-23 21:20:13.013279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
311
+ 2022-03-23 21:20:13.013297: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
312
+ 2022-03-23 21:20:13.013312: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
313
+ 2022-03-23 21:20:13.013326: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
314
+ 2022-03-23 21:20:13.013339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
315
+ 2022-03-23 21:20:13.013353: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
316
+ 2022-03-23 21:20:13.013366: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
317
+ 2022-03-23 21:20:13.013380: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
318
+ 2022-03-23 21:20:13.015933: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
319
+ 2022-03-23 21:20:13.015966: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
320
+ 2022-03-23 21:20:13.517332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
321
+ 2022-03-23 21:20:13.517471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
322
+ 2022-03-23 21:20:13.517482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
323
+ 2022-03-23 21:20:13.522517: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37401 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:8d:00.0, compute capability: 8.0)
324
+ 2022-03-23 21:20:30.393340: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
325
+ 2022-03-23 21:20:30.393943: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 1999945000 Hz
326
+ 2022-03-23 21:20:30.537517: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
327
+ 2022-03-23 21:20:31.074552: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
328
+ 2022-03-23 21:20:31.076949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1958db949ce339e7c96f85befe4f9e4e8bf86dbbd7bf2759d315bbb6972c8f92
3
+ size 14161910
fold_0/logs.models.fold_0.ENCSR622HTS/logfile.modelling.fold_0.ENCSR622HTS.stdout_v1.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6dd20056b9839cd1804b08c18aa27df9ffa54602945d137c965c43e9fec8eab8
3
+ size 14160304
fold_0/model.bias_scaled.fold_0.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0800e98cd12eba1e963396fa508fb8a3327eade2cd2a761b43fc8e9d88d3edd7
3
+ size 2688440
fold_0/model.bias_scaled.fold_0.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7e75f0294aa3425fbe14b340597b6fdb5e93be54ca52c02a7bb24f8e51193614
3
+ size 1198080
fold_0/model.chrombpnet.fold_0.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f935792e5a1788a26ca7af94dd12530ac895535efc02999a5689543b1795e00b
3
+ size 26447928
fold_0/model.chrombpnet.fold_0.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:07a4ee304e2da995134d3a9f7049ac39055e740171b24fa78d10828c3501f87e
3
+ size 27607040
fold_0/model.chrombpnet_nobias.fold_0.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7fdf1d8862d4e69e04b75559b26ba4317dccc2757c227a4a0d8ffa387633c5a7
3
+ size 25583536
fold_0/model.chrombpnet_nobias.fold_0.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:78fd4a927133f88c6dff0ac044373ee243578fd4dc5af66e2307bd70e4c9b6bb
3
+ size 26081280
fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fc7a1ae87e9d8cc71f6d648f2f624ace2399c178aaf76318caff7c43ea7a2bdd
3
+ size 12409438
fold_1/logs.models.fold_1.ENCSR622HTS/logfile.modelling.fold_1.ENCSR622HTS.stdout_v1.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c26e3d70cd8b2d4dd01e6e5296ad60b776d8df63156e0a7e49c623894f8b5672
3
+ size 12407765
fold_1/model.bias_scaled.fold_1.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f6413b31f52e31a6cc835503fbf4bcc9bacf9e6ee9758e24916a9f916b517155
3
+ size 2688440
fold_1/model.bias_scaled.fold_1.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:be0a932ca0360e801a80824821c58c8be8b042f1c4bed4b805ba9da27f52ef95
3
+ size 1198080
fold_1/model.chrombpnet.fold_1.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f99dacd3a54f2c1fea6bc1e2469c9a0e1a47ecd318ee670b6546063f5e8cbb4d
3
+ size 26447928
fold_1/model.chrombpnet.fold_1.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:43c4031590e00d9b28161a4ee68d5811c25007d4de2d81b7a131af1260d90fc3
3
+ size 27607040
fold_1/model.chrombpnet_nobias.fold_1.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8d217d7abfeecb086afb2617ddb90cd33e5026057c9c5e359a03af8c6600a049
3
+ size 25583536
fold_1/model.chrombpnet_nobias.fold_1.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1741953dde2d2c7cfcb46988a1419da9949608158ab7fc1b9c9487e67045de6c
3
+ size 26081280
fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.args.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
3
+ "bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//preprocessing/bigWigs/ENCSR622HTS.bigWig",
4
+ "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2//filtered.peaks.bed",
5
+ "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2//filtered.nonpeaks.bed",
6
+ "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2//chrombpnet",
7
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
8
+ "trackables": [
9
+ "logcount_predictions_loss",
10
+ "loss",
11
+ "logits_profile_predictions_loss",
12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
15
+ ],
16
+ "epochs": 50,
17
+ "early_stop": 5,
18
+ "batch_size": 64,
19
+ "learning_rate": 0.001,
20
+ "params": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2//chrombpnet_model_params.tsv",
21
+ "seed": 1234,
22
+ "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
+ }
fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.chrombpnet_no_bias_formatting.stderr.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.chrombpnet_no_bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR622HTS//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:28dbc31e4d21ef1bcd3400478b40b98f69f73d4356456cd244df104e3291340a
3
+ size 12676992
fold_2/logs.models.fold_2.ENCSR622HTS/logfile.modelling.fold_2.ENCSR622HTS.stdout_v1.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9227e26b4cddef277d08114a21feee1060aa6754156fa712e84ca33e7dd3152a
3
+ size 19911117
fold_2/model.bias_scaled.fold_2.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ef383b134e7c0194cc706a3738bc59161845a688f5fbcb05db78390b60245cb5
3
+ size 2688440
fold_2/model.bias_scaled.fold_2.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e72052c7a3d0cfb97b84ff735ac67756896a15bf1e659bf3cfa0dd779d444285
3
+ size 1198080
fold_2/model.chrombpnet.fold_2.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:51d39bc1a3f8d9a5658a5acec34e8d543db2452882b1762431b7a3854df0ef2a
3
+ size 26447928
fold_2/model.chrombpnet.fold_2.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:662031e144d6346a80a662c7fb032661f5782bca6c7810002ccd2dea27a76750
3
+ size 27607040
fold_2/model.chrombpnet_nobias.fold_2.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:442539d557d2cb6e39eea939576c43ebe4a174e02a5d3fbecfb4dee8e11fccd3
3
+ size 25583536
fold_2/model.chrombpnet_nobias.fold_2.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:73eb5dd0fcade13a6b95dc8afbe26acffe542657805d86632f9358901f6087ad
3
+ size 26081280
fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:96c88b6b9d73f2e6724e6ca20348b3c6602723313f791202aee19eb8d08f464a
3
+ size 12720520
fold_3/logs.models.fold_3.ENCSR622HTS/logfile.modelling.fold_3.ENCSR622HTS.stdout_v1.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c069eca58c66ea04c1c01e86de008efc493a3d6547db54787a69368995515b4b
3
+ size 12718847
fold_3/model.bias_scaled.fold_3.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:636f4343fa4e03a1fcf862d885ae9ed13840b2dde9be425df639c5ba28ea9d78
3
+ size 2688440
fold_3/model.bias_scaled.fold_3.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ba15951fdd7e893d310d719073555d6387ab24a97840d1c98727e163ecf7bc1f
3
+ size 1198080
fold_3/model.chrombpnet.fold_3.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fd99819873e9bd0a2d96a4070c7626a7d9b31a48f2a93acbacfd0f3094305772
3
+ size 26447928
fold_3/model.chrombpnet.fold_3.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a0219ecdebf99849bc3e1cd4fa25067e119c81751c9c655765881d8dded063d
3
+ size 27607040
fold_3/model.chrombpnet_nobias.fold_3.ENCSR622HTS.h5 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b784c0195b4dcdcd355b2daf021db513403320d9ac9dda0c3a6576fff11e1674
3
+ size 25583536
fold_3/model.chrombpnet_nobias.fold_3.ENCSR622HTS.tar ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:87ed0ecc2be973300758a6fa04c13ef34c02d8d8899ee60bacf1a9b4706e08d9
3
+ size 26081280
fold_4/logs.models.fold_4.ENCSR622HTS/logfile.modelling.fold_4.ENCSR622HTS.stdout.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bd11541458df00e210a651504ab4926211edd08598aa087c0d43ad1390dfe7c4
3
+ size 13462091