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encode-chrombpnet-DNASE-activated-CD4-positive-alpha-beta-T-ENCSR154NOT-ENCSR114ZKF

chrombpnet
encode
chromatin-accessibility
DNASE
t-cell
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +6 -0
  2. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.args.json +23 -0
  3. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.batch_loss.tsv +0 -0
  4. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.bias_formatting.stdout.txt +1 -0
  5. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.chrombpnet_formatting.stdout.txt +1 -0
  6. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.epoch_loss.csv +19 -0
  9. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.stdout.txt +3 -0
  10. fold_0/logs.models.fold_0.ENCSR154NOT/logfile.modelling.fold_0.ENCSR154NOT.stdout_v1.txt +3 -0
  11. fold_0/model.bias_scaled.fold_0.ENCSR154NOT.h5 +3 -0
  12. fold_0/model.bias_scaled.fold_0.ENCSR154NOT.tar +3 -0
  13. fold_0/model.chrombpnet.fold_0.ENCSR154NOT.h5 +3 -0
  14. fold_0/model.chrombpnet.fold_0.ENCSR154NOT.tar +3 -0
  15. fold_0/model.chrombpnet_nobias.fold_0.ENCSR154NOT.h5 +3 -0
  16. fold_0/model.chrombpnet_nobias.fold_0.ENCSR154NOT.tar +3 -0
  17. fold_1/logs.models.fold_1.ENCSR154NOT/logfile.modelling.fold_1.ENCSR154NOT.stdout.txt +3 -0
  18. fold_1/logs.models.fold_1.ENCSR154NOT/logfile.modelling.fold_1.ENCSR154NOT.stdout_v1.txt +3 -0
  19. fold_1/model.bias_scaled.fold_1.ENCSR154NOT.h5 +3 -0
  20. fold_1/model.bias_scaled.fold_1.ENCSR154NOT.tar +3 -0
  21. fold_1/model.chrombpnet.fold_1.ENCSR154NOT.h5 +3 -0
  22. fold_1/model.chrombpnet.fold_1.ENCSR154NOT.tar +3 -0
  23. fold_1/model.chrombpnet_nobias.fold_1.ENCSR154NOT.h5 +3 -0
  24. fold_1/model.chrombpnet_nobias.fold_1.ENCSR154NOT.tar +3 -0
  25. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.args.json +23 -0
  26. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.batch_loss.tsv +0 -0
  27. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.bias_formatting.stderr.txt +38 -0
  28. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.bias_formatting.stdout.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet.params.json +11 -0
  30. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_data_params.tsv +3 -0
  31. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_formatting.stderr.txt +40 -0
  32. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_model_params.tsv +9 -0
  34. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  35. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  36. fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.epoch_loss.csv +15 -0
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  42. fold_2/model.chrombpnet.fold_2.ENCSR154NOT.h5 +3 -0
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  49. fold_3/model.chrombpnet.fold_3.ENCSR154NOT.tar +3 -0
  50. fold_3/model.chrombpnet_nobias.fold_3.ENCSR154NOT.h5 +3 -0
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+ "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/ENCSR154NOT//chrombppnet_model_encsr283tme_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.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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
+ 2023-07-16 23:45:20.398725: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-16 23:45:24.028984: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-16 23:45:24.034762: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-16 23:45:24.068569: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:82:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
8
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
9
+ 2023-07-16 23:45:24.068662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-16 23:45:24.099079: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-16 23:45:24.099225: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-16 23:45:24.114770: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-16 23:45:24.122140: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-16 23:45:24.148922: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-16 23:45:24.155889: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-16 23:45:24.157436: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-16 23:45:24.159642: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-16 23:45:24.160050: 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
+ 2023-07-16 23:45:24.161206: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-16 23:45:24.161536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:82:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
24
+ 2023-07-16 23:45:24.161579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-16 23:45:24.161647: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-16 23:45:24.161682: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-16 23:45:24.161716: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-16 23:45:24.161750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-16 23:45:24.161783: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-16 23:45:24.161815: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-16 23:45:24.161849: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-16 23:45:24.162261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-16 23:45:24.163889: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-16 23:45:26.451355: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-16 23:45:26.451463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-16 23:45:26.451487: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-16 23:45:26.455040: 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: 0000:82:00.0, compute capability: 6.0)
38
+ 2023-07-16 23:45:27.517397: 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_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "4.3",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/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_2.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 5.0
2
+ counts_sum_max_thresh 1438.0
3
+ trainings_pts_post_thresh 176835
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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
+ 2023-07-17 13:13:56.376786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 13:14:00.145704: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 13:14:00.151409: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-17 13:14:00.195068: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:82:00.0 name: NVIDIA TITAN V computeCapability: 7.0
8
+ coreClock: 1.455GHz coreCount: 80 deviceMemorySize: 11.77GiB deviceMemoryBandwidth: 607.97GiB/s
9
+ 2023-07-17 13:14:00.195173: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-17 13:14:00.225575: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-17 13:14:00.225748: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-17 13:14:00.241987: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 13:14:00.249943: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 13:14:00.277055: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 13:14:00.284040: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 13:14:00.285618: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 13:14:00.287981: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 13:14:00.288372: 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
+ 2023-07-17 13:14:00.289450: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 13:14:00.290667: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:82:00.0 name: NVIDIA TITAN V computeCapability: 7.0
23
+ coreClock: 1.455GHz coreCount: 80 deviceMemorySize: 11.77GiB deviceMemoryBandwidth: 607.97GiB/s
24
+ 2023-07-17 13:14:00.290715: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 13:14:00.290760: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 13:14:00.290786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-17 13:14:00.290811: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-17 13:14:00.290836: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 13:14:00.290860: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 13:14:00.290884: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 13:14:00.290909: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 13:14:00.291416: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 13:14:00.293039: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 13:14:02.603308: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 13:14:02.603410: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 13:14:02.603430: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 13:14:02.607233: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10907 MB memory) -> physical GPU (device: 0, name: NVIDIA TITAN V, pci bus id: 0000:82:00.0, compute capability: 7.0)
38
+ 2023-07-17 13:14:05.508810: 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_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 4.3
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/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_2.json
9
+ negative_sampling_ratio 0.1
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.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//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.epoch_loss.csv ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,1.018155813217163,280.98382568359375,285.36224365234375,0.6224915385246277,281.9400634765625,284.6166687011719
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+ 8,0.3710912764072418,259.18121337890625,260.7768859863281,0.4108295440673828,275.66253662109375,277.42913818359375
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+ 9,0.35443568229675293,257.3683776855469,258.892333984375,0.4269165098667145,275.6818542480469,277.5176696777344
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+ 10,0.34331393241882324,255.96728515625,257.4440002441406,0.4045581817626953,276.6063537597656,278.3459777832031
13
+ 11,0.33433547616004944,254.7960968017578,256.2340393066406,0.43374139070510864,275.9014892578125,277.7664794921875
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+ 12,0.3168388903141022,252.3664093017578,253.7283935546875,0.4000672399997711,277.5106201171875,279.2309265136719
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+ 13,0.30968037247657776,251.66165161132812,252.9932403564453,0.4039236009120941,278.48992919921875,280.2266540527344
fold_2/logs.models.fold_2.ENCSR154NOT/logfile.modelling.fold_2.ENCSR154NOT.stderr.txt ADDED
@@ -0,0 +1,328 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-10-05 00:06:07.508117: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2
+ 2022-10-05 00:10:55.055117: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
3
+ 2022-10-05 00:10:55.057086: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
4
+ 2022-10-05 00:10:55.521151: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
5
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
6
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
7
+ 2022-10-05 00:10:55.521221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
8
+ 2022-10-05 00:10:55.544299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
9
+ 2022-10-05 00:10:55.544358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
10
+ 2022-10-05 00:10:55.556651: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
11
+ 2022-10-05 00:10:55.562260: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
12
+ 2022-10-05 00:10:55.581936: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
13
+ 2022-10-05 00:10:55.587386: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
14
+ 2022-10-05 00:10:55.588668: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
15
+ 2022-10-05 00:10:55.592993: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
16
+ 2022-10-05 00:10:55.593340: 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
+ 2022-10-05 00:10:55.593433: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
19
+ 2022-10-05 00:10:55.594938: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
20
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
21
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
22
+ 2022-10-05 00:10:55.594969: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
23
+ 2022-10-05 00:10:55.594989: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
24
+ 2022-10-05 00:10:55.595006: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
25
+ 2022-10-05 00:10:55.595022: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
26
+ 2022-10-05 00:10:55.595036: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
27
+ 2022-10-05 00:10:55.595051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
28
+ 2022-10-05 00:10:55.595066: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
29
+ 2022-10-05 00:10:55.595080: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
30
+ 2022-10-05 00:10:55.597970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
31
+ 2022-10-05 00:10:55.599539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
32
+ 2022-10-05 00:10:57.134274: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
33
+ 2022-10-05 00:10:57.134342: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
34
+ 2022-10-05 00:10:57.134357: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
35
+ 2022-10-05 00:10:57.140944: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
36
+ 2022-10-05 00:10:58.950346: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
37
+ 2022-10-05 00:10:58.958431: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
38
+ 2022-10-05 00:10:59.129108: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
39
+ 2022-10-05 00:11:00.562978: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
40
+ 2022-10-05 00:11:00.574049: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
41
+ 2022-10-05 00:11:31.961510: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
42
+ 2022-10-05 00:11:33.470011: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
43
+ 2022-10-05 00:11:33.470838: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
44
+ 2022-10-05 00:11:33.759139: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
45
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
46
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
47
+ 2022-10-05 00:11:33.759211: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
48
+ 2022-10-05 00:11:33.761661: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
49
+ 2022-10-05 00:11:33.761708: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
50
+ 2022-10-05 00:11:33.762729: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
51
+ 2022-10-05 00:11:33.762916: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
52
+ 2022-10-05 00:11:33.765306: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
53
+ 2022-10-05 00:11:33.765793: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
54
+ 2022-10-05 00:11:33.765919: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
55
+ 2022-10-05 00:11:33.767623: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
56
+ 2022-10-05 00:11:33.767919: 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
+ 2022-10-05 00:11:33.768011: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
59
+ 2022-10-05 00:11:33.768860: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
60
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
61
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
62
+ 2022-10-05 00:11:33.768905: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
63
+ 2022-10-05 00:11:33.768924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
64
+ 2022-10-05 00:11:33.768937: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
65
+ 2022-10-05 00:11:33.768950: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
66
+ 2022-10-05 00:11:33.768963: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
67
+ 2022-10-05 00:11:33.768975: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
68
+ 2022-10-05 00:11:33.768987: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
69
+ 2022-10-05 00:11:33.768999: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
70
+ 2022-10-05 00:11:33.770601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
71
+ 2022-10-05 00:11:33.770639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
72
+ 2022-10-05 00:11:34.312721: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
73
+ 2022-10-05 00:11:34.312829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
74
+ 2022-10-05 00:11:34.312844: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
75
+ 2022-10-05 00:11:34.315629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
76
+ 2022-10-05 00:16:35.025911: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
77
+ 2022-10-05 00:16:35.026406: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
78
+ 2022-10-05 00:16:36.439391: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
79
+ 2022-10-05 00:16:36.917421: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
80
+ 2022-10-05 00:16:36.931870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
81
+ 2022-10-05 00:16:40.170664: 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
+ 2022-10-05 01:45:44.045195: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
83
+ 2022-10-05 01:45:46.611965: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
84
+ 2022-10-05 01:45:46.612896: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
85
+ 2022-10-05 01:45:46.891425: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
86
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
87
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
88
+ 2022-10-05 01:45:46.891537: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
89
+ 2022-10-05 01:45:46.894145: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
90
+ 2022-10-05 01:45:46.894200: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
91
+ 2022-10-05 01:45:46.895242: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
92
+ 2022-10-05 01:45:46.895438: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
93
+ 2022-10-05 01:45:46.897804: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
94
+ 2022-10-05 01:45:46.898297: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
95
+ 2022-10-05 01:45:46.898430: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
96
+ 2022-10-05 01:45:46.900184: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
97
+ 2022-10-05 01:45:46.900495: 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
+ 2022-10-05 01:45:46.900592: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
100
+ 2022-10-05 01:45:46.901463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
101
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
102
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
103
+ 2022-10-05 01:45:46.901488: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
104
+ 2022-10-05 01:45:46.901506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
105
+ 2022-10-05 01:45:46.901522: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
106
+ 2022-10-05 01:45:46.901536: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
107
+ 2022-10-05 01:45:46.901550: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
108
+ 2022-10-05 01:45:46.901564: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
109
+ 2022-10-05 01:45:46.901578: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
110
+ 2022-10-05 01:45:46.901600: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
111
+ 2022-10-05 01:45:46.903190: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
112
+ 2022-10-05 01:45:46.903225: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
113
+ 2022-10-05 01:45:47.379465: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
114
+ 2022-10-05 01:45:47.379653: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
115
+ 2022-10-05 01:45:47.379669: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
116
+ 2022-10-05 01:45:47.382517: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
117
+ 2022-10-05 01:46:56.875933: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
118
+ 2022-10-05 01:46:56.879011: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
119
+ 2022-10-05 01:46:56.956022: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
120
+ 2022-10-05 01:46:57.428997: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
121
+ 2022-10-05 01:46:57.431220: 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
+ 2022-10-05 01:48:52.120302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
139
+ 2022-10-05 01:48:54.370640: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
140
+ 2022-10-05 01:48:54.371556: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
141
+ 2022-10-05 01:48:54.649764: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
142
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
143
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
144
+ 2022-10-05 01:48:54.649875: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
145
+ 2022-10-05 01:48:54.652166: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
146
+ 2022-10-05 01:48:54.652219: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
147
+ 2022-10-05 01:48:54.653206: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
148
+ 2022-10-05 01:48:54.653394: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
149
+ 2022-10-05 01:48:54.655612: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
150
+ 2022-10-05 01:48:54.656063: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
151
+ 2022-10-05 01:48:54.656200: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
152
+ 2022-10-05 01:48:54.657879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
153
+ 2022-10-05 01:48:54.658194: 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
+ 2022-10-05 01:48:54.658311: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
156
+ 2022-10-05 01:48:54.659157: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
157
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
158
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
159
+ 2022-10-05 01:48:54.659182: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
160
+ 2022-10-05 01:48:54.659201: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
161
+ 2022-10-05 01:48:54.659215: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
162
+ 2022-10-05 01:48:54.659229: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
163
+ 2022-10-05 01:48:54.659243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
164
+ 2022-10-05 01:48:54.659256: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
165
+ 2022-10-05 01:48:54.659270: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
166
+ 2022-10-05 01:48:54.659284: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
167
+ 2022-10-05 01:48:54.660879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
168
+ 2022-10-05 01:48:54.660916: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
169
+ 2022-10-05 01:48:55.134241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
170
+ 2022-10-05 01:48:55.134370: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
171
+ 2022-10-05 01:48:55.134389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
172
+ 2022-10-05 01:48:55.137274: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, 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
+ 2022-10-05 01:50:02.104196: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
175
+ 2022-10-05 01:50:02.106439: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
176
+ 2022-10-05 01:50:02.159126: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
177
+ 2022-10-05 01:50:02.632575: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
178
+ 2022-10-05 01:50:02.634213: 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
+ 2022-10-05 01:51:49.290573: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
194
+ 2022-10-05 01:51:51.540416: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
195
+ 2022-10-05 01:51:51.541302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
196
+ 2022-10-05 01:51:51.815752: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
197
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
198
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
199
+ 2022-10-05 01:51:51.815847: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
200
+ 2022-10-05 01:51:51.818247: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
201
+ 2022-10-05 01:51:51.818305: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
202
+ 2022-10-05 01:51:51.819376: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
203
+ 2022-10-05 01:51:51.819626: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
204
+ 2022-10-05 01:51:51.821853: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
205
+ 2022-10-05 01:51:51.822299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
206
+ 2022-10-05 01:51:51.822429: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
207
+ 2022-10-05 01:51:51.824086: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
208
+ 2022-10-05 01:51:51.824382: 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
+ 2022-10-05 01:51:51.824471: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
211
+ 2022-10-05 01:51:51.825318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
212
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
213
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
214
+ 2022-10-05 01:51:51.825341: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
215
+ 2022-10-05 01:51:51.825360: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
216
+ 2022-10-05 01:51:51.825375: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
217
+ 2022-10-05 01:51:51.825411: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
218
+ 2022-10-05 01:51:51.825427: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
219
+ 2022-10-05 01:51:51.825441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
220
+ 2022-10-05 01:51:51.825455: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
221
+ 2022-10-05 01:51:51.825468: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
222
+ 2022-10-05 01:51:51.827069: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
223
+ 2022-10-05 01:51:51.827104: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
224
+ 2022-10-05 01:51:52.291123: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
225
+ 2022-10-05 01:51:52.291249: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
226
+ 2022-10-05 01:51:52.291263: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
227
+ 2022-10-05 01:51:52.294121: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
228
+ 2022-10-05 01:52:56.233799: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
229
+ 2022-10-05 01:52:56.235418: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
230
+ 2022-10-05 01:52:56.268581: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
231
+ 2022-10-05 01:52:56.729325: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
232
+ 2022-10-05 01:52:56.731014: 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
+ 2022-10-05 01:53:53.711118: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
248
+ 2022-10-05 01:53:54.789077: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
249
+ 2022-10-05 01:53:54.790036: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
250
+ 2022-10-05 01:53:55.063882: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
251
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
252
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
253
+ 2022-10-05 01:53:55.063964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
254
+ 2022-10-05 01:53:55.066073: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
255
+ 2022-10-05 01:53:55.066125: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
256
+ 2022-10-05 01:53:55.067057: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
257
+ 2022-10-05 01:53:55.067245: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
258
+ 2022-10-05 01:53:55.069379: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
259
+ 2022-10-05 01:53:55.069856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
260
+ 2022-10-05 01:53:55.069990: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
261
+ 2022-10-05 01:53:55.071636: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
262
+ 2022-10-05 01:53:55.071945: 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
+ 2022-10-05 01:53:55.072041: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
265
+ 2022-10-05 01:53:55.072924: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
266
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
267
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
268
+ 2022-10-05 01:53:55.072955: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
269
+ 2022-10-05 01:53:55.072974: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
270
+ 2022-10-05 01:53:55.072990: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
271
+ 2022-10-05 01:53:55.073005: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
272
+ 2022-10-05 01:53:55.073019: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
273
+ 2022-10-05 01:53:55.073033: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
274
+ 2022-10-05 01:53:55.073047: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
275
+ 2022-10-05 01:53:55.073061: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
276
+ 2022-10-05 01:53:55.074643: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
277
+ 2022-10-05 01:53:55.074695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
278
+ 2022-10-05 01:53:55.533514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
279
+ 2022-10-05 01:53:55.533670: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
280
+ 2022-10-05 01:53:55.533686: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
281
+ 2022-10-05 01:53:55.536430: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, 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
+ 2022-10-05 01:54:09.833991: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
284
+ 2022-10-05 01:54:09.834540: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
285
+ 2022-10-05 01:54:10.021476: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
286
+ 2022-10-05 01:54:10.530956: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
287
+ 2022-10-05 01:54:10.532731: 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/ENCSR154NOT//chrombppnet_model_encsr283tme_bias_fold_2//footprints’: File exists
289
+ 2022-10-05 01:55:50.066833: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
290
+ 2022-10-05 01:55:51.150523: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
291
+ 2022-10-05 01:55:51.151502: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
292
+ 2022-10-05 01:55:51.427098: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
293
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
294
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
295
+ 2022-10-05 01:55:51.427187: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
296
+ 2022-10-05 01:55:51.430160: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
297
+ 2022-10-05 01:55:51.430211: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
298
+ 2022-10-05 01:55:51.431123: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
299
+ 2022-10-05 01:55:51.431303: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
300
+ 2022-10-05 01:55:51.433410: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
301
+ 2022-10-05 01:55:51.433866: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
302
+ 2022-10-05 01:55:51.433995: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
303
+ 2022-10-05 01:55:51.435637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
304
+ 2022-10-05 01:55:51.435937: 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
+ 2022-10-05 01:55:51.436022: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
307
+ 2022-10-05 01:55:51.436861: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
308
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
309
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
310
+ 2022-10-05 01:55:51.436912: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
311
+ 2022-10-05 01:55:51.436931: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
312
+ 2022-10-05 01:55:51.436946: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
313
+ 2022-10-05 01:55:51.436960: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
314
+ 2022-10-05 01:55:51.436974: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
315
+ 2022-10-05 01:55:51.436987: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
316
+ 2022-10-05 01:55:51.437000: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
317
+ 2022-10-05 01:55:51.437014: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
318
+ 2022-10-05 01:55:51.438600: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
319
+ 2022-10-05 01:55:51.438639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
320
+ 2022-10-05 01:55:51.899389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
321
+ 2022-10-05 01:55:51.899504: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
322
+ 2022-10-05 01:55:51.899518: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
323
+ 2022-10-05 01:55:51.902262: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
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+ 2022-10-05 01:56:05.430446: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
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+ 2022-10-05 01:56:05.431016: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
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+ 2022-10-05 01:56:06.057945: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2022-10-05 01:56:06.059619: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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