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encode-chrombpnet-DNASE-ENCSR679EFH-ENCSR434QWM

chrombpnet
encode
chromatin-accessibility
DNASE
t-cell
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +3 -0
  2. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet.params.json +11 -0
  4. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet_data_params.tsv +3 -0
  5. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet_formatting.stderr.txt +40 -0
  6. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.stdout_v1.txt +3 -0
  9. fold_0/model.bias_scaled.fold_0.ENCSR679EFH.h5 +3 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR679EFH.tar +3 -0
  11. fold_0/model.chrombpnet.fold_0.ENCSR679EFH.h5 +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR679EFH.tar +3 -0
  13. fold_0/model.chrombpnet_nobias.fold_0.ENCSR679EFH.h5 +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR679EFH.tar +3 -0
  15. fold_1/model.bias_scaled.fold_1.ENCSR679EFH.h5 +3 -0
  16. fold_1/model.bias_scaled.fold_1.ENCSR679EFH.tar +3 -0
  17. fold_1/model.chrombpnet.fold_1.ENCSR679EFH.h5 +3 -0
  18. fold_1/model.chrombpnet.fold_1.ENCSR679EFH.tar +3 -0
  19. fold_1/model.chrombpnet_nobias.fold_1.ENCSR679EFH.h5 +3 -0
  20. fold_1/model.chrombpnet_nobias.fold_1.ENCSR679EFH.tar +3 -0
  21. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.args.json +23 -0
  22. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.batch_loss.tsv +0 -0
  23. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.bias_formatting.stderr.txt +38 -0
  24. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.bias_formatting.stdout.txt +1 -0
  25. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet.params.json +11 -0
  26. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_data_params.tsv +3 -0
  27. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_formatting.stderr.txt +40 -0
  28. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_formatting.stdout.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_model_params.tsv +9 -0
  30. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  31. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.epoch_loss.csv +14 -0
  33. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.stderr.txt +332 -0
  34. fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.stdout.txt +0 -0
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  36. fold_2/model.bias_scaled.fold_2.ENCSR679EFH.h5 +3 -0
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  38. fold_2/model.chrombpnet.fold_2.ENCSR679EFH.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR679EFH.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR679EFH.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR679EFH.tar +3 -0
  42. fold_3/model.bias_scaled.fold_3.ENCSR679EFH.h5 +3 -0
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  48. fold_4/logs.models.fold_4.ENCSR679EFH/logfile.modelling.fold_4.ENCSR679EFH.stdout.txt +3 -0
  49. fold_4/logs.models.fold_4.ENCSR679EFH/logfile.modelling.fold_4.ENCSR679EFH.stdout_v1.txt +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR679EFH.h5 +3 -0
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fold_0/logs.models.fold_0.ENCSR679EFH/logfile.modelling.fold_0.ENCSR679EFH.chrombpnet.params.json ADDED
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fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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
+ 2023-07-17 00:22:01.718668: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 00:22:04.038919: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 00:22:04.042705: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-17 00:22:05.181078: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-17 00:22:05.181277: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-17 00:22:05.205289: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-17 00:22:05.205335: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-17 00:22:05.214476: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 00:22:05.219023: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 00:22:05.234699: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 00:22:05.238898: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 00:22:05.239824: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 00:22:05.338404: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 00:22:05.338879: 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 00:22:05.340534: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 00:22:05.381013: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-17 00:22:05.381074: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 00:22:05.381113: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 00:22:05.381142: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-17 00:22:05.381167: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-17 00:22:05.381192: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 00:22:05.381216: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 00:22:05.381240: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 00:22:05.381264: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 00:22:05.422690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 00:22:05.425109: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 00:22:07.672099: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 00:22:07.672263: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 00:22:07.672277: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 00:22:07.678646: 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: 0000:4b:00.0, compute capability: 8.0)
38
+ 2023-07-17 00:22:08.702095: 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.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "1.8",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR679EFH//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.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 0.0
2
+ counts_sum_max_thresh 1023.0
3
+ trainings_pts_post_thresh 175637
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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 13:48:38.925654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 13:48:41.630105: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 13:48:41.633769: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-17 13:48:42.107252: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-17 13:48:42.107357: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-17 13:48:42.128181: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-17 13:48:42.128322: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-17 13:48:42.139249: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 13:48:42.144496: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 13:48:42.162796: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 13:48:42.167730: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 13:48:42.168839: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 13:48:42.196958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 13:48:42.197395: 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 13:48:42.198397: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 13:48:42.218694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-17 13:48:42.218771: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 13:48:42.218810: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 13:48:42.218827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-17 13:48:42.218843: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-17 13:48:42.218859: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 13:48:42.218874: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 13:48:42.218888: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 13:48:42.218903: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 13:48:42.266736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 13:48:42.268595: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 13:48:45.242362: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 13:48:45.242496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 13:48:45.242511: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 13:48:45.296713: 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: 0000:4b:00.0, compute capability: 8.0)
38
+ 2023-07-17 13:48:47.780569: 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.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 1.8
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR679EFH//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.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.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//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.epoch_loss.csv ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,1.7199225425720215,181.88893127441406,184.98463439941406,0.8858486413955688,199.95782470703125,201.55238342285156
3
+ 1,0.8007082939147949,173.67295837402344,175.1145782470703,0.8870822787284851,195.6143035888672,197.21096801757812
4
+ 2,0.7112559080123901,171.30374145507812,172.58416748046875,0.6598244309425354,194.76602172851562,195.95384216308594
5
+ 3,0.6513178944587708,169.85362243652344,171.026123046875,0.6308434009552002,194.12718200683594,195.26271057128906
6
+ 4,0.6185383200645447,168.95199584960938,170.0654296875,0.7016143798828125,193.6898193359375,194.952880859375
7
+ 5,0.6012855172157288,168.3081512451172,169.39060974121094,0.5961201190948486,193.79612731933594,194.8691864013672
8
+ 6,0.5847542881965637,167.12339782714844,168.1757354736328,0.5717376470565796,193.87820434570312,194.9072723388672
9
+ 7,0.5667877793312073,166.30523681640625,167.3258056640625,0.5820107460021973,192.60975646972656,193.65740966796875
10
+ 8,0.5518271327018738,166.0205841064453,167.01364135742188,0.5722978115081787,192.90426635742188,193.93434143066406
11
+ 9,0.5469607710838318,165.473876953125,166.4580535888672,0.6315106153488159,193.12864685058594,194.26541137695312
12
+ 10,0.5376306772232056,164.7610321044922,165.72872924804688,0.567589282989502,194.6714324951172,195.6930389404297
13
+ 11,0.499386191368103,162.68112182617188,163.5801544189453,0.5618689656257629,193.1634063720703,194.1747283935547
14
+ 12,0.48890358209609985,161.1442108154297,162.0240020751953,0.5445017218589783,192.87156677246094,193.85174560546875
fold_2/logs.models.fold_2.ENCSR679EFH/logfile.modelling.fold_2.ENCSR679EFH.stderr.txt ADDED
@@ -0,0 +1,332 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
4
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
5
+ 2023-01-18 20:17:16.967778: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
6
+ 2023-01-18 20:20:51.744057: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
7
+ 2023-01-18 20:20:51.747076: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
8
+ 2023-01-18 20:20:51.929384: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
9
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
10
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
11
+ 2023-01-18 20:20:51.929450: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
12
+ 2023-01-18 20:20:51.946444: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
13
+ 2023-01-18 20:20:51.946500: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
14
+ 2023-01-18 20:20:51.955342: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
15
+ 2023-01-18 20:20:51.959529: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
16
+ 2023-01-18 20:20:51.973985: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
17
+ 2023-01-18 20:20:51.977821: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
18
+ 2023-01-18 20:20:51.978723: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
19
+ 2023-01-18 20:20:51.982629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
20
+ 2023-01-18 20:20:51.982926: 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
21
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
22
+ 2023-01-18 20:20:51.983580: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
23
+ 2023-01-18 20:20:51.985045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
24
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
25
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
26
+ 2023-01-18 20:20:51.985071: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
27
+ 2023-01-18 20:20:51.985087: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
28
+ 2023-01-18 20:20:51.985101: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
29
+ 2023-01-18 20:20:51.985112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
30
+ 2023-01-18 20:20:51.985123: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
31
+ 2023-01-18 20:20:51.985134: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
32
+ 2023-01-18 20:20:51.985145: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
33
+ 2023-01-18 20:20:51.985156: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
34
+ 2023-01-18 20:20:51.987975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
35
+ 2023-01-18 20:20:51.989042: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
36
+ 2023-01-18 20:20:53.272950: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
37
+ 2023-01-18 20:20:53.273119: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
38
+ 2023-01-18 20:20:53.273132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
39
+ 2023-01-18 20:20:53.278541: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
40
+ 2023-01-18 20:20:54.673994: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
41
+ 2023-01-18 20:20:55.730312: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
42
+ 2023-01-18 20:20:55.888545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
43
+ 2023-01-18 20:20:57.067005: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
44
+ 2023-01-18 20:20:57.073707: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
45
+ 2023-01-18 20:21:24.400060: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
46
+ 2023-01-18 20:21:25.839265: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
47
+ 2023-01-18 20:21:25.839965: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
48
+ 2023-01-18 20:21:25.955548: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
49
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
50
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
51
+ 2023-01-18 20:21:25.955599: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
52
+ 2023-01-18 20:21:25.957556: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
53
+ 2023-01-18 20:21:25.957599: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
54
+ 2023-01-18 20:21:25.958506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
55
+ 2023-01-18 20:21:25.958774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
56
+ 2023-01-18 20:21:25.960560: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
57
+ 2023-01-18 20:21:25.961042: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
58
+ 2023-01-18 20:21:25.961303: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
59
+ 2023-01-18 20:21:25.963059: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
60
+ 2023-01-18 20:21:25.963335: 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
61
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
62
+ 2023-01-18 20:21:25.963390: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
63
+ 2023-01-18 20:21:25.964286: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
64
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
65
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
66
+ 2023-01-18 20:21:25.964308: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
67
+ 2023-01-18 20:21:25.964322: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
68
+ 2023-01-18 20:21:25.964334: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
69
+ 2023-01-18 20:21:25.964344: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
70
+ 2023-01-18 20:21:25.964355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
71
+ 2023-01-18 20:21:25.964365: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
72
+ 2023-01-18 20:21:25.964375: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
73
+ 2023-01-18 20:21:25.964385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
74
+ 2023-01-18 20:21:25.966034: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
75
+ 2023-01-18 20:21:25.966064: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
76
+ 2023-01-18 20:21:26.478921: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
77
+ 2023-01-18 20:21:26.479055: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
78
+ 2023-01-18 20:21:26.479069: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
79
+ 2023-01-18 20:21:26.481854: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
80
+ 2023-01-18 20:25:03.491191: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
81
+ 2023-01-18 20:25:03.491605: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
82
+ 2023-01-18 20:25:04.651742: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
83
+ 2023-01-18 20:25:05.069627: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
84
+ 2023-01-18 20:25:05.083360: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
85
+ 2023-01-18 20:25:07.727871: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
86
+ 2023-01-18 21:47:51.102128: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
87
+ 2023-01-18 21:47:53.332030: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
88
+ 2023-01-18 21:47:53.332915: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
89
+ 2023-01-18 21:47:53.475663: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
90
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
91
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
92
+ 2023-01-18 21:47:53.475767: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
93
+ 2023-01-18 21:47:53.477851: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
94
+ 2023-01-18 21:47:53.477902: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
95
+ 2023-01-18 21:47:53.478799: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
96
+ 2023-01-18 21:47:53.479069: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
97
+ 2023-01-18 21:47:53.480988: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
98
+ 2023-01-18 21:47:53.481486: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
99
+ 2023-01-18 21:47:53.481774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
100
+ 2023-01-18 21:47:53.483524: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
101
+ 2023-01-18 21:47:53.483809: 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
102
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
103
+ 2023-01-18 21:47:53.483871: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
104
+ 2023-01-18 21:47:53.484763: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
105
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
106
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
107
+ 2023-01-18 21:47:53.484784: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
108
+ 2023-01-18 21:47:53.484800: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
109
+ 2023-01-18 21:47:53.484813: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
110
+ 2023-01-18 21:47:53.484825: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
111
+ 2023-01-18 21:47:53.484836: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
112
+ 2023-01-18 21:47:53.484848: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
113
+ 2023-01-18 21:47:53.484858: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
114
+ 2023-01-18 21:47:53.484870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
115
+ 2023-01-18 21:47:53.486523: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
116
+ 2023-01-18 21:47:53.486550: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
117
+ 2023-01-18 21:47:53.899740: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
118
+ 2023-01-18 21:47:53.899804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
119
+ 2023-01-18 21:47:53.899816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
120
+ 2023-01-18 21:47:53.902685: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
121
+ 2023-01-18 21:48:45.139829: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
122
+ 2023-01-18 21:48:45.142487: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
123
+ 2023-01-18 21:48:45.208347: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
124
+ 2023-01-18 21:48:45.603880: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
125
+ 2023-01-18 21:48:45.605714: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
126
+ /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.
127
+ , UserWarning)
128
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
129
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
130
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
131
+ profile_prob = profile / np.sum(profile)
132
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
133
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
134
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
135
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
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
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
138
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
139
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
140
+ 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.
141
+ 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.
142
+ 2023-01-18 21:50:45.201358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
143
+ 2023-01-18 21:50:47.352461: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
144
+ 2023-01-18 21:50:47.353678: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
145
+ 2023-01-18 21:50:47.501841: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
146
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
147
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
148
+ 2023-01-18 21:50:47.501989: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
149
+ 2023-01-18 21:50:47.503957: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
150
+ 2023-01-18 21:50:47.504005: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
151
+ 2023-01-18 21:50:47.504871: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
152
+ 2023-01-18 21:50:47.505127: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
153
+ 2023-01-18 21:50:47.506906: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
154
+ 2023-01-18 21:50:47.507381: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
155
+ 2023-01-18 21:50:47.507671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
156
+ 2023-01-18 21:50:47.509492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
157
+ 2023-01-18 21:50:47.509789: 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
158
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
159
+ 2023-01-18 21:50:47.509852: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
160
+ 2023-01-18 21:50:47.510715: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
161
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
162
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
163
+ 2023-01-18 21:50:47.510735: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
164
+ 2023-01-18 21:50:47.510751: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
165
+ 2023-01-18 21:50:47.510764: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
166
+ 2023-01-18 21:50:47.510775: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
167
+ 2023-01-18 21:50:47.510786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
168
+ 2023-01-18 21:50:47.510797: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
169
+ 2023-01-18 21:50:47.510808: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
170
+ 2023-01-18 21:50:47.510818: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
171
+ 2023-01-18 21:50:47.512445: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
172
+ 2023-01-18 21:50:47.512471: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
173
+ 2023-01-18 21:50:47.943200: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
174
+ 2023-01-18 21:50:47.943302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
175
+ 2023-01-18 21:50:47.943314: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
176
+ 2023-01-18 21:50:47.946303: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
177
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
178
+ 2023-01-18 21:51:34.183340: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
179
+ 2023-01-18 21:51:34.185222: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
180
+ 2023-01-18 21:51:34.228424: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
181
+ 2023-01-18 21:51:34.615571: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
182
+ 2023-01-18 21:51:34.617081: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
183
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
184
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
185
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
186
+ profile_prob = profile / np.sum(profile)
187
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
188
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
189
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
190
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
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
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
193
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
194
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
195
+ 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.
196
+ 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.
197
+ 2023-01-18 21:53:17.955273: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
198
+ 2023-01-18 21:53:20.070060: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
199
+ 2023-01-18 21:53:20.071216: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
200
+ 2023-01-18 21:53:20.220631: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
201
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
202
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
203
+ 2023-01-18 21:53:20.220690: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
204
+ 2023-01-18 21:53:20.222692: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
205
+ 2023-01-18 21:53:20.222740: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
206
+ 2023-01-18 21:53:20.223633: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
207
+ 2023-01-18 21:53:20.223878: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
208
+ 2023-01-18 21:53:20.225733: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
209
+ 2023-01-18 21:53:20.226211: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
210
+ 2023-01-18 21:53:20.226487: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
211
+ 2023-01-18 21:53:20.228290: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
212
+ 2023-01-18 21:53:20.228559: 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
213
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
214
+ 2023-01-18 21:53:20.228614: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
215
+ 2023-01-18 21:53:20.229477: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
216
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
217
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
218
+ 2023-01-18 21:53:20.229499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
219
+ 2023-01-18 21:53:20.229536: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
220
+ 2023-01-18 21:53:20.229553: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
221
+ 2023-01-18 21:53:20.229567: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
222
+ 2023-01-18 21:53:20.229581: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
223
+ 2023-01-18 21:53:20.229594: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
224
+ 2023-01-18 21:53:20.229606: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
225
+ 2023-01-18 21:53:20.229619: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
226
+ 2023-01-18 21:53:20.231236: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
227
+ 2023-01-18 21:53:20.231264: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
228
+ 2023-01-18 21:53:20.654435: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
229
+ 2023-01-18 21:53:20.654559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
230
+ 2023-01-18 21:53:20.654571: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
231
+ 2023-01-18 21:53:20.657480: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
232
+ 2023-01-18 21:54:06.681644: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
233
+ 2023-01-18 21:54:06.683098: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
234
+ 2023-01-18 21:54:06.711227: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
235
+ 2023-01-18 21:54:07.100438: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
236
+ 2023-01-18 21:54:07.101893: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
237
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
238
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
239
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
240
+ profile_prob = profile / np.sum(profile)
241
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
242
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
243
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
244
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
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
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
247
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
248
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
249
+ 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.
250
+ 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.
251
+ 2023-01-18 21:54:57.767269: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
252
+ 2023-01-18 21:54:58.836591: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
253
+ 2023-01-18 21:54:58.837564: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
254
+ 2023-01-18 21:54:58.989185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
255
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
256
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
257
+ 2023-01-18 21:54:58.989260: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
258
+ 2023-01-18 21:54:58.991718: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
259
+ 2023-01-18 21:54:58.991782: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
260
+ 2023-01-18 21:54:58.992887: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
261
+ 2023-01-18 21:54:58.993240: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
262
+ 2023-01-18 21:54:58.995463: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
263
+ 2023-01-18 21:54:58.996190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
264
+ 2023-01-18 21:54:58.996482: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
265
+ 2023-01-18 21:54:58.998232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
266
+ 2023-01-18 21:54:58.998501: 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
267
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
268
+ 2023-01-18 21:54:58.998558: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
269
+ 2023-01-18 21:54:58.999410: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
270
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
271
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
272
+ 2023-01-18 21:54:58.999436: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
273
+ 2023-01-18 21:54:58.999452: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
274
+ 2023-01-18 21:54:58.999464: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
275
+ 2023-01-18 21:54:58.999476: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
276
+ 2023-01-18 21:54:58.999488: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
277
+ 2023-01-18 21:54:58.999499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
278
+ 2023-01-18 21:54:58.999511: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
279
+ 2023-01-18 21:54:58.999522: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
280
+ 2023-01-18 21:54:59.001220: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
281
+ 2023-01-18 21:54:59.001252: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
282
+ 2023-01-18 21:54:59.431528: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
283
+ 2023-01-18 21:54:59.431637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
284
+ 2023-01-18 21:54:59.431649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
285
+ 2023-01-18 21:54:59.434580: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
286
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
287
+ 2023-01-18 21:55:08.043317: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
288
+ 2023-01-18 21:55:08.043762: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
289
+ 2023-01-18 21:55:08.203168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
290
+ 2023-01-18 21:55:08.639345: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
291
+ 2023-01-18 21:55:08.641062: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
292
+ mkdir: cannot create directory ‘/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR679EFH//chrombppnet_model_encsr283tme_bias_fold_2//footprints’: File exists
293
+ 2023-01-18 21:56:43.610653: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
294
+ 2023-01-18 21:56:44.663970: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
295
+ 2023-01-18 21:56:44.664774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
296
+ 2023-01-18 21:56:44.811931: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
297
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
298
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
299
+ 2023-01-18 21:56:44.812043: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
300
+ 2023-01-18 21:56:44.814073: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
301
+ 2023-01-18 21:56:44.814119: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
302
+ 2023-01-18 21:56:44.814995: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
303
+ 2023-01-18 21:56:44.815247: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
304
+ 2023-01-18 21:56:44.817100: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
305
+ 2023-01-18 21:56:44.817570: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
306
+ 2023-01-18 21:56:44.817850: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
307
+ 2023-01-18 21:56:44.819553: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
308
+ 2023-01-18 21:56:44.819818: 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
309
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
310
+ 2023-01-18 21:56:44.819897: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
311
+ 2023-01-18 21:56:44.820767: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
312
+ pciBusID: 0000:c1:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
313
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.18GiB deviceMemoryBandwidth: 1.85TiB/s
314
+ 2023-01-18 21:56:44.820793: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
315
+ 2023-01-18 21:56:44.820809: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
316
+ 2023-01-18 21:56:44.820823: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
317
+ 2023-01-18 21:56:44.820835: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
318
+ 2023-01-18 21:56:44.820847: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
319
+ 2023-01-18 21:56:44.820859: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
320
+ 2023-01-18 21:56:44.820870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
321
+ 2023-01-18 21:56:44.820882: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
322
+ 2023-01-18 21:56:44.822492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
323
+ 2023-01-18 21:56:44.822525: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
324
+ 2023-01-18 21:56:45.252068: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
325
+ 2023-01-18 21:56:45.252202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
326
+ 2023-01-18 21:56:45.252215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
327
+ 2023-01-18 21:56:45.255209: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75686 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c1:00.0, compute capability: 8.0)
328
+ 2023-01-18 21:56:53.763513: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
329
+ 2023-01-18 21:56:53.763953: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794885000 Hz
330
+ 2023-01-18 21:56:53.878341: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
331
+ 2023-01-18 21:56:54.318871: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
332
+ 2023-01-18 21:56:54.320472: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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