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encode-chrombpnet-DNASE-T-cell-ENCSR299BQG-ENCSR870KZC

chrombpnet
encode
chromatin-accessibility
DNASE
t-cell
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +9 -0
  2. fold_0/logs.models.fold_0.ENCSR299BQG/logfile.modelling.fold_0.ENCSR299BQG.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR299BQG/logfile.modelling.fold_0.ENCSR299BQG.chrombpnet.params.json +11 -0
  4. fold_0/logs.models.fold_0.ENCSR299BQG/logfile.modelling.fold_0.ENCSR299BQG.chrombpnet_formatting.stderr.txt +40 -0
  5. fold_0/logs.models.fold_0.ENCSR299BQG/logfile.modelling.fold_0.ENCSR299BQG.stdout_v1.txt +3 -0
  6. fold_0/model.bias_scaled.fold_0.ENCSR299BQG.h5 +3 -0
  7. fold_0/model.bias_scaled.fold_0.ENCSR299BQG.tar +3 -0
  8. fold_0/model.chrombpnet.fold_0.ENCSR299BQG.h5 +3 -0
  9. fold_0/model.chrombpnet.fold_0.ENCSR299BQG.tar +3 -0
  10. fold_0/model.chrombpnet_nobias.fold_0.ENCSR299BQG.h5 +3 -0
  11. fold_0/model.chrombpnet_nobias.fold_0.ENCSR299BQG.tar +3 -0
  12. fold_1/logs.models.fold_1.ENCSR299BQG/logfile.modelling.fold_1.ENCSR299BQG.stdout.txt +3 -0
  13. fold_1/logs.models.fold_1.ENCSR299BQG/logfile.modelling.fold_1.ENCSR299BQG.stdout_v1.txt +3 -0
  14. fold_1/model.bias_scaled.fold_1.ENCSR299BQG.h5 +3 -0
  15. fold_1/model.bias_scaled.fold_1.ENCSR299BQG.tar +3 -0
  16. fold_1/model.chrombpnet.fold_1.ENCSR299BQG.h5 +3 -0
  17. fold_1/model.chrombpnet.fold_1.ENCSR299BQG.tar +3 -0
  18. fold_1/model.chrombpnet_nobias.fold_1.ENCSR299BQG.h5 +3 -0
  19. fold_1/model.chrombpnet_nobias.fold_1.ENCSR299BQG.tar +3 -0
  20. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.args.json +23 -0
  21. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.bias_formatting.stderr.txt +38 -0
  22. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.bias_formatting.stdout.txt +1 -0
  23. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet.params.json +11 -0
  24. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_data_params.tsv +3 -0
  25. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_formatting.stderr.txt +40 -0
  26. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_formatting.stdout.txt +1 -0
  27. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_model_params.tsv +9 -0
  28. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  30. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.epoch_loss.csv +18 -0
  31. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.stderr.txt +328 -0
  32. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.stdout.txt +3 -0
  33. fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.stdout_v1.txt +3 -0
  34. fold_2/model.bias_scaled.fold_2.ENCSR299BQG.h5 +3 -0
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  36. fold_2/model.chrombpnet.fold_2.ENCSR299BQG.h5 +3 -0
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  41. fold_3/logs.models.fold_3.ENCSR299BQG/logfile.modelling.fold_3.ENCSR299BQG.stdout_v1.txt +3 -0
  42. fold_3/model.bias_scaled.fold_3.ENCSR299BQG.h5 +3 -0
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  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR299BQG.tar +3 -0
  48. fold_4/logs.models.fold_4.ENCSR299BQG/logfile.modelling.fold_4.ENCSR299BQG.stdout.txt +3 -0
  49. fold_4/logs.models.fold_4.ENCSR299BQG/logfile.modelling.fold_4.ENCSR299BQG.stdout_v1.txt +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR299BQG.h5 +3 -0
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+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
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+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
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+ 2023-07-17 13:01:43.400544: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
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+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
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+ 2023-07-17 13:01:43.719540: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-17 13:01:43.740925: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-17 13:01:43.741124: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-17 13:01:43.753363: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-17 13:01:43.782356: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
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+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
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+ 2023-07-17 13:01:43.858772: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-17 13:01:43.858897: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-17 13:01:43.858913: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-17 13:01:43.959405: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-17 13:01:43.961251: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-17 13:01:47.172713: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
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+ 2023-07-17 13:01:47.172826: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
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+ 2023-07-17 13:01:47.172843: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-07-17 13:01:47.179692: 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: 0000:84:00.0, compute capability: 8.0)
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+ 2023-07-17 13:01:49.818493: 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.
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+ /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.
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+ , UserWarning)
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+ "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.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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 23:38:10.255607: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-16 23:38:12.993614: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-16 23:38:12.997540: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-16 23:38:13.148060: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-16 23:38:13.148226: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-16 23:38:13.170137: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-16 23:38:13.170357: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-16 23:38:13.180990: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-16 23:38:13.186569: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-16 23:38:13.207173: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-16 23:38:13.214802: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-16 23:38:13.216653: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-16 23:38:13.225083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-16 23:38:13.225405: 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 23:38:13.226225: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-16 23:38:13.228477: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-16 23:38:13.228503: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-16 23:38:13.228530: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-16 23:38:13.228545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-16 23:38:13.228557: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-16 23:38:13.228570: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-16 23:38:13.228582: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-16 23:38:13.228593: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-16 23:38:13.228605: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-16 23:38:13.232975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-16 23:38:13.234189: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-16 23:38:16.740519: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-16 23:38:16.740715: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-16 23:38:16.740730: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-16 23:38:16.747524: 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: 0000:45:00.0, compute capability: 8.0)
38
+ 2023-07-16 23:38:17.922301: 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.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "7.6",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR299BQG//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.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 9.0
2
+ counts_sum_max_thresh 3680.0
3
+ trainings_pts_post_thresh 179249
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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 13:01:40.502190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 13:01:44.021010: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 13:01:44.025782: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-17 13:01:44.058037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
8
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
9
+ 2023-07-17 13:01:44.058138: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-17 13:01:44.087681: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-17 13:01:44.087833: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-17 13:01:44.103520: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 13:01:44.110722: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 13:01:44.136875: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 13:01:44.143367: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 13:01:44.144699: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 13:01:44.152673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 13:01:44.153134: 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 13:01:44.154203: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 13:01:44.154502: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
24
+ 2023-07-17 13:01:44.154544: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 13:01:44.154587: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 13:01:44.154612: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-17 13:01:44.154637: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-17 13:01:44.154661: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 13:01:44.154694: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 13:01:44.154719: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 13:01:44.154744: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 13:01:44.155126: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 13:01:44.156682: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 13:01:46.292606: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 13:01:46.292725: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 13:01:46.292746: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 13:01:46.296374: 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: 0000:04:00.0, compute capability: 6.0)
38
+ 2023-07-17 13:01:49.048759: 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.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 7.6
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR299BQG//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.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.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//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.epoch_loss.csv ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,1.7190160751342773,421.5097961425781,434.57379150390625,0.776383638381958,419.27374267578125,425.1741638183594
3
+ 1,0.626598060131073,400.0983581542969,404.8601379394531,0.4795469641685486,410.948974609375,414.593505859375
4
+ 2,0.5216206312179565,393.2956848144531,397.259765625,0.4113367199897766,406.1388854980469,409.26531982421875
5
+ 3,0.47729241847991943,388.6971435546875,392.3249206542969,0.4178563952445984,408.5360107421875,411.7117614746094
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+ 4,0.4461462199687958,386.5809020996094,389.9713439941406,0.3821568489074707,404.3286437988281,407.2331848144531
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+ 5,0.4282015264034271,383.07586669921875,386.3304443359375,0.3721165657043457,403.298095703125,406.1261901855469
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+ 6,0.4082212448120117,381.0652770996094,384.16845703125,0.3500646948814392,403.8447265625,406.5052490234375
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+ 7,0.3938811719417572,378.77606201171875,381.7702331542969,0.35500073432922363,403.6272888183594,406.3253173828125
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+ 8,0.3788606822490692,377.33624267578125,380.21563720703125,0.3453710675239563,405.0132751464844,407.63812255859375
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+ 9,0.3405926823616028,371.45477294921875,374.0431823730469,0.3252922296524048,402.3100891113281,404.7823181152344
12
+ 10,0.3268519341945648,367.4955139160156,369.9791564941406,0.32120537757873535,402.6747131347656,405.1159973144531
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+ 11,0.3153547942638397,364.23138427734375,366.6282958984375,0.3187396228313446,402.0372009277344,404.4595642089844
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+ 12,0.307323694229126,362.639404296875,364.97442626953125,0.3344576954841614,404.21221923828125,406.7538757324219
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+ 13,0.29572221636772156,360.7967224121094,363.0435485839844,0.3188649117946625,403.5113220214844,405.93450927734375
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+ 14,0.2884102761745453,359.3979797363281,361.59014892578125,0.3628629446029663,405.7742614746094,408.5318908691406
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+ 15,0.2708584666252136,355.46429443359375,357.5225830078125,0.32256799936294556,404.5713195800781,407.02294921875
18
+ 16,0.264458566904068,352.8078308105469,354.8179016113281,0.32504600286483765,406.7800598144531,409.2506103515625
fold_2/logs.models.fold_2.ENCSR299BQG/logfile.modelling.fold_2.ENCSR299BQG.stderr.txt ADDED
@@ -0,0 +1,328 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-10-05 01:02:12.752592: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2
+ 2022-10-05 01:08:46.674534: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
3
+ 2022-10-05 01:08:46.675924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
4
+ 2022-10-05 01:08:47.038983: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
5
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
6
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
7
+ 2022-10-05 01:08:47.039066: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
8
+ 2022-10-05 01:08:47.064308: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
9
+ 2022-10-05 01:08:47.064394: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
10
+ 2022-10-05 01:08:47.077942: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
11
+ 2022-10-05 01:08:47.084116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
12
+ 2022-10-05 01:08:47.105819: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
13
+ 2022-10-05 01:08:47.112037: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
14
+ 2022-10-05 01:08:47.113457: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
15
+ 2022-10-05 01:08:47.117898: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
16
+ 2022-10-05 01:08:47.118267: 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 01:08:47.118343: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
19
+ 2022-10-05 01:08:47.119733: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
20
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
21
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
22
+ 2022-10-05 01:08:47.119760: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
23
+ 2022-10-05 01:08:47.119777: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
24
+ 2022-10-05 01:08:47.119792: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
25
+ 2022-10-05 01:08:47.119808: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
26
+ 2022-10-05 01:08:47.119823: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
27
+ 2022-10-05 01:08:47.119838: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
28
+ 2022-10-05 01:08:47.119852: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
29
+ 2022-10-05 01:08:47.119866: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
30
+ 2022-10-05 01:08:47.122542: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
31
+ 2022-10-05 01:08:47.124117: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
32
+ 2022-10-05 01:08:48.806654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
33
+ 2022-10-05 01:08:48.806798: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
34
+ 2022-10-05 01:08:48.806812: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
35
+ 2022-10-05 01:08:48.814316: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, compute capability: 8.0)
36
+ 2022-10-05 01:08:50.289118: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
37
+ 2022-10-05 01:08:50.298071: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
38
+ 2022-10-05 01:08:50.477812: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
39
+ 2022-10-05 01:08:52.010575: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
40
+ 2022-10-05 01:08:52.019706: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
41
+ 2022-10-05 01:09:24.883462: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
42
+ 2022-10-05 01:09:26.496234: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
43
+ 2022-10-05 01:09:26.497162: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
44
+ 2022-10-05 01:09:26.735619: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
45
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
46
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
47
+ 2022-10-05 01:09:26.735722: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
48
+ 2022-10-05 01:09:26.737992: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
49
+ 2022-10-05 01:09:26.738046: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
50
+ 2022-10-05 01:09:26.739061: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
51
+ 2022-10-05 01:09:26.739255: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
52
+ 2022-10-05 01:09:26.741616: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
53
+ 2022-10-05 01:09:26.742128: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
54
+ 2022-10-05 01:09:26.742270: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
55
+ 2022-10-05 01:09:26.744057: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
56
+ 2022-10-05 01:09:26.744385: 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 01:09:26.744459: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
59
+ 2022-10-05 01:09:26.745339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
60
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
61
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
62
+ 2022-10-05 01:09:26.745383: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
63
+ 2022-10-05 01:09:26.745401: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
64
+ 2022-10-05 01:09:26.745415: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
65
+ 2022-10-05 01:09:26.745429: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
66
+ 2022-10-05 01:09:26.745443: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
67
+ 2022-10-05 01:09:26.745456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
68
+ 2022-10-05 01:09:26.745469: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
69
+ 2022-10-05 01:09:26.745482: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
70
+ 2022-10-05 01:09:26.747130: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
71
+ 2022-10-05 01:09:26.747168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
72
+ 2022-10-05 01:09:27.240661: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
73
+ 2022-10-05 01:09:27.240781: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
74
+ 2022-10-05 01:09:27.240794: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
75
+ 2022-10-05 01:09:27.243688: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, compute capability: 8.0)
76
+ 2022-10-05 01:15:43.062601: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
77
+ 2022-10-05 01:15:43.063050: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
78
+ 2022-10-05 01:15:44.527406: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
79
+ 2022-10-05 01:15:45.014413: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
80
+ 2022-10-05 01:15:45.030964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
81
+ 2022-10-05 01:15:48.587283: 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 03:15:07.690800: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
83
+ 2022-10-05 03:15:10.390790: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
84
+ 2022-10-05 03:15:10.391891: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
85
+ 2022-10-05 03:15:10.760575: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
86
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
87
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
88
+ 2022-10-05 03:15:10.760696: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
89
+ 2022-10-05 03:15:10.763021: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
90
+ 2022-10-05 03:15:10.763094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
91
+ 2022-10-05 03:15:10.764185: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
92
+ 2022-10-05 03:15:10.764377: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
93
+ 2022-10-05 03:15:10.766780: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
94
+ 2022-10-05 03:15:10.767307: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
95
+ 2022-10-05 03:15:10.767448: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
96
+ 2022-10-05 03:15:10.770755: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
97
+ 2022-10-05 03:15:10.771099: 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 03:15:10.771181: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
100
+ 2022-10-05 03:15:10.772816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
101
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
102
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
103
+ 2022-10-05 03:15:10.772841: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
104
+ 2022-10-05 03:15:10.772859: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
105
+ 2022-10-05 03:15:10.772875: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
106
+ 2022-10-05 03:15:10.772889: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
107
+ 2022-10-05 03:15:10.772903: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
108
+ 2022-10-05 03:15:10.772916: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
109
+ 2022-10-05 03:15:10.772930: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
110
+ 2022-10-05 03:15:10.772943: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
111
+ 2022-10-05 03:15:10.776062: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
112
+ 2022-10-05 03:15:10.776096: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
113
+ 2022-10-05 03:15:11.367655: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
114
+ 2022-10-05 03:15:11.367772: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
115
+ 2022-10-05 03:15:11.367784: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
116
+ 2022-10-05 03:15:11.371058: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, compute capability: 8.0)
117
+ 2022-10-05 03:16:40.338969: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
118
+ 2022-10-05 03:16:40.342594: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
119
+ 2022-10-05 03:16:40.430513: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
120
+ 2022-10-05 03:16:40.960177: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
121
+ 2022-10-05 03:16:40.962509: 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 03:18:43.062491: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
139
+ 2022-10-05 03:18:45.470740: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
140
+ 2022-10-05 03:18:45.471804: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
141
+ 2022-10-05 03:18:45.785185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
142
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
143
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
144
+ 2022-10-05 03:18:45.785309: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
145
+ 2022-10-05 03:18:45.787658: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
146
+ 2022-10-05 03:18:45.787733: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
147
+ 2022-10-05 03:18:45.788776: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
148
+ 2022-10-05 03:18:45.788969: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
149
+ 2022-10-05 03:18:45.791402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
150
+ 2022-10-05 03:18:45.791928: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
151
+ 2022-10-05 03:18:45.792066: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
152
+ 2022-10-05 03:18:45.794291: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
153
+ 2022-10-05 03:18:45.794625: 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 03:18:45.794727: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
156
+ 2022-10-05 03:18:45.795757: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
157
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
158
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
159
+ 2022-10-05 03:18:45.795781: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
160
+ 2022-10-05 03:18:45.795800: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
161
+ 2022-10-05 03:18:45.795815: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
162
+ 2022-10-05 03:18:45.795829: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
163
+ 2022-10-05 03:18:45.795843: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
164
+ 2022-10-05 03:18:45.795856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
165
+ 2022-10-05 03:18:45.795870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
166
+ 2022-10-05 03:18:45.795885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
167
+ 2022-10-05 03:18:45.797832: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
168
+ 2022-10-05 03:18:45.797862: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
169
+ 2022-10-05 03:18:46.320731: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
170
+ 2022-10-05 03:18:46.320862: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
171
+ 2022-10-05 03:18:46.320874: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
172
+ 2022-10-05 03:18:46.324470: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, 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 03:20:05.287703: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
175
+ 2022-10-05 03:20:05.290221: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
176
+ 2022-10-05 03:20:05.349392: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
177
+ 2022-10-05 03:20:05.878518: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
178
+ 2022-10-05 03:20:05.880170: 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 03:21:58.708221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
194
+ 2022-10-05 03:22:01.122700: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
195
+ 2022-10-05 03:22:01.123726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
196
+ 2022-10-05 03:22:01.494509: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
197
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
198
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
199
+ 2022-10-05 03:22:01.494629: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
200
+ 2022-10-05 03:22:01.496970: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
201
+ 2022-10-05 03:22:01.497037: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
202
+ 2022-10-05 03:22:01.498068: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
203
+ 2022-10-05 03:22:01.498262: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
204
+ 2022-10-05 03:22:01.500645: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
205
+ 2022-10-05 03:22:01.501187: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
206
+ 2022-10-05 03:22:01.501331: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
207
+ 2022-10-05 03:22:01.504154: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
208
+ 2022-10-05 03:22:01.504488: 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 03:22:01.504566: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
211
+ 2022-10-05 03:22:01.505933: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
212
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
213
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
214
+ 2022-10-05 03:22:01.505957: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
215
+ 2022-10-05 03:22:01.505977: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
216
+ 2022-10-05 03:22:01.505994: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
217
+ 2022-10-05 03:22:01.506035: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
218
+ 2022-10-05 03:22:01.506052: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
219
+ 2022-10-05 03:22:01.506068: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
220
+ 2022-10-05 03:22:01.506083: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
221
+ 2022-10-05 03:22:01.506099: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
222
+ 2022-10-05 03:22:01.508690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
223
+ 2022-10-05 03:22:01.508720: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
224
+ 2022-10-05 03:22:02.044737: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
225
+ 2022-10-05 03:22:02.044865: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
226
+ 2022-10-05 03:22:02.044878: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
227
+ 2022-10-05 03:22:02.048510: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, compute capability: 8.0)
228
+ 2022-10-05 03:23:20.406000: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
229
+ 2022-10-05 03:23:20.407879: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
230
+ 2022-10-05 03:23:20.446981: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
231
+ 2022-10-05 03:23:20.974457: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
232
+ 2022-10-05 03:23:20.976129: 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 03:24:21.677327: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
248
+ 2022-10-05 03:24:22.864918: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
249
+ 2022-10-05 03:24:22.865901: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
250
+ 2022-10-05 03:24:23.174595: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
251
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
252
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
253
+ 2022-10-05 03:24:23.174718: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
254
+ 2022-10-05 03:24:23.177018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
255
+ 2022-10-05 03:24:23.177084: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
256
+ 2022-10-05 03:24:23.178111: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
257
+ 2022-10-05 03:24:23.178310: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
258
+ 2022-10-05 03:24:23.180713: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
259
+ 2022-10-05 03:24:23.181239: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
260
+ 2022-10-05 03:24:23.181377: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
261
+ 2022-10-05 03:24:23.183193: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
262
+ 2022-10-05 03:24:23.183538: 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 03:24:23.183615: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
265
+ 2022-10-05 03:24:23.184477: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
266
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
267
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
268
+ 2022-10-05 03:24:23.184506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
269
+ 2022-10-05 03:24:23.184526: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
270
+ 2022-10-05 03:24:23.184542: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
271
+ 2022-10-05 03:24:23.184558: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
272
+ 2022-10-05 03:24:23.184574: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
273
+ 2022-10-05 03:24:23.184590: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
274
+ 2022-10-05 03:24:23.184605: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
275
+ 2022-10-05 03:24:23.184620: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
276
+ 2022-10-05 03:24:23.186261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
277
+ 2022-10-05 03:24:23.186299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
278
+ 2022-10-05 03:24:23.707301: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
279
+ 2022-10-05 03:24:23.707446: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
280
+ 2022-10-05 03:24:23.707460: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
281
+ 2022-10-05 03:24:23.711132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, 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 03:24:41.485214: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
284
+ 2022-10-05 03:24:41.485805: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
285
+ 2022-10-05 03:24:41.690278: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
286
+ 2022-10-05 03:24:42.264455: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
287
+ 2022-10-05 03:24:42.266306: 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/ENCSR299BQG//chrombppnet_model_encsr283tme_bias_fold_2//footprints’: File exists
289
+ 2022-10-05 03:26:25.628757: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
290
+ 2022-10-05 03:26:26.802447: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
291
+ 2022-10-05 03:26:26.803482: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
292
+ 2022-10-05 03:26:27.106892: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
293
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
294
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
295
+ 2022-10-05 03:26:27.107017: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
296
+ 2022-10-05 03:26:27.109349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
297
+ 2022-10-05 03:26:27.109410: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
298
+ 2022-10-05 03:26:27.110463: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
299
+ 2022-10-05 03:26:27.110656: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
300
+ 2022-10-05 03:26:27.113027: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
301
+ 2022-10-05 03:26:27.113555: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
302
+ 2022-10-05 03:26:27.113695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
303
+ 2022-10-05 03:26:27.115641: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
304
+ 2022-10-05 03:26:27.115979: 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 03:26:27.116065: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
307
+ 2022-10-05 03:26:27.116962: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
308
+ pciBusID: 0000:87:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
309
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.45GiB deviceMemoryBandwidth: 1.41TiB/s
310
+ 2022-10-05 03:26:27.117017: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
311
+ 2022-10-05 03:26:27.117036: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
312
+ 2022-10-05 03:26:27.117052: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
313
+ 2022-10-05 03:26:27.117067: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
314
+ 2022-10-05 03:26:27.117082: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
315
+ 2022-10-05 03:26:27.117097: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
316
+ 2022-10-05 03:26:27.117112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
317
+ 2022-10-05 03:26:27.117127: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
318
+ 2022-10-05 03:26:27.118797: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
319
+ 2022-10-05 03:26:27.118835: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
320
+ 2022-10-05 03:26:27.623488: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
321
+ 2022-10-05 03:26:27.623619: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
322
+ 2022-10-05 03:26:27.623631: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
323
+ 2022-10-05 03:26:27.627434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37440 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:87:00.0, compute capability: 8.0)
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+ 2022-10-05 03:26:44.037645: 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 03:26:44.038237: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2000015000 Hz
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+ 2022-10-05 03:26:44.737172: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2022-10-05 03:26:44.738924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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