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kundajelab
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encode-chrombpnet-DNASE-activated-CD4-positive-CD25-positive-ENCSR242CLA-ENCSR151JCL

chrombpnet
encode
chromatin-accessibility
DNASE
t-cell
hg38
Model card Files
xet
 Community
chang-m-yun commited on
Commit
097f712
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verified ·
1 Parent(s): b64de4b

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  1. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.args.json +23 -0
  2. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.bias_formatting.stderr.txt +38 -0
  4. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.bias_formatting.stdout.txt +1 -0
  5. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet.params.json +11 -0
  6. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_data_params.tsv +3 -0
  7. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_formatting.stderr.txt +40 -0
  8. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_model_params.tsv +9 -0
  9. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  10. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  11. fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.epoch_loss.csv +13 -0
  12. fold_0/model.bias_scaled.fold_0.ENCSR242CLA.h5 +3 -0
  13. fold_0/model.bias_scaled.fold_0.ENCSR242CLA.tar +3 -0
  14. fold_0/model.chrombpnet.fold_0.ENCSR242CLA.h5 +3 -0
  15. fold_0/model.chrombpnet.fold_0.ENCSR242CLA.tar +3 -0
  16. fold_0/model.chrombpnet_nobias.fold_0.ENCSR242CLA.h5 +3 -0
  17. fold_0/model.chrombpnet_nobias.fold_0.ENCSR242CLA.tar +3 -0
  18. fold_1/model.bias_scaled.fold_1.ENCSR242CLA.h5 +3 -0
  19. fold_1/model.bias_scaled.fold_1.ENCSR242CLA.tar +3 -0
  20. fold_1/model.chrombpnet.fold_1.ENCSR242CLA.h5 +3 -0
  21. fold_1/model.chrombpnet.fold_1.ENCSR242CLA.tar +3 -0
  22. fold_1/model.chrombpnet_nobias.fold_1.ENCSR242CLA.h5 +3 -0
  23. fold_1/model.chrombpnet_nobias.fold_1.ENCSR242CLA.tar +3 -0
  24. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.args.json +23 -0
  25. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.bias_formatting.stderr.txt +38 -0
  26. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.bias_formatting.stdout.txt +1 -0
  27. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet.params.json +11 -0
  28. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_data_params.tsv +3 -0
  29. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_formatting.stderr.txt +40 -0
  30. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_formatting.stdout.txt +1 -0
  31. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_model_params.tsv +9 -0
  32. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  34. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.epoch_loss.csv +12 -0
  35. fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.stderr.txt +328 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR242CLA.h5 +3 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR242CLA.tar +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR242CLA.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR242CLA.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR242CLA.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR242CLA.tar +3 -0
  42. fold_3/logs.models.fold_3.ENCSR242CLA/logfile.modelling.fold_3.ENCSR242CLA.stdout.txt +0 -0
  43. fold_3/model.bias_scaled.fold_3.ENCSR242CLA.h5 +3 -0
  44. fold_3/model.bias_scaled.fold_3.ENCSR242CLA.tar +3 -0
  45. fold_3/model.chrombpnet.fold_3.ENCSR242CLA.h5 +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR242CLA.tar +3 -0
  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR242CLA.h5 +3 -0
  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR242CLA.tar +3 -0
  49. fold_4/model.bias_scaled.fold_4.ENCSR242CLA.h5 +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR242CLA.tar +3 -0
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.args.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "genome": "reference/hg38.genome.fa",
3
+ "bigwig": "data/ENCSR242CLA.bigWig",
4
+ "peaks": "chrombppnet_model_encsr283tme_bias//filtered.peaks.bed",
5
+ "nonpeaks": "chrombppnet_model_encsr283tme_bias//filtered.nonpeaks.bed",
6
+ "output_prefix": "chrombppnet_model_encsr283tme_bias//chrombpnet",
7
+ "chr_fold_path": "splits/fold_0.json",
8
+ "trackables": [
9
+ "logcount_predictions_loss",
10
+ "loss",
11
+ "logits_profile_predictions_loss",
12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
15
+ ],
16
+ "epochs": 50,
17
+ "early_stop": 5,
18
+ "batch_size": 64,
19
+ "learning_rate": 0.001,
20
+ "params": "chrombppnet_model_encsr283tme_bias//chrombpnet_model_params.tsv",
21
+ "seed": 1234,
22
+ "architecture_from_file": "/scratch/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
+ }
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 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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+ 2023-07-16 23:31:40.163528: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-16 23:31:43.375072: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-16 23:31:43.379565: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-16 23:31:43.405424: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:03:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
8
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
9
+ 2023-07-16 23:31:43.405486: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-16 23:31:43.433472: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-16 23:31:43.433597: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-16 23:31:43.448054: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-16 23:31:43.454576: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-16 23:31:43.478508: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-16 23:31:43.484606: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-16 23:31:43.485870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-16 23:31:43.487827: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-16 23:31:43.488186: 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 23:31:43.489103: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-16 23:31:43.501307: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:03:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
24
+ 2023-07-16 23:31:43.501431: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-16 23:31:43.501490: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-16 23:31:43.501514: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-16 23:31:43.501537: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-16 23:31:43.501560: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-16 23:31:43.501583: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-16 23:31:43.501605: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-16 23:31:43.501628: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-16 23:31:43.502142: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-16 23:31:43.503661: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-16 23:31:45.534815: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-16 23:31:45.534907: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-16 23:31:45.534926: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-16 23:31:45.558529: 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: 0000:03:00.0, compute capability: 6.0)
38
+ 2023-07-16 23:31:46.470342: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias/new_model_formats/bias_model_scaled
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "13.0",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5",
6
+ "inputlen": "2114",
7
+ "outputlen": "1000",
8
+ "max_jitter": "500",
9
+ "chr_fold_path": "splits/fold_0.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 12.0
2
+ counts_sum_max_thresh 4248.79
3
+ trainings_pts_post_thresh 169548
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.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 12:49:45.022194: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 12:49:47.794516: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 12:49:47.798224: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-17 12:49:48.009285: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.39GiB deviceMemoryBandwidth: 1.41TiB/s
9
+ 2023-07-17 12:49:48.009343: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-17 12:49:48.031580: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-17 12:49:48.031695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-17 12:49:48.043025: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 12:49:48.048802: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 12:49:48.069157: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 12:49:48.074269: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 12:49:48.075358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 12:49:48.087361: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 12:49:48.087739: 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 12:49:48.088993: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 12:49:48.113149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.39GiB deviceMemoryBandwidth: 1.41TiB/s
24
+ 2023-07-17 12:49:48.113212: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 12:49:48.113253: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 12:49:48.113282: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-17 12:49:48.113329: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-17 12:49:48.113358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 12:49:48.113385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 12:49:48.113412: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 12:49:48.113439: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 12:49:48.128855: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 12:49:48.131458: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 12:49:49.964016: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 12:49:49.964125: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 12:49:49.964140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 12:49:49.972230: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37381 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-PCIE-40GB, pci bus id: 0000:07:00.0, compute capability: 8.0)
38
+ 2023-07-17 12:49:52.142738: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
39
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
40
+ , UserWarning)
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 13.0
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5
5
+ inputlen 2114
6
+ outputlen 1000
7
+ max_jitter 500
8
+ chr_fold_path splits/fold_0.json
9
+ negative_sampling_ratio 0.1
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR242CLA/logfile.modelling.fold_0.ENCSR242CLA.chrombpnet_no_bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
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+ {
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+ "logcount_predictions_loss",
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fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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 23:31:40.128274: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-16 23:31:43.354374: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-16 23:31:43.360168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-16 23:31:43.396972: 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
+ 2023-07-16 23:31:43.397081: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-16 23:31:43.426454: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-16 23:31:43.426616: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-16 23:31:43.441604: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-16 23:31:43.448172: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-16 23:31:43.472693: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-16 23:31:43.478572: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-16 23:31:43.479917: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-16 23:31:43.481819: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-16 23:31:43.482188: 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
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21
+ 2023-07-16 23:31:43.483419: 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
+ 2023-07-16 23:31:43.483452: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "13.0",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR242CLA//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.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 14.0
2
+ counts_sum_max_thresh 4235.0
3
+ trainings_pts_post_thresh 179238
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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 12:49:48.500403: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 12:49:53.566539: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
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6
+ 2023-07-17 12:49:53.596600: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:45:00.0 name: NVIDIA GeForce RTX 3090 computeCapability: 8.6
8
+ coreClock: 1.695GHz coreCount: 82 deviceMemorySize: 23.69GiB deviceMemoryBandwidth: 871.81GiB/s
9
+ 2023-07-17 12:49:53.596704: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
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11
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12
+ 2023-07-17 12:49:53.701553: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-17 12:49:53.790934: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-17 12:49:53.865653: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-17 12:49:53.890309: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-17 12:49:53.894791: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-17 12:49:53.897286: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 12:49:53.897670: 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 12:49:53.897774: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 12:49:53.898183: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:45:00.0 name: NVIDIA GeForce RTX 3090 computeCapability: 8.6
23
+ coreClock: 1.695GHz coreCount: 82 deviceMemorySize: 23.69GiB deviceMemoryBandwidth: 871.81GiB/s
24
+ 2023-07-17 12:49:53.898215: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
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26
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27
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28
+ 2023-07-17 12:49:53.898299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-17 12:49:53.898318: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 12:49:53.898336: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 12:49:53.898363: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 12:49:53.898980: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-17 12:49:53.901911: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-17 12:49:56.711950: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
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36
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37
+ 2023-07-17 12:49:56.715432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 22421 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:45:00.0, compute capability: 8.6)
38
+ 2023-07-17 12:49:58.763382: 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.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 13.0
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR242CLA//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.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.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//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.epoch_loss.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,1.0287328958511353,647.9010009765625,661.2728881835938,0.4764181673526764,666.4458618164062,672.6392822265625
3
+ 1,0.47433480620384216,622.9020385742188,629.0684814453125,0.4417632222175598,659.5077514648438,665.2506713867188
4
+ 2,0.4307745695114136,617.6201171875,623.2202758789062,0.38156673312187195,651.557861328125,656.5173950195312
5
+ 3,0.4050230085849762,613.00537109375,618.2703857421875,0.36746400594711304,653.3897094726562,658.167236328125
6
+ 4,0.38016775250434875,610.70068359375,615.6441650390625,0.3684902787208557,650.330322265625,655.1207275390625
7
+ 5,0.37137851119041443,607.8301391601562,612.6572265625,0.37207433581352234,648.069580078125,652.9066772460938
8
+ 6,0.358430951833725,605.7765502929688,610.4371948242188,0.34865880012512207,655.1749877929688,659.7074584960938
9
+ 7,0.3503694236278534,604.126708984375,608.6806030273438,0.4184098243713379,654.5783081054688,660.0174560546875
10
+ 8,0.3418841063976288,602.08251953125,606.52685546875,0.369803786277771,657.7201538085938,662.5274047851562
11
+ 9,0.3089928925037384,593.8406372070312,597.857421875,0.3539661169052124,653.4658813476562,658.0676879882812
12
+ 10,0.29421770572662354,590.0775146484375,593.9020385742188,0.3534355163574219,653.7476196289062,658.34228515625
fold_2/logs.models.fold_2.ENCSR242CLA/logfile.modelling.fold_2.ENCSR242CLA.stderr.txt ADDED
@@ -0,0 +1,328 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2022-10-05 10:16:11.718547: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2
+ 2022-10-05 10:21:35.976514: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
3
+ 2022-10-05 10:21:35.978606: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
4
+ 2022-10-05 10:21:36.392447: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
5
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
6
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
7
+ 2022-10-05 10:21:36.392617: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
8
+ 2022-10-05 10:21:36.419446: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
9
+ 2022-10-05 10:21:36.419500: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
10
+ 2022-10-05 10:21:36.432257: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
11
+ 2022-10-05 10:21:36.438098: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
12
+ 2022-10-05 10:21:36.457911: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
13
+ 2022-10-05 10:21:36.463469: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
14
+ 2022-10-05 10:21:36.464774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
15
+ 2022-10-05 10:21:36.472425: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
16
+ 2022-10-05 10:21:36.472805: 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 10:21:36.472926: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
19
+ 2022-10-05 10:21:36.478806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
20
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
21
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
22
+ 2022-10-05 10:21:36.478844: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
23
+ 2022-10-05 10:21:36.478867: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
24
+ 2022-10-05 10:21:36.478885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
25
+ 2022-10-05 10:21:36.478903: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
26
+ 2022-10-05 10:21:36.478920: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
27
+ 2022-10-05 10:21:36.478936: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
28
+ 2022-10-05 10:21:36.478953: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
29
+ 2022-10-05 10:21:36.478969: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
30
+ 2022-10-05 10:21:36.488533: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
31
+ 2022-10-05 10:21:36.490710: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
32
+ 2022-10-05 10:21:38.621971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
33
+ 2022-10-05 10:21:38.622083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
34
+ 2022-10-05 10:21:38.622098: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
35
+ 2022-10-05 10:21:38.628919: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, compute capability: 8.0)
36
+ 2022-10-05 10:21:40.307927: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
37
+ 2022-10-05 10:21:40.318207: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
38
+ 2022-10-05 10:21:40.494644: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
39
+ 2022-10-05 10:21:42.118532: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
40
+ 2022-10-05 10:21:42.126677: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
41
+ 2022-10-05 10:22:13.561585: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
42
+ 2022-10-05 10:22:15.174062: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
43
+ 2022-10-05 10:22:15.175427: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
44
+ 2022-10-05 10:22:16.148114: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
45
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
46
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
47
+ 2022-10-05 10:22:16.148279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
48
+ 2022-10-05 10:22:16.151478: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
49
+ 2022-10-05 10:22:16.151564: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
50
+ 2022-10-05 10:22:16.152896: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
51
+ 2022-10-05 10:22:16.153157: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
52
+ 2022-10-05 10:22:16.156077: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
53
+ 2022-10-05 10:22:16.156753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
54
+ 2022-10-05 10:22:16.156918: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
55
+ 2022-10-05 10:22:16.163033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
56
+ 2022-10-05 10:22:16.163342: 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 10:22:16.163444: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
59
+ 2022-10-05 10:22:16.183108: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
60
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
61
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
62
+ 2022-10-05 10:22:16.183358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
63
+ 2022-10-05 10:22:16.183412: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
64
+ 2022-10-05 10:22:16.183434: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
65
+ 2022-10-05 10:22:16.183454: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
66
+ 2022-10-05 10:22:16.183473: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
67
+ 2022-10-05 10:22:16.183492: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
68
+ 2022-10-05 10:22:16.183511: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
69
+ 2022-10-05 10:22:16.183531: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
70
+ 2022-10-05 10:22:16.188141: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
71
+ 2022-10-05 10:22:16.188194: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
72
+ 2022-10-05 10:22:16.967185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
73
+ 2022-10-05 10:22:16.967389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
74
+ 2022-10-05 10:22:16.967404: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
75
+ 2022-10-05 10:22:16.971006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, compute capability: 8.0)
76
+ 2022-10-05 10:27:43.860958: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
77
+ 2022-10-05 10:27:43.861476: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
78
+ 2022-10-05 10:27:45.343490: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
79
+ 2022-10-05 10:27:46.752695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
80
+ 2022-10-05 10:27:46.770251: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
81
+ 2022-10-05 10:27:50.157306: 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 11:39:22.201607: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
83
+ 2022-10-05 11:39:24.756301: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
84
+ 2022-10-05 11:39:24.757302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
85
+ 2022-10-05 11:39:25.111039: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
86
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
87
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
88
+ 2022-10-05 11:39:25.111198: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
89
+ 2022-10-05 11:39:25.113679: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
90
+ 2022-10-05 11:39:25.113741: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
91
+ 2022-10-05 11:39:25.114794: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
92
+ 2022-10-05 11:39:25.114986: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
93
+ 2022-10-05 11:39:25.117261: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
94
+ 2022-10-05 11:39:25.117765: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
95
+ 2022-10-05 11:39:25.117902: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
96
+ 2022-10-05 11:39:25.119650: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
97
+ 2022-10-05 11:39:25.119954: 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 11:39:25.120052: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
100
+ 2022-10-05 11:39:25.121394: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
101
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
102
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
103
+ 2022-10-05 11:39:25.121421: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
104
+ 2022-10-05 11:39:25.121441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
105
+ 2022-10-05 11:39:25.121456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
106
+ 2022-10-05 11:39:25.121470: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
107
+ 2022-10-05 11:39:25.121484: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
108
+ 2022-10-05 11:39:25.121498: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
109
+ 2022-10-05 11:39:25.121511: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
110
+ 2022-10-05 11:39:25.121524: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
111
+ 2022-10-05 11:39:25.123189: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
112
+ 2022-10-05 11:39:25.123227: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
113
+ 2022-10-05 11:39:25.606892: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
114
+ 2022-10-05 11:39:25.607045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
115
+ 2022-10-05 11:39:25.607060: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
116
+ 2022-10-05 11:39:25.609987: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, compute capability: 8.0)
117
+ 2022-10-05 11:40:36.402801: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
118
+ 2022-10-05 11:40:36.406011: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
119
+ 2022-10-05 11:40:36.484800: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
120
+ 2022-10-05 11:40:37.187425: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
121
+ 2022-10-05 11:40:37.189718: 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 11:42:29.449012: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
139
+ 2022-10-05 11:42:31.668922: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
140
+ 2022-10-05 11:42:31.669913: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
141
+ 2022-10-05 11:42:31.981249: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
142
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
143
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
144
+ 2022-10-05 11:42:31.981369: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
145
+ 2022-10-05 11:42:31.984745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
146
+ 2022-10-05 11:42:31.984842: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
147
+ 2022-10-05 11:42:31.986410: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
148
+ 2022-10-05 11:42:31.986755: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
149
+ 2022-10-05 11:42:31.990324: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
150
+ 2022-10-05 11:42:31.990955: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
151
+ 2022-10-05 11:42:31.991100: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
152
+ 2022-10-05 11:42:31.992829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
153
+ 2022-10-05 11:42:31.993121: 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 11:42:31.993251: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
156
+ 2022-10-05 11:42:31.994144: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
157
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
158
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
159
+ 2022-10-05 11:42:31.994169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
160
+ 2022-10-05 11:42:31.994189: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
161
+ 2022-10-05 11:42:31.994206: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
162
+ 2022-10-05 11:42:31.994222: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
163
+ 2022-10-05 11:42:31.994238: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
164
+ 2022-10-05 11:42:31.994253: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
165
+ 2022-10-05 11:42:31.994268: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
166
+ 2022-10-05 11:42:31.994283: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
167
+ 2022-10-05 11:42:31.995942: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
168
+ 2022-10-05 11:42:31.995978: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
169
+ 2022-10-05 11:42:32.481174: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
170
+ 2022-10-05 11:42:32.481345: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
171
+ 2022-10-05 11:42:32.481359: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
172
+ 2022-10-05 11:42:32.484248: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, 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 11:43:30.055227: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
175
+ 2022-10-05 11:43:30.057477: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
176
+ 2022-10-05 11:43:30.110371: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
177
+ 2022-10-05 11:43:30.630694: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
178
+ 2022-10-05 11:43:30.632439: 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 11:45:16.153100: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
194
+ 2022-10-05 11:45:18.428284: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
195
+ 2022-10-05 11:45:18.429297: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
196
+ 2022-10-05 11:45:18.931514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
197
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
198
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
199
+ 2022-10-05 11:45:18.931695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
200
+ 2022-10-05 11:45:18.934490: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
201
+ 2022-10-05 11:45:18.934560: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
202
+ 2022-10-05 11:45:18.935740: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
203
+ 2022-10-05 11:45:18.935974: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
204
+ 2022-10-05 11:45:18.938808: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
205
+ 2022-10-05 11:45:18.939382: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
206
+ 2022-10-05 11:45:18.939548: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
207
+ 2022-10-05 11:45:18.955103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
208
+ 2022-10-05 11:45:18.955579: 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 11:45:18.955832: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
211
+ 2022-10-05 11:45:18.960506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
212
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
213
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
214
+ 2022-10-05 11:45:18.960547: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
215
+ 2022-10-05 11:45:18.960583: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
216
+ 2022-10-05 11:45:18.960628: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
217
+ 2022-10-05 11:45:18.960688: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
218
+ 2022-10-05 11:45:18.960711: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
219
+ 2022-10-05 11:45:18.960732: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
220
+ 2022-10-05 11:45:18.960753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
221
+ 2022-10-05 11:45:18.960774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
222
+ 2022-10-05 11:45:18.966047: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
223
+ 2022-10-05 11:45:18.966113: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
224
+ 2022-10-05 11:45:19.568029: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
225
+ 2022-10-05 11:45:19.568204: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
226
+ 2022-10-05 11:45:19.568218: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
227
+ 2022-10-05 11:45:19.571176: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, compute capability: 8.0)
228
+ 2022-10-05 11:46:17.841538: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
229
+ 2022-10-05 11:46:17.843221: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
230
+ 2022-10-05 11:46:17.878743: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
231
+ 2022-10-05 11:46:18.566803: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
232
+ 2022-10-05 11:46:18.568441: 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 11:47:16.445512: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
248
+ 2022-10-05 11:47:17.619720: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
249
+ 2022-10-05 11:47:17.620691: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
250
+ 2022-10-05 11:47:17.873490: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
251
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
252
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
253
+ 2022-10-05 11:47:17.873710: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
254
+ 2022-10-05 11:47:17.877332: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
255
+ 2022-10-05 11:47:17.877452: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
256
+ 2022-10-05 11:47:17.879102: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
257
+ 2022-10-05 11:47:17.879456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
258
+ 2022-10-05 11:47:17.882212: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
259
+ 2022-10-05 11:47:17.882687: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
260
+ 2022-10-05 11:47:17.882828: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
261
+ 2022-10-05 11:47:17.885751: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
262
+ 2022-10-05 11:47:17.886058: 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 11:47:17.886173: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
265
+ 2022-10-05 11:47:17.887062: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
266
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
267
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
268
+ 2022-10-05 11:47:17.887093: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
269
+ 2022-10-05 11:47:17.887112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
270
+ 2022-10-05 11:47:17.887126: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
271
+ 2022-10-05 11:47:17.887141: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
272
+ 2022-10-05 11:47:17.887154: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
273
+ 2022-10-05 11:47:17.887169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
274
+ 2022-10-05 11:47:17.887182: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
275
+ 2022-10-05 11:47:17.887196: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
276
+ 2022-10-05 11:47:17.888884: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
277
+ 2022-10-05 11:47:17.888959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
278
+ 2022-10-05 11:47:18.425769: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
279
+ 2022-10-05 11:47:18.425972: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
280
+ 2022-10-05 11:47:18.425988: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
281
+ 2022-10-05 11:47:18.428824: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, 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 11:47:32.484448: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
284
+ 2022-10-05 11:47:32.484995: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
285
+ 2022-10-05 11:47:32.762539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
286
+ 2022-10-05 11:47:33.621376: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
287
+ 2022-10-05 11:47:33.623407: 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/ENCSR242CLA//chrombppnet_model_encsr283tme_bias_fold_2//footprints’: File exists
289
+ 2022-10-05 11:49:21.757156: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
290
+ 2022-10-05 11:49:22.907429: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
291
+ 2022-10-05 11:49:22.908331: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
292
+ 2022-10-05 11:49:23.174961: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
293
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
294
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
295
+ 2022-10-05 11:49:23.175121: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
296
+ 2022-10-05 11:49:23.177627: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
297
+ 2022-10-05 11:49:23.177681: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
298
+ 2022-10-05 11:49:23.178723: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
299
+ 2022-10-05 11:49:23.178918: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
300
+ 2022-10-05 11:49:23.181243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
301
+ 2022-10-05 11:49:23.181755: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
302
+ 2022-10-05 11:49:23.181891: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
303
+ 2022-10-05 11:49:23.184287: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
304
+ 2022-10-05 11:49:23.184613: 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 11:49:23.184710: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
307
+ 2022-10-05 11:49:23.185620: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
308
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
309
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
310
+ 2022-10-05 11:49:23.185684: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
311
+ 2022-10-05 11:49:23.185705: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
312
+ 2022-10-05 11:49:23.185721: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
313
+ 2022-10-05 11:49:23.185737: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
314
+ 2022-10-05 11:49:23.185752: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
315
+ 2022-10-05 11:49:23.185767: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
316
+ 2022-10-05 11:49:23.185782: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
317
+ 2022-10-05 11:49:23.185796: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
318
+ 2022-10-05 11:49:23.187441: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
319
+ 2022-10-05 11:49:23.187486: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
320
+ 2022-10-05 11:49:23.679655: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
321
+ 2022-10-05 11:49:23.679829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
322
+ 2022-10-05 11:49:23.679843: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
323
+ 2022-10-05 11:49:23.682673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:84:00.0, compute capability: 8.0)
324
+ 2022-10-05 11:49:37.593983: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
325
+ 2022-10-05 11:49:37.594563: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
326
+ 2022-10-05 11:49:37.731232: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
327
+ 2022-10-05 11:49:38.351957: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
328
+ 2022-10-05 11:49:38.368407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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