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encode-chrombpnet-DNASE-heart-right-ventricle-ENCSR211SUT-ENCSR215KHF

chrombpnet
encode
chromatin-accessibility
DNASE
heart
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +6 -0
  2. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.bias_formatting.stderr.txt +38 -0
  4. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.bias_formatting.stdout.txt +1 -0
  5. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.chrombpnet_fix_formatting.stderr.txt +42 -0
  6. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  7. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.stdout_v1.txt +3 -0
  9. fold_0/model.bias_scaled.fold_0.ENCSR211SUT.h5 +3 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR211SUT.tar +3 -0
  11. fold_0/model.chrombpnet.fold_0.ENCSR211SUT.h5 +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR211SUT.tar +3 -0
  13. fold_0/model.chrombpnet_nobias.fold_0.ENCSR211SUT.h5 +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR211SUT.tar +3 -0
  15. fold_1/model.bias_scaled.fold_1.ENCSR211SUT.h5 +3 -0
  16. fold_1/model.bias_scaled.fold_1.ENCSR211SUT.tar +3 -0
  17. fold_1/model.chrombpnet.fold_1.ENCSR211SUT.h5 +3 -0
  18. fold_1/model.chrombpnet.fold_1.ENCSR211SUT.tar +3 -0
  19. fold_1/model.chrombpnet_nobias.fold_1.ENCSR211SUT.h5 +3 -0
  20. fold_1/model.chrombpnet_nobias.fold_1.ENCSR211SUT.tar +3 -0
  21. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.args.json +23 -0
  22. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.batch_loss.tsv +0 -0
  23. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.bias_formatting.stderr.txt +38 -0
  24. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.bias_formatting.stdout.txt +1 -0
  25. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet.params.json +11 -0
  26. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_data_params.tsv +3 -0
  27. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_formatting.stderr.txt +40 -0
  28. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_formatting.stdout.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  30. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  31. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.epoch_loss.csv +15 -0
  32. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.stderr.txt +0 -0
  33. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.stdout.txt +3 -0
  34. fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.stdout_v1.txt +3 -0
  35. fold_2/model.bias_scaled.fold_2.ENCSR211SUT.h5 +3 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR211SUT.tar +3 -0
  37. fold_2/model.chrombpnet.fold_2.ENCSR211SUT.h5 +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR211SUT.tar +3 -0
  39. fold_2/model.chrombpnet_nobias.fold_2.ENCSR211SUT.h5 +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR211SUT.tar +3 -0
  41. fold_3/logs.models.fold_3.ENCSR211SUT/logfile.modelling.fold_3.ENCSR211SUT.stdout_v1.txt +3 -0
  42. fold_3/model.bias_scaled.fold_3.ENCSR211SUT.h5 +3 -0
  43. fold_3/model.bias_scaled.fold_3.ENCSR211SUT.tar +3 -0
  44. fold_3/model.chrombpnet.fold_3.ENCSR211SUT.h5 +3 -0
  45. fold_3/model.chrombpnet.fold_3.ENCSR211SUT.tar +3 -0
  46. fold_3/model.chrombpnet_nobias.fold_3.ENCSR211SUT.h5 +3 -0
  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR211SUT.tar +3 -0
  48. fold_4/logs.models.fold_4.ENCSR211SUT/logfile.modelling.fold_4.ENCSR211SUT.stdout.txt +3 -0
  49. fold_4/logs.models.fold_4.ENCSR211SUT/logfile.modelling.fold_4.ENCSR211SUT.stdout_v1.txt +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR211SUT.h5 +3 -0
.gitattributes CHANGED
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+ fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_4/logs.models.fold_4.ENCSR211SUT/logfile.modelling.fold_4.ENCSR211SUT.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_4/logs.models.fold_4.ENCSR211SUT/logfile.modelling.fold_4.ENCSR211SUT.stdout.txt filter=lfs diff=lfs merge=lfs -text
fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.batch_loss.tsv ADDED
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fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ 2023-07-15 02:33:57.020397: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:59.335848: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-15 02:33:59.339264: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-15 02:33:59.920388: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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+ pciBusID: 0000:07:00.0 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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+ 2023-07-15 02:33:59.920521: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:59.942841: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-15 02:33:59.942902: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-15 02:33:59.952422: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:33:59.956958: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:33:59.972808: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:33:59.977024: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:33:59.977939: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:34:00.008150: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-15 02:34:00.008615: 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.
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+ 2023-07-15 02:34:00.010191: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 02:34:00.032711: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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+ pciBusID: 0000:07:00.0 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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+ 2023-07-15 02:34:00.032782: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:34:00.032819: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-15 02:34:00.032872: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:34:00.032896: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:34:00.032920: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:34:00.032943: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:34:00.032967: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:34:00.079793: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-15 02:34:00.082370: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:34:02.907235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 02:34:02.907406: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
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+ 2023-07-15 02:34:02.907419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-07-15 02:34:02.913953: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:07:00.0, compute capability: 8.0)
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+ 2023-07-15 02:34:04.040871: 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.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
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+ 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//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/new_model_formats/bias_model_scaled
fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.chrombpnet_fix_formatting.stderr.txt ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
4
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
5
+ 2023-08-20 01:04:46.833493: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-08-20 01:04:49.431379: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-08-20 01:04:49.435406: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-08-20 01:04:49.847946: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
9
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
10
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
11
+ 2023-08-20 01:04:49.848115: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-08-20 01:04:49.872214: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-08-20 01:04:49.872268: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-08-20 01:04:49.883033: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-08-20 01:04:49.888180: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-08-20 01:04:49.906180: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-08-20 01:04:49.910964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-08-20 01:04:49.912003: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-08-20 01:04:49.984113: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-08-20 01:04:49.984588: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
21
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
22
+ 2023-08-20 01:04:49.986038: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
23
+ 2023-08-20 01:04:49.995279: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
24
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
25
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
26
+ 2023-08-20 01:04:49.995325: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
27
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+ 2023-08-20 01:04:49.995376: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-08-20 01:04:49.995396: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
30
+ 2023-08-20 01:04:49.995415: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
31
+ 2023-08-20 01:04:49.995433: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
32
+ 2023-08-20 01:04:49.995452: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
33
+ 2023-08-20 01:04:49.995471: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
34
+ 2023-08-20 01:04:50.026564: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
35
+ 2023-08-20 01:04:50.028849: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
36
+ 2023-08-20 01:04:51.834899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
37
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38
+ 2023-08-20 01:04:51.835083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-08-20 01:04:51.841831: 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)
40
+ 2023-08-20 01:04:54.565353: 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.
41
+ /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.
42
+ , UserWarning)
fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.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//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.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//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR211SUT/logfile.modelling.fold_0.ENCSR211SUT.stdout_v1.txt ADDED
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fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.args.json ADDED
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+ {
2
+ "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
3
+ "bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//preprocessing/bigWigs/ENCSR211SUT.bigWig",
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5
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9
+ "logcount_predictions_loss",
10
+ "loss",
11
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12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
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+ ],
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17
+ "early_stop": 5,
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19
+ "learning_rate": 0.001,
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21
+ "seed": 1234,
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23
+ }
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 02:33:57.065786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 02:33:59.343310: 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
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7
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-15 02:34:00.295695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 02:34:00.317555: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
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12
+ 2023-07-15 02:34:00.326699: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-15 02:34:00.331050: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 02:34:00.346207: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 02:34:00.350224: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 02:34:00.351112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 02:34:00.387970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
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19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 02:34:00.389991: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
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22
+ pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-15 02:34:00.441303: 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
+ 2023-07-15 02:34:02.861155: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
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38
+ 2023-07-15 02:34:04.046178: 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.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.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//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "20.6",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR211SUT//chrombppnet_model_encsr880cub_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.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 28.0
2
+ counts_sum_max_thresh 3224.67
3
+ trainings_pts_post_thresh 176876
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 01:33:17.278899: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 01:33:20.369092: 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
+ 2023-07-15 01:33:20.419912: 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
+ 2023-07-15 01:33:20.420036: 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
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13
+ 2023-07-15 01:33:20.474232: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 01:33:20.501035: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 01:33:20.508308: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 01:33:20.509784: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 01:33:20.516597: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 01:33:20.516978: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 01:33:20.517986: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 01:33:20.518326: 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
+ 2023-07-15 01:33:20.518361: 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
+ 2023-07-15 01:33:20.518468: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
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30
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31
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32
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33
+ 2023-07-15 01:33:20.520472: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
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35
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36
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37
+ 2023-07-15 01:33:22.392428: 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
+ 2023-07-15 01:33:24.759488: 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.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.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//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.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//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.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//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR211SUT//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR211SUT/logfile.modelling.fold_2.ENCSR211SUT.epoch_loss.csv ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,2.1102142333984375,685.030029296875,728.4995727539062,0.3993287682533264,678.3511962890625,686.5772705078125
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