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encode-chrombpnet-DNASE-ENCSR217TAW-ENCSR174HCP

chrombpnet
encode
chromatin-accessibility
DNASE
GM23248
hg38
Model card Files
xet
 Community
chang-m-yun commited on
Commit
d2b1ab3
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  1. .gitattributes +10 -0
  2. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.bias_formatting.stderr.txt +38 -0
  4. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.chrombpnet.params.json +11 -0
  5. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.chrombpnet_formatting.stderr.txt +40 -0
  6. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.epoch_loss.csv +17 -0
  8. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.stdout.txt +3 -0
  9. fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.stdout_v1.txt +3 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR217TAW.h5 +3 -0
  11. fold_0/model.bias_scaled.fold_0.ENCSR217TAW.tar +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR217TAW.h5 +3 -0
  13. fold_0/model.chrombpnet.fold_0.ENCSR217TAW.tar +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR217TAW.h5 +3 -0
  15. fold_0/model.chrombpnet_nobias.fold_0.ENCSR217TAW.tar +3 -0
  16. fold_1/logs.models.fold_1.ENCSR217TAW/logfile.modelling.fold_1.ENCSR217TAW.stdout.txt +3 -0
  17. fold_1/logs.models.fold_1.ENCSR217TAW/logfile.modelling.fold_1.ENCSR217TAW.stdout_v1.txt +3 -0
  18. fold_1/model.bias_scaled.fold_1.ENCSR217TAW.h5 +3 -0
  19. fold_1/model.bias_scaled.fold_1.ENCSR217TAW.tar +3 -0
  20. fold_1/model.chrombpnet.fold_1.ENCSR217TAW.h5 +3 -0
  21. fold_1/model.chrombpnet.fold_1.ENCSR217TAW.tar +3 -0
  22. fold_1/model.chrombpnet_nobias.fold_1.ENCSR217TAW.h5 +3 -0
  23. fold_1/model.chrombpnet_nobias.fold_1.ENCSR217TAW.tar +3 -0
  24. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.args.json +23 -0
  25. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.bias_formatting.stderr.txt +38 -0
  26. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.bias_formatting.stdout.txt +1 -0
  27. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet.params.json +11 -0
  28. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_data_params.tsv +3 -0
  29. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_formatting.stderr.txt +40 -0
  30. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_model_params.tsv +9 -0
  31. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.epoch_loss.csv +18 -0
  34. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.stdout.txt +3 -0
  35. fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.stdout_v1.txt +3 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR217TAW.h5 +3 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR217TAW.tar +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR217TAW.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR217TAW.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR217TAW.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR217TAW.tar +3 -0
  42. fold_3/logs.models.fold_3.ENCSR217TAW/logfile.modelling.fold_3.ENCSR217TAW.stdout.txt +3 -0
  43. fold_3/logs.models.fold_3.ENCSR217TAW/logfile.modelling.fold_3.ENCSR217TAW.stdout_v1.txt +3 -0
  44. fold_3/model.bias_scaled.fold_3.ENCSR217TAW.h5 +3 -0
  45. fold_3/model.bias_scaled.fold_3.ENCSR217TAW.tar +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR217TAW.h5 +3 -0
  47. fold_3/model.chrombpnet.fold_3.ENCSR217TAW.tar +3 -0
  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR217TAW.h5 +3 -0
  49. fold_3/model.chrombpnet_nobias.fold_3.ENCSR217TAW.tar +3 -0
  50. fold_4/logs.models.fold_4.ENCSR217TAW/logfile.modelling.fold_4.ENCSR217TAW.stdout.txt +3 -0
.gitattributes CHANGED
@@ -33,3 +33,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_1/logs.models.fold_1.ENCSR217TAW/logfile.modelling.fold_1.ENCSR217TAW.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_1/logs.models.fold_1.ENCSR217TAW/logfile.modelling.fold_1.ENCSR217TAW.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_4/logs.models.fold_4.ENCSR217TAW/logfile.modelling.fold_4.ENCSR217TAW.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_4/logs.models.fold_4.ENCSR217TAW/logfile.modelling.fold_4.ENCSR217TAW.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_3/logs.models.fold_3.ENCSR217TAW/logfile.modelling.fold_3.ENCSR217TAW.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_3/logs.models.fold_3.ENCSR217TAW/logfile.modelling.fold_3.ENCSR217TAW.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.batch_loss.tsv ADDED
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fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.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
+ 2023-08-18 16:26:14.505589: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-08-18 16:26:16.963047: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-08-18 16:26:16.966877: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-08-18 16:26:17.646881: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-08-18 16:26:17.646999: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-08-18 16:26:17.667226: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-08-18 16:26:17.667287: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-08-18 16:26:17.676951: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-08-18 16:26:17.681362: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-08-18 16:26:17.697433: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-08-18 16:26:17.701604: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-08-18 16:26:17.702523: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-08-18 16:26:17.722969: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-08-18 16:26:17.723287: 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
+ 2023-08-18 16:26:17.724154: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-08-18 16:26:17.745966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-08-18 16:26:17.745998: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-08-18 16:26:17.746018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-08-18 16:26:17.746033: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-08-18 16:26:17.746047: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-08-18 16:26:17.746060: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-08-18 16:26:17.746073: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-08-18 16:26:17.746085: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-08-18 16:26:17.746098: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-08-18 16:26:17.788277: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-08-18 16:26:17.789579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-08-18 16:26:20.205367: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-08-18 16:26:20.205468: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-08-18 16:26:20.205482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-08-18 16:26:20.212109: 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)
38
+ 2023-08-18 16:26:21.546116: 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.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "140.3",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR217TAW//chrombpnet_model_feb15_fold_0/bias_model_scaled.h5",
6
+ "inputlen": "2114",
7
+ "outputlen": "1000",
8
+ "max_jitter": "500",
9
+ "chr_fold_path": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/splits/fold_0.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.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
+ 2023-08-18 15:14:04.121883: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-08-18 15:14:06.565160: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-08-18 15:14:06.569067: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-08-18 15:14:06.970559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-08-18 15:14:06.970717: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-08-18 15:14:06.991996: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-08-18 15:14:06.992048: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-08-18 15:14:07.001659: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-08-18 15:14:07.006247: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-08-18 15:14:07.022223: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-08-18 15:14:07.026534: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-08-18 15:14:07.027438: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-08-18 15:14:07.074872: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-08-18 15:14:07.075182: 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
+ 2023-08-18 15:14:07.076038: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-08-18 15:14:07.083163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-08-18 15:14:07.083196: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-08-18 15:14:07.083216: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-08-18 15:14:07.083230: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-08-18 15:14:07.083243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-08-18 15:14:07.083256: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-08-18 15:14:07.083268: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-08-18 15:14:07.083281: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-08-18 15:14:07.083295: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-08-18 15:14:07.113573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-08-18 15:14:07.114884: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-08-18 15:14:08.861187: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-08-18 15:14:08.861330: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-08-18 15:14:08.861343: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-08-18 15:14:08.867806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
38
+ 2023-08-18 15:14:11.068182: 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.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 140.3
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR217TAW//chrombpnet_model_feb15_fold_0/bias_model_scaled.h5
5
+ inputlen 2114
6
+ outputlen 1000
7
+ max_jitter 500
8
+ chr_fold_path /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/splits/fold_0.json
9
+ negative_sampling_ratio 0.1
fold_0/logs.models.fold_0.ENCSR217TAW/logfile.modelling.fold_0.ENCSR217TAW.epoch_loss.csv ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
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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//ENCSR217TAW//preprocessing/bigWigs/ENCSR217TAW.bigWig",
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+ "trackables": [
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+ "logcount_predictions_loss",
10
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+ "seed": 1234,
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+ "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
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fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.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
+ 2023-08-18 16:26:14.481323: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
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5
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6
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7
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8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-08-18 16:26:17.252678: 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
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14
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15
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16
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17
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18
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19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
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21
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22
+ pciBusID: 0000:8a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
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25
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26
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27
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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
+ 2023-08-18 16:26:20.281803: 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: 0000:8a:00.0, compute capability: 8.0)
38
+ 2023-08-18 16:26:21.447209: 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.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.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//ENCSR217TAW//chrombpnet_model_feb15_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR217TAW//chrombpnet_model_feb15_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "141.0",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR217TAW//chrombpnet_model_feb15_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.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 12.0
2
+ counts_sum_max_thresh 15212.0
3
+ trainings_pts_post_thresh 175948
fold_2/logs.models.fold_2.ENCSR217TAW/logfile.modelling.fold_2.ENCSR217TAW.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
+ 2023-08-18 15:14:04.886484: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
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5
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6
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7
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-08-18 15:14:07.512667: 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
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14
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15
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16
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17
+ 2023-08-18 15:14:07.573255: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-08-18 15:14:07.573527: 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
+ 2023-08-18 15:14:07.574251: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-08-18 15:14:07.576537: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-08-18 15:14:07.576560: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-08-18 15:14:07.576577: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-08-18 15:14:07.576592: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-08-18 15:14:07.576605: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-08-18 15:14:07.576617: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-08-18 15:14:07.576628: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-08-18 15:14:07.576640: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-08-18 15:14:07.576651: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-08-18 15:14:07.581213: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-08-18 15:14:07.582266: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-08-18 15:14:09.235127: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-08-18 15:14:09.235265: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-08-18 15:14:09.235278: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-08-18 15:14:09.241629: 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)
38
+ 2023-08-18 15:14:11.475955: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
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+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
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