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encode-chrombpnet-DNASE-T-helper-1-cell-ENCSR384GGJ-ENCSR653VWJ

chrombpnet
encode
chromatin-accessibility
DNASE
t-helper
hg38
Model card Files
xet
 Community
chang-m-yun commited on
Commit
ec240b2
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1 Parent(s): 790a861

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  1. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.batch_loss.tsv +0 -0
  2. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.bias_formatting.stderr.txt +38 -0
  3. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet.params.json +11 -0
  4. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_data_params.tsv +3 -0
  5. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_formatting.stderr.txt +40 -0
  6. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  9. fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.stdout_v1.txt +0 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR384GGJ.h5 +3 -0
  11. fold_0/model.bias_scaled.fold_0.ENCSR384GGJ.tar +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR384GGJ.h5 +3 -0
  13. fold_0/model.chrombpnet.fold_0.ENCSR384GGJ.tar +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR384GGJ.h5 +3 -0
  15. fold_0/model.chrombpnet_nobias.fold_0.ENCSR384GGJ.tar +3 -0
  16. fold_1/model.bias_scaled.fold_1.ENCSR384GGJ.h5 +3 -0
  17. fold_1/model.bias_scaled.fold_1.ENCSR384GGJ.tar +3 -0
  18. fold_1/model.chrombpnet.fold_1.ENCSR384GGJ.h5 +3 -0
  19. fold_1/model.chrombpnet.fold_1.ENCSR384GGJ.tar +3 -0
  20. fold_1/model.chrombpnet_nobias.fold_1.ENCSR384GGJ.h5 +3 -0
  21. fold_1/model.chrombpnet_nobias.fold_1.ENCSR384GGJ.tar +3 -0
  22. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.args.json +23 -0
  23. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.batch_loss.tsv +0 -0
  24. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.bias_formatting.stderr.txt +38 -0
  25. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.bias_formatting.stdout.txt +1 -0
  26. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet.params.json +11 -0
  27. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_data_params.tsv +3 -0
  28. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_formatting.stderr.txt +40 -0
  29. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_formatting.stdout.txt +1 -0
  30. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_model_params.tsv +9 -0
  31. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.epoch_loss.csv +15 -0
  34. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.stderr.txt +0 -0
  35. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.stdout.txt +0 -0
  36. fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.stdout_v1.txt +0 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR384GGJ.h5 +3 -0
  38. fold_2/model.bias_scaled.fold_2.ENCSR384GGJ.tar +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR384GGJ.h5 +3 -0
  40. fold_2/model.chrombpnet.fold_2.ENCSR384GGJ.tar +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR384GGJ.h5 +3 -0
  42. fold_2/model.chrombpnet_nobias.fold_2.ENCSR384GGJ.tar +3 -0
  43. fold_3/model.bias_scaled.fold_3.ENCSR384GGJ.h5 +3 -0
  44. fold_3/model.bias_scaled.fold_3.ENCSR384GGJ.tar +3 -0
  45. fold_3/model.chrombpnet.fold_3.ENCSR384GGJ.h5 +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR384GGJ.tar +3 -0
  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR384GGJ.h5 +3 -0
  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR384GGJ.tar +3 -0
  49. fold_4/model.bias_scaled.fold_4.ENCSR384GGJ.h5 +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR384GGJ.tar +3 -0
fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.batch_loss.tsv ADDED
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fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.bias_formatting.stderr.txt ADDED
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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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+ 2023-07-16 23:53:05.316124: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-16 23:53:08.466824: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-16 23:53:08.473269: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-16 23:53:08.503649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
8
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
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+ 2023-07-16 23:53:08.503723: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-16 23:53:08.534264: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-16 23:53:08.534403: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-16 23:53:08.548786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-16 23:53:08.555169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-16 23:53:08.578304: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-16 23:53:08.584140: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-16 23:53:08.585431: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-16 23:53:08.587825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-16 23:53:08.588196: 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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+ 2023-07-16 23:53:08.589094: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-16 23:53:08.600351: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
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+ 2023-07-16 23:53:08.600385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-16 23:53:08.600413: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-16 23:53:08.600435: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-16 23:53:08.600456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-16 23:53:08.600476: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-16 23:53:08.600497: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-16 23:53:08.600517: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-16 23:53:08.600538: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-16 23:53:08.601570: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-16 23:53:08.603056: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-16 23:53:10.600674: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-16 23:53:10.600769: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-16 23:53:10.600788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-16 23:53:10.603993: 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: 0000:83:00.0, compute capability: 6.0)
38
+ 2023-07-16 23:53:11.536129: 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.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "7.0",
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.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_data_params.tsv ADDED
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1
+ counts_sum_min_thresh 2.0
2
+ counts_sum_max_thresh 4192.68
3
+ trainings_pts_post_thresh 86592
fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-17 13:18:22.440034: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 13:18:25.221739: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-17 13:18:25.225408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-17 13:18:25.826032: 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
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+ 2023-07-17 13:18:25.826103: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-17 13:18:25.852156: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-17 13:18:25.852340: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-17 13:18:25.863384: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-17 13:18:25.868463: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-17 13:18:25.886462: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-17 13:18:25.891390: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-17 13:18:25.892424: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-17 13:18:25.927981: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 13:18:25.928329: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-17 13:18:25.929453: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 13:18:25.951984: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
+ 2023-07-17 13:18:25.952023: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 13:18:25.952051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-17 13:18:25.952072: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-17 13:18:25.952091: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-17 13:18:25.952110: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-17 13:18:25.952128: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-17 13:18:25.952147: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-17 13:18:25.952166: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-17 13:18:25.978358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-17 13:18:25.980478: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-17 13:18:28.738473: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-17 13:18:28.738632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-17 13:18:28.738648: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-17 13:18:28.836025: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
38
+ 2023-07-17 13:18:31.293364: 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.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 7.0
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.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_no_bias_formatting.stderr.txt ADDED
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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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.chrombpnet_no_bias_formatting.stdout.txt ADDED
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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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR384GGJ/logfile.modelling.fold_0.ENCSR384GGJ.stdout_v1.txt ADDED
The diff for this file is too large to render. See raw diff
 
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fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.args.json ADDED
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+ {
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+ "bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//preprocessing/bigWigs/ENCSR384GGJ.bigWig",
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+ "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2//filtered.nonpeaks.bed",
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23
+ }
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.batch_loss.tsv ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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 23:53:05.335605: 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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8
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9
+ 2023-07-16 23:53:09.040820: 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
+ 2023-07-16 23:53:09.121686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-16 23:53:09.128529: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-16 23:53:09.130103: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-16 23:53:09.132446: 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
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21
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22
+ pciBusID: 0000:82:00.0 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 23:53:09.134341: 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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fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "7.0",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR384GGJ//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.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 2.0
2
+ counts_sum_max_thresh 4143.6
3
+ trainings_pts_post_thresh 91725
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-17 13:18:22.242333: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-17 13:18:24.918685: 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: 0000:07:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-17 13:18:25.070017: 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
+ 2023-07-17 13:18:25.145089: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-17 13:18:25.145442: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-17 13:18:25.146415: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 13:18:25.151184: 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
+ 2023-07-17 13:18:25.151220: 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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37
+ 2023-07-17 13:18:28.722631: 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
+ 2023-07-17 13:18:31.212954: 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.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 7.0
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR384GGJ//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.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR384GGJ//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR384GGJ/logfile.modelling.fold_2.ENCSR384GGJ.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
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+ 0,3.350593328475952,515.4959106445312,538.9498901367188,1.2230786085128784,481.7232971191406,490.28485107421875
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