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encode-chrombpnet-DNASE-CD14-positive-monocyte-ENCSR695AUY-ENCSR576XND

chrombpnet
encode
chromatin-accessibility
DNASE
CD14-positive-monocyte
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.args.json +23 -0
  2. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.bias_formatting.stderr.txt +38 -0
  3. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.bias_formatting.stdout.txt +1 -0
  4. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.chrombpnet.params.json +11 -0
  5. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.chrombpnet_formatting.stdout.txt +1 -0
  6. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  7. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  8. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.epoch_loss.csv +17 -0
  9. fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.stdout_v1.txt +0 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR695AUY.h5 +3 -0
  11. fold_0/model.bias_scaled.fold_0.ENCSR695AUY.tar +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR695AUY.h5 +3 -0
  13. fold_0/model.chrombpnet.fold_0.ENCSR695AUY.tar +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR695AUY.h5 +3 -0
  15. fold_0/model.chrombpnet_nobias.fold_0.ENCSR695AUY.tar +3 -0
  16. fold_1/model.bias_scaled.fold_1.ENCSR695AUY.h5 +3 -0
  17. fold_1/model.bias_scaled.fold_1.ENCSR695AUY.tar +3 -0
  18. fold_1/model.chrombpnet.fold_1.ENCSR695AUY.h5 +3 -0
  19. fold_1/model.chrombpnet.fold_1.ENCSR695AUY.tar +3 -0
  20. fold_1/model.chrombpnet_nobias.fold_1.ENCSR695AUY.h5 +3 -0
  21. fold_1/model.chrombpnet_nobias.fold_1.ENCSR695AUY.tar +3 -0
  22. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.args.json +23 -0
  23. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.batch_loss.tsv +0 -0
  24. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.bias_formatting.stderr.txt +38 -0
  25. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.bias_formatting.stdout.txt +1 -0
  26. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet.params.json +11 -0
  27. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_data_params.tsv +3 -0
  28. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_formatting.stderr.txt +40 -0
  29. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_formatting.stdout.txt +1 -0
  30. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_model_params.tsv +9 -0
  31. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.epoch_loss.csv +17 -0
  34. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.stderr.txt +0 -0
  35. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.stdout.txt +0 -0
  36. fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.stdout_v1.txt +0 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR695AUY.h5 +3 -0
  38. fold_2/model.bias_scaled.fold_2.ENCSR695AUY.tar +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR695AUY.h5 +3 -0
  40. fold_2/model.chrombpnet.fold_2.ENCSR695AUY.tar +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR695AUY.h5 +3 -0
  42. fold_2/model.chrombpnet_nobias.fold_2.ENCSR695AUY.tar +3 -0
  43. fold_3/model.bias_scaled.fold_3.ENCSR695AUY.h5 +3 -0
  44. fold_3/model.bias_scaled.fold_3.ENCSR695AUY.tar +3 -0
  45. fold_3/model.chrombpnet.fold_3.ENCSR695AUY.h5 +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR695AUY.tar +3 -0
  47. fold_3/model.chrombpnet_nobias.fold_3.ENCSR695AUY.h5 +3 -0
  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR695AUY.tar +3 -0
  49. fold_4/model.bias_scaled.fold_4.ENCSR695AUY.h5 +3 -0
  50. fold_4/model.bias_scaled.fold_4.ENCSR695AUY.tar +3 -0
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.args.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "genome": "reference/hg38.genome.fa",
3
+ "bigwig": "data/ENCSR695AUY.bigWig",
4
+ "peaks": "chrombppnet_model_encsr283tme_bias//filtered.peaks.bed",
5
+ "nonpeaks": "chrombppnet_model_encsr283tme_bias//filtered.nonpeaks.bed",
6
+ "output_prefix": "chrombppnet_model_encsr283tme_bias//chrombpnet",
7
+ "chr_fold_path": "splits/fold_0.json",
8
+ "trackables": [
9
+ "logcount_predictions_loss",
10
+ "loss",
11
+ "logits_profile_predictions_loss",
12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
15
+ ],
16
+ "epochs": 50,
17
+ "early_stop": 5,
18
+ "batch_size": 64,
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+ "learning_rate": 0.001,
20
+ "params": "chrombppnet_model_encsr283tme_bias//chrombpnet_model_params.tsv",
21
+ "seed": 1234,
22
+ "architecture_from_file": "/scratch/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
+ }
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.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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+ 2023-07-17 00:25:41.252616: 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 00:25:43.502123: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-17 00:25:43.505626: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-17 00:25:44.072234: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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+ pciBusID: 0000:8a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
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+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
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+ 2023-07-17 00:25:44.072355: 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 00:25:44.094493: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-17 00:25:44.094549: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-17 00:25:44.104056: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-17 00:25:44.108438: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-17 00:25:44.124120: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-17 00:25:44.128412: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-17 00:25:44.129344: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-17 00:25:44.160868: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-17 00:25:44.161201: 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 00:25:44.162196: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-17 00:25:44.185047: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
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
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+ 2023-07-17 00:25:44.185105: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-17 00:25:44.185143: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-17 00:25:44.185172: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-17 00:25:44.185198: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-17 00:25:44.185223: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-17 00:25:44.185247: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-17 00:25:44.185271: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-17 00:25:44.185295: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-17 00:25:44.232070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
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+ 2023-07-17 00:25:44.234506: 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 00:25:46.975510: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
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+ 2023-07-17 00:25:46.975611: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
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+ 2023-07-17 00:25:46.975624: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-07-17 00:25:46.982466: 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
+ 2023-07-17 00:25:48.017305: 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.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/new_model_formats/bias_model_scaled
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "2.7",
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.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias
fold_0/logs.models.fold_0.ENCSR695AUY/logfile.modelling.fold_0.ENCSR695AUY.epoch_loss.csv ADDED
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fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.batch_loss.tsv ADDED
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1
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+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
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19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
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22
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23
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30
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fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
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fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
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3
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4
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6
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10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
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2
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3
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fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
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7
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8
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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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23
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24
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25
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33
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38
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39
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fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 2.7
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5
5
+ inputlen 2114
6
+ outputlen 1000
7
+ max_jitter 500
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+ 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.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.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//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR695AUY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR695AUY/logfile.modelling.fold_2.ENCSR695AUY.epoch_loss.csv ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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