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encode-chrombpnet-DNASE-ENCSR945JJB-ENCSR376IJB

chrombpnet
encode
chromatin-accessibility
DNASE
lung
hg38
Model card Files
xet
 Community
chang-m-yun commited on
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  1. .gitattributes +8 -0
  2. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.bias_formatting.stderr.txt +38 -0
  4. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.bias_formatting.stdout.txt +1 -0
  5. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.chrombpnet_formatting.stdout.txt +1 -0
  6. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.chrombpnet_model_params.tsv +9 -0
  7. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.stderr.txt +0 -0
  8. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.stdout.txt +3 -0
  9. fold_0/logs.models.fold_0.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.stdout_v1.txt +3 -0
  10. fold_0/model.bias_scaled.fold_0.ENCSR945JJB.h5 +3 -0
  11. fold_0/model.bias_scaled.fold_0.ENCSR945JJB.tar +3 -0
  12. fold_0/model.chrombpnet.fold_0.ENCSR945JJB.h5 +3 -0
  13. fold_0/model.chrombpnet.fold_0.ENCSR945JJB.tar +3 -0
  14. fold_0/model.chrombpnet_nobias.fold_0.ENCSR945JJB.h5 +3 -0
  15. fold_0/model.chrombpnet_nobias.fold_0.ENCSR945JJB.tar +3 -0
  16. fold_1/logs.models.fold_1.ENCSR945JJB/logfile.modelling.fold_1.ENCSR945JJB.stdout.txt +3 -0
  17. fold_1/logs.models.fold_1.ENCSR945JJB/logfile.modelling.fold_1.ENCSR945JJB.stdout_v1.txt +3 -0
  18. fold_1/model.bias_scaled.fold_1.ENCSR945JJB.h5 +3 -0
  19. fold_1/model.bias_scaled.fold_1.ENCSR945JJB.tar +3 -0
  20. fold_1/model.chrombpnet.fold_1.ENCSR945JJB.h5 +3 -0
  21. fold_1/model.chrombpnet.fold_1.ENCSR945JJB.tar +3 -0
  22. fold_1/model.chrombpnet_nobias.fold_1.ENCSR945JJB.h5 +3 -0
  23. fold_1/model.chrombpnet_nobias.fold_1.ENCSR945JJB.tar +3 -0
  24. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.args.json +23 -0
  25. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.bias_formatting.stderr.txt +38 -0
  26. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet.params.json +11 -0
  27. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_data_params.tsv +3 -0
  28. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_formatting.stderr.txt +40 -0
  29. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_formatting.stdout.txt +1 -0
  30. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_model_params.tsv +9 -0
  31. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  32. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.stderr.txt +0 -0
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  35. fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.stdout_v1.txt +0 -0
  36. fold_2/model.bias_scaled.fold_2.ENCSR945JJB.h5 +3 -0
  37. fold_2/model.bias_scaled.fold_2.ENCSR945JJB.tar +3 -0
  38. fold_2/model.chrombpnet.fold_2.ENCSR945JJB.h5 +3 -0
  39. fold_2/model.chrombpnet.fold_2.ENCSR945JJB.tar +3 -0
  40. fold_2/model.chrombpnet_nobias.fold_2.ENCSR945JJB.h5 +3 -0
  41. fold_2/model.chrombpnet_nobias.fold_2.ENCSR945JJB.tar +3 -0
  42. fold_3/logs.models.fold_3.ENCSR945JJB/logfile.modelling.fold_3.ENCSR945JJB.stdout.txt +3 -0
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  44. fold_3/model.bias_scaled.fold_3.ENCSR945JJB.h5 +3 -0
  45. fold_3/model.bias_scaled.fold_3.ENCSR945JJB.tar +3 -0
  46. fold_3/model.chrombpnet.fold_3.ENCSR945JJB.h5 +3 -0
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  48. fold_3/model.chrombpnet_nobias.fold_3.ENCSR945JJB.h5 +3 -0
  49. fold_3/model.chrombpnet_nobias.fold_3.ENCSR945JJB.tar +3 -0
  50. fold_4/logs.models.fold_4.ENCSR945JJB/logfile.modelling.fold_4.ENCSR945JJB.stdout.txt +3 -0
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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 02:17:27.569087: 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 02:17:27.830050: 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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+ 2023-07-15 02:17:27.919791: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:17:28.110638: 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
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+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
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+ 2023-07-15 02:17:28.113922: 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 02:17:28.113980: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:17:28.114016: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:17:28.119936: 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 02:17:31.532924: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
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+ 2023-07-15 02:17:31.533093: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
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+ 2023-07-15 02:17:31.533107: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-07-15 02:17:31.539716: 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 02:17:32.699080: 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.ENCSR945JJB/logfile.modelling.fold_0.ENCSR945JJB.bias_formatting.stdout.txt ADDED
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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//ENCSR945JJB//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//chrombpnet_model_encsr880cub_bias/new_model_formats/bias_model_scaled
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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//ENCSR945JJB//chrombpnet_model_encsr880cub_bias/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet
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+ outputlen 1000
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+ chr_fold_path /scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json
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+ negative_sampling_ratio 0.1
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+ "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
3
+ "bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//preprocessing/bigWigs/ENCSR945JJB.bigWig",
4
+ "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2//filtered.peaks.bed",
5
+ "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2//filtered.nonpeaks.bed",
6
+ "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2//chrombpnet",
7
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
8
+ "trackables": [
9
+ "logcount_predictions_loss",
10
+ "loss",
11
+ "logits_profile_predictions_loss",
12
+ "val_logcount_predictions_loss",
13
+ "val_loss",
14
+ "val_logits_profile_predictions_loss"
15
+ ],
16
+ "epochs": 50,
17
+ "early_stop": 5,
18
+ "batch_size": 64,
19
+ "learning_rate": 0.001,
20
+ "params": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2//chrombpnet_model_params.tsv",
21
+ "seed": 1234,
22
+ "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
23
+ }
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.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 02:17:25.566823: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 02:17:28.484605: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-15 02:17:28.488326: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-15 02:17:28.665905: 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
+ 2023-07-15 02:17:28.666038: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 02:17:28.689155: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-15 02:17:28.689234: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-15 02:17:28.700087: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-15 02:17:28.705087: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 02:17:28.723937: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 02:17:28.729241: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 02:17:28.730401: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 02:17:28.736365: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 02:17:28.736770: 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 02:17:28.737636: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 02:17:28.739947: 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
+ 2023-07-15 02:17:28.739973: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 02:17:28.739992: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-15 02:17:28.740007: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-15 02:17:28.740020: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 02:17:28.740033: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 02:17:28.740045: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-15 02:17:28.740058: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-15 02:17:28.740071: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-15 02:17:28.744724: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 02:17:28.746030: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 02:17:30.643068: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 02:17:30.643205: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 02:17:30.643219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 02:17:30.649933: 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
+ 2023-07-15 02:17:31.950287: 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.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "18.1",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//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.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 32.0
2
+ counts_sum_max_thresh 2975.0
3
+ trainings_pts_post_thresh 177857
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.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 01:12:38.678686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 01:12:41.832189: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
5
+ 2023-07-15 01:12:41.837341: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
6
+ 2023-07-15 01:12:41.867165: 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 01:12:41.867261: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 01:12:41.896731: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-15 01:12:41.896862: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-15 01:12:41.910884: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
13
+ 2023-07-15 01:12:41.917111: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
14
+ 2023-07-15 01:12:41.941613: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
15
+ 2023-07-15 01:12:41.947532: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
16
+ 2023-07-15 01:12:41.948906: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
17
+ 2023-07-15 01:12:41.974845: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 01:12:41.975253: 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 01:12:41.976208: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 01:12:41.994542: 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 01:12:41.994652: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 01:12:41.994725: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-15 01:12:41.994750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-15 01:12:41.994772: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 01:12:41.994794: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 01:12:41.994815: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-15 01:12:41.994836: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-15 01:12:41.994858: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-15 01:12:41.997043: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 01:12:41.998504: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 01:12:43.902797: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 01:12:43.902851: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 01:12:43.902869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 01:12:43.905772: 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 01:12:46.307447: 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.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.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//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 18.1
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR945JJB//chrombppnet_model_encsr880cub_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.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.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//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.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//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR945JJB//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.stderr.txt ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.stdout.txt ADDED
The diff for this file is too large to render. See raw diff
 
fold_2/logs.models.fold_2.ENCSR945JJB/logfile.modelling.fold_2.ENCSR945JJB.stdout_v1.txt ADDED
The diff for this file is too large to render. See raw diff
 
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