Add files using upload-large-folder tool

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+fold_1/logs.models.fold_1.ENCSR134CIY/logfile.modelling.fold_1.ENCSR134CIY.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
+fold_1/logs.models.fold_1.ENCSR134CIY/logfile.modelling.fold_1.ENCSR134CIY.stdout.txt filter=lfs diff=lfs merge=lfs -text

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.args.json

@@ -0,0 +1,23 @@
+{
+    "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
+    "bigwig": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//preprocessing/bigWigs/ENCSR134CIY.bigWig",
+    "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias//filtered.peaks.bed",
+    "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias//filtered.nonpeaks.bed",
+    "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias//chrombpnet",
+    "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
+    "trackables": [
+        "logcount_predictions_loss",
+        "loss",
+        "logits_profile_predictions_loss",
+        "val_logcount_predictions_loss",
+        "val_loss",
+        "val_logits_profile_predictions_loss"
+    ],
+    "epochs": 50,
+    "early_stop": 5,
+    "batch_size": 64,
+    "learning_rate": 0.001,
+    "params": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias//chrombpnet_model_params.tsv",
+    "seed": 1234,
+    "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
+}

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.bias_formatting.stderr.txt

@@ -0,0 +1,38 @@
+INFO:    underlay of /etc/localtime required more than 50 (88) bind mounts
+INFO:    underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
+2023-07-17 00:03:49.922179: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:53.480352: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 00:03:53.485388: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-17 00:03:53.517475: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 00:03:53.517583: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:53.547115: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 00:03:53.547285: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 00:03:53.562535: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 00:03:53.569489: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 00:03:53.595608: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 00:03:53.602517: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 00:03:53.604097: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 00:03:53.606153: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 00:03:53.606549: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2023-07-17 00:03:53.607588: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 00:03:53.607916: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:83:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 00:03:53.607954: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:53.607995: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 00:03:53.608021: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 00:03:53.608045: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 00:03:53.608069: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 00:03:53.608092: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 00:03:53.608117: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 00:03:53.608141: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 00:03:53.608557: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 00:03:53.610111: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:55.855029: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-17 00:03:55.855137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-17 00:03:55.855160: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-17 00:03:55.858772: 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)
+2023-07-17 00:03:56.858391: 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.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.chrombpnet.params.json

@@ -0,0 +1,11 @@
+{
+    "counts_loss_weight": "4.0",
+    "filters": "512",
+    "n_dil_layers": "8",
+    "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5",
+    "inputlen": "2114",
+    "outputlen": "1000",
+    "max_jitter": "500",
+    "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
+    "negative_sampling_ratio": "0.1"
+}

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.chrombpnet_formatting.stderr.txt

@@ -0,0 +1,40 @@
+INFO:    underlay of /etc/localtime required more than 50 (88) bind mounts
+INFO:    underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
+2023-07-17 13:31:19.859973: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:22.950908: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 13:31:22.955302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-17 13:31:23.011888: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 13:31:23.011970: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:23.039441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 13:31:23.039563: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 13:31:23.054371: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 13:31:23.060602: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 13:31:23.085017: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 13:31:23.090764: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 13:31:23.091960: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 13:31:23.095487: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 13:31:23.095841: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2023-07-17 13:31:23.096852: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 13:31:23.098507: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 13:31:23.098538: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:23.098563: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 13:31:23.098585: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 13:31:23.098606: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 13:31:23.098627: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 13:31:23.098648: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 13:31:23.098669: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 13:31:23.098690: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 13:31:23.099051: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 13:31:23.100384: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:24.931333: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-17 13:31:24.931435: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-17 13:31:24.931454: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-17 13:31:24.947764: 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)
+2023-07-17 13:31:27.313044: 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.
+/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.
+  , UserWarning)

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.chrombpnet_model_params.tsv

@@ -0,0 +1,9 @@
+counts_loss_weight	4.0
+filters	512
+n_dil_layers	8
+bias_model_path	/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias/bias_model_scaled.h5
+inputlen	2114
+outputlen	1000
+max_jitter	500
+chr_fold_path	/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json
+negative_sampling_ratio	0.1

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.chrombpnet_no_bias_formatting.stderr.txt

@@ -0,0 +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//ENCSR134CIY//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.chrombpnet_no_bias_formatting.stdout.txt

@@ -0,0 +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//ENCSR134CIY//chrombppnet_model_encsr283tme_bias/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//chrombppnet_model_encsr283tme_bias/new_model_formats/chrombpnet_wo_bias

fold_0/logs.models.fold_0.ENCSR134CIY/logfile.modelling.fold_0.ENCSR134CIY.epoch_loss.csv

@@ -0,0 +1,14 @@
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fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.args.json

@@ -0,0 +1,23 @@
+{
+    "genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
+    "bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//preprocessing/bigWigs/ENCSR134CIY.bigWig",
+    "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2//filtered.peaks.bed",
+    "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2//filtered.nonpeaks.bed",
+    "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2//chrombpnet",
+    "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
+    "trackables": [
+        "logcount_predictions_loss",
+        "loss",
+        "logits_profile_predictions_loss",
+        "val_logcount_predictions_loss",
+        "val_loss",
+        "val_logits_profile_predictions_loss"
+    ],
+    "epochs": 50,
+    "early_stop": 5,
+    "batch_size": 64,
+    "learning_rate": 0.001,
+    "params": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2//chrombpnet_model_params.tsv",
+    "seed": 1234,
+    "architecture_from_file": "/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/models/chrombpnet_with_bias_model.py"
+}

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.bias_formatting.stderr.txt

@@ -0,0 +1,38 @@
+INFO:    underlay of /etc/localtime required more than 50 (88) bind mounts
+INFO:    underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
+2023-07-17 00:03:49.932350: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:52.652792: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 00:03:52.656311: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-17 00:03:53.035170: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:c0:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
+2023-07-17 00:03:53.035277: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:53.059288: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 00:03:53.059506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 00:03:53.073624: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 00:03:53.079153: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 00:03:53.097505: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 00:03:53.102252: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 00:03:53.103291: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 00:03:53.146992: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 00:03:53.147507: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2023-07-17 00:03:53.148623: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 00:03:53.175356: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:c0:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
+2023-07-17 00:03:53.175409: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:53.175451: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 00:03:53.175469: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 00:03:53.175485: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 00:03:53.175500: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 00:03:53.175515: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 00:03:53.175530: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 00:03:53.175545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 00:03:53.202497: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 00:03:53.204212: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 00:03:56.137549: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-17 00:03:56.137667: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-17 00:03:56.137682: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-17 00:03:56.144467: 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:c0:00.0, compute capability: 8.0)
+2023-07-17 00:03:57.599371: 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.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet.params.json

@@ -0,0 +1,11 @@
+{
+    "counts_loss_weight": "4.0",
+    "filters": "512",
+    "n_dil_layers": "8",
+    "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/bias_model_scaled.h5",
+    "inputlen": "2114",
+    "outputlen": "1000",
+    "max_jitter": "500",
+    "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
+    "negative_sampling_ratio": "0.1"
+}

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet_data_params.tsv

@@ -0,0 +1,3 @@
+counts_sum_min_thresh	2.0
+counts_sum_max_thresh	1278.0
+trainings_pts_post_thresh	170987

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet_formatting.stderr.txt

@@ -0,0 +1,40 @@
+INFO:    underlay of /etc/localtime required more than 50 (88) bind mounts
+INFO:    underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
+2023-07-17 13:31:19.874489: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:22.955235: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 13:31:22.961135: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-17 13:31:22.985403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:03:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 13:31:22.985473: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:23.016347: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 13:31:23.016464: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 13:31:23.030959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 13:31:23.037343: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 13:31:23.060700: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 13:31:23.066690: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 13:31:23.068332: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 13:31:23.070517: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 13:31:23.070920: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2023-07-17 13:31:23.071874: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-17 13:31:23.078690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:03:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
+coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
+2023-07-17 13:31:23.078727: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:23.078762: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-17 13:31:23.078785: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-17 13:31:23.078807: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-17 13:31:23.078829: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-17 13:31:23.078851: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-17 13:31:23.078873: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-17 13:31:23.078895: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-17 13:31:23.079907: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-17 13:31:23.081475: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-17 13:31:24.963560: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-17 13:31:24.963673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-17 13:31:24.963693: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-17 13:31:24.966678: 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: 0000:03:00.0, compute capability: 6.0)
+2023-07-17 13:31:27.324404: 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.
+/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.
+  , UserWarning)

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet_formatting.stdout.txt

@@ -0,0 +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//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet_no_bias_formatting.stderr.txt

@@ -0,0 +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//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.chrombpnet_no_bias_formatting.stdout.txt

@@ -0,0 +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//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2/new_model_formats/chrombpnet_wo_bias

fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.epoch_loss.csv

@@ -0,0 +1,14 @@
+epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
+0,4.043898582458496,283.57684326171875,299.75213623046875,1.1273096799850464,284.4803161621094,288.98956298828125
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+11,0.4637898802757263,255.0692138671875,256.92413330078125,0.4939974248409271,276.3403625488281,278.3163146972656
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fold_2/logs.models.fold_2.ENCSR134CIY/logfile.modelling.fold_2.ENCSR134CIY.stderr.txt

@@ -0,0 +1,328 @@
+2022-10-04 22:29:44.736823: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:35:52.789437: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-04 22:35:52.792393: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-04 22:35:53.209048: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-04 22:35:53.209159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:35:53.232302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:35:53.232424: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:35:53.245163: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-04 22:35:53.250850: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-04 22:35:53.270917: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-04 22:35:53.276394: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-04 22:35:53.277774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:35:53.281958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-04 22:35:53.282312: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-04 22:35:53.282447: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-04 22:35:53.283829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-04 22:35:53.283862: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:35:53.283885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:35:53.283902: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:35:53.283918: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-04 22:35:53.283933: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-04 22:35:53.283947: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-04 22:35:53.283962: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-04 22:35:53.283979: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:35:53.286534: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-04 22:35:53.288093: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:35:54.853663: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-04 22:35:54.853786: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-04 22:35:54.853801: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-04 22:35:54.860629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+2022-10-04 22:35:56.745804: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-04 22:35:56.754092: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-04 22:35:56.937390: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:35:58.444173: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:35:58.452186: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:36:28.380162: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:36:29.999266: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-04 22:36:30.000243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-04 22:36:30.258347: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-04 22:36:30.258433: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:36:30.261217: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:36:30.261283: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:36:30.262466: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-04 22:36:30.262674: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-04 22:36:30.264955: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-04 22:36:30.265518: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-04 22:36:30.265681: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:36:30.267462: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-04 22:36:30.267782: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-04 22:36:30.267890: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-04 22:36:30.268748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-04 22:36:30.268790: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:36:30.268810: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:36:30.268824: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:36:30.268837: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-04 22:36:30.268850: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-04 22:36:30.268863: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-04 22:36:30.268875: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-04 22:36:30.268890: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:36:30.270498: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-04 22:36:30.270538: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-04 22:36:30.828685: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-04 22:36:30.828780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-04 22:36:30.828796: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-04 22:36:30.831647: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+2022-10-04 22:42:26.969011: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-04 22:42:26.969474: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-04 22:42:28.366486: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-04 22:42:28.903479: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-04 22:42:28.918752: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-04 22:42:32.467042: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
+2022-10-05 00:04:21.066639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:04:23.272963: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:04:23.273941: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-05 00:04:23.481865: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:04:23.481917: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:04:23.483880: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:04:23.483927: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:04:23.484797: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:04:23.484966: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:04:23.486963: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:04:23.487378: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:04:23.487499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:04:23.489164: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:04:23.489443: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-05 00:04:23.489534: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:04:23.490415: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:04:23.490438: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:04:23.490455: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:04:23.490468: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:04:23.490481: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:04:23.490492: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:04:23.490504: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:04:23.490515: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:04:23.490527: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:04:23.492107: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:04:23.492153: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:04:23.939722: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-05 00:04:23.939811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-05 00:04:23.939825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-05 00:04:23.942601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+2022-10-05 00:05:33.940793: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-05 00:05:33.943425: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-05 00:05:34.011266: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:05:34.438679: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:05:34.440615: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+/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.
+  , UserWarning)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
+  cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
+  profile_prob = profile / np.sum(profile)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
+  shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
+  curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+2022-10-05 00:07:19.868756: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:07:21.881398: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:07:21.882690: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-05 00:07:22.156815: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:07:22.156878: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:07:22.159207: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:07:22.159263: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:07:22.160295: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:07:22.160465: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:07:22.162499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:07:22.162929: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:07:22.163048: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:07:22.164736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:07:22.165027: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-05 00:07:22.165148: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:07:22.165998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:07:22.166023: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:07:22.166041: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:07:22.166055: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:07:22.166069: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:07:22.166083: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:07:22.166096: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:07:22.166109: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:07:22.166122: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:07:22.167713: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:07:22.167748: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:07:22.622364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-05 00:07:22.622456: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-05 00:07:22.622471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-05 00:07:22.625234: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
+2022-10-05 00:08:29.602763: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-05 00:08:29.604808: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-05 00:08:29.652814: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:08:30.110913: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:08:30.112478: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
+  cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
+  profile_prob = profile / np.sum(profile)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
+  shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
+  curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+2022-10-05 00:10:06.881288: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:10:09.071055: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:10:09.072054: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-05 00:10:09.343562: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:10:09.343624: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:10:09.345645: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:10:09.345690: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:10:09.346532: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:10:09.346705: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:10:09.348827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:10:09.349241: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:10:09.349360: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:10:09.351035: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:10:09.351325: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-05 00:10:09.351408: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:10:09.352253: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:10:09.352276: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:10:09.352295: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:10:09.352309: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:10:09.352339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:10:09.352355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:10:09.352369: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:10:09.352382: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:10:09.352395: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:10:09.353977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:10:09.354009: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:10:09.789801: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-05 00:10:09.789890: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-05 00:10:09.789905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-05 00:10:09.792729: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+2022-10-05 00:11:15.740526: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-05 00:11:15.741960: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-05 00:11:15.771440: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:11:16.195027: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:11:16.196462: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
+  cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
+  profile_prob = profile / np.sum(profile)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
+  shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
+/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
+  curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
+2022-10-05 00:12:06.683748: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:12:07.677250: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:12:07.678094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-05 00:12:07.982649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:12:07.982720: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:12:07.985131: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:12:07.985193: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:12:07.986277: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:12:07.986499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:12:07.989001: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:12:07.989540: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:12:07.989721: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:12:07.991399: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:12:07.991689: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-05 00:12:07.991782: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:12:07.992626: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:12:07.992657: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:12:07.992678: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:12:07.992695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:12:07.992711: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:12:07.992726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:12:07.992742: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:12:07.992757: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:12:07.992772: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:12:07.994357: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:12:07.994398: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:12:08.434852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-05 00:12:08.434959: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-05 00:12:08.434974: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-05 00:12:08.437699: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
+2022-10-05 00:12:22.802705: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-05 00:12:22.803137: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-05 00:12:22.982121: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:12:23.459630: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:12:23.461248: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+mkdir: cannot create directory ‘/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR134CIY//chrombppnet_model_encsr283tme_bias_fold_2//footprints’: File exists
+2022-10-05 00:14:01.039732: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:14:02.026364: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:14:02.027656: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2022-10-05 00:14:02.357298: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:14:02.357362: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:14:02.359385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:14:02.359436: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:14:02.360336: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:14:02.360509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:14:02.362585: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:14:02.363018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:14:02.363143: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:14:02.364809: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:14:02.365078: 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
+To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
+2022-10-05 00:14:02.365164: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2022-10-05 00:14:02.366078: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
+2022-10-05 00:14:02.366122: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:14:02.366140: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:14:02.366153: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:14:02.366166: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2022-10-05 00:14:02.366178: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2022-10-05 00:14:02.366190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2022-10-05 00:14:02.366202: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2022-10-05 00:14:02.366214: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2022-10-05 00:14:02.368056: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2022-10-05 00:14:02.368095: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2022-10-05 00:14:02.843140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2022-10-05 00:14:02.843249: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2022-10-05 00:14:02.843262: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2022-10-05 00:14:02.845971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
+2022-10-05 00:14:17.095357: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
+2022-10-05 00:14:17.095832: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
+2022-10-05 00:14:17.217773: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2022-10-05 00:14:17.704112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2022-10-05 00:14:17.705666: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8

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