Add files using upload-large-folder tool

.gitattributes

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fold_0/logs.models.fold_0.ENCSR011SAG/logfile.modelling.fold_0.ENCSR011SAG.chrombpnet.params.json

@@ -0,0 +1,11 @@
+{
+    "counts_loss_weight": "19.4",
+    "filters": "512",
+    "n_dil_layers": "8",
+    "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR011SAG//chrombpnet_model_encsr880cub_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.ENCSR011SAG/logfile.modelling.fold_0.ENCSR011SAG.chrombpnet_data_params.tsv

@@ -0,0 +1,3 @@
+counts_sum_min_thresh	20.0
+counts_sum_max_thresh	3463.33
+trainings_pts_post_thresh	168872

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fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.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//ENCSR011SAG//preprocessing/bigWigs/ENCSR011SAG.bigWig",
+    "peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR011SAG//chrombppnet_model_encsr880cub_bias_fold_2//filtered.peaks.bed",
+    "nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR011SAG//chrombppnet_model_encsr880cub_bias_fold_2//filtered.nonpeaks.bed",
+    "output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR011SAG//chrombppnet_model_encsr880cub_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/ENCSR011SAG//chrombppnet_model_encsr880cub_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.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.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
+2023-07-15 02:17:54.964346: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 02:17:57.307184: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-15 02:17:57.310739: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-15 02:17:58.401257: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
+2023-07-15 02:17:58.401456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 02:17:58.426164: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-15 02:17:58.426347: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-15 02:17:58.435801: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-15 02:17:58.440399: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-15 02:17:58.456103: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-15 02:17:58.460255: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-15 02:17:58.461165: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-15 02:17:58.584139: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-15 02:17:58.584600: 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.
+2023-07-15 02:17:58.586148: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-15 02:17:58.636072: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:4b:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
+2023-07-15 02:17:58.636120: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 02:17:58.636153: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-15 02:17:58.636176: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-15 02:17:58.636197: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-15 02:17:58.636218: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-15 02:17:58.636238: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-15 02:17:58.636259: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-15 02:17:58.636279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-15 02:17:58.687850: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-15 02:17:58.690315: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 02:18:00.968298: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-15 02:18:00.968482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-15 02:18:00.968496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-15 02:18:00.974814: 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: 0000:4b:00.0, compute capability: 8.0)
+2023-07-15 02:18:01.999568: 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.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.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//ENCSR011SAG//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR011SAG//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/bias_model_scaled

fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet.params.json

@@ -0,0 +1,11 @@
+{
+    "counts_loss_weight": "19.5",
+    "filters": "512",
+    "n_dil_layers": "8",
+    "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR011SAG//chrombppnet_model_encsr880cub_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.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet_data_params.tsv

@@ -0,0 +1,3 @@
+counts_sum_min_thresh	21.0
+counts_sum_max_thresh	3446.06
+trainings_pts_post_thresh	176441

fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.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
+2023-07-15 01:12:50.092429: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 01:12:52.999265: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-15 01:12:53.003287: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
+2023-07-15 01:12:53.777873: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.39GiB deviceMemoryBandwidth: 1.41TiB/s
+2023-07-15 01:12:53.778016: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 01:12:53.804556: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
+2023-07-15 01:12:53.804686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
+2023-07-15 01:12:53.817005: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-15 01:12:53.823358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-15 01:12:53.845507: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-15 01:12:53.850595: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-15 01:12:53.851663: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-15 01:12:53.893525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-15 01:12:53.894050: 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.
+2023-07-15 01:12:53.895907: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
+2023-07-15 01:12:53.914308: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
+pciBusID: 0000:07:00.0 name: NVIDIA A100-SXM4-40GB computeCapability: 8.0
+coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.39GiB deviceMemoryBandwidth: 1.41TiB/s
+2023-07-15 01:12:53.914366: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 01:12:53.914404: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+2023-07-15 01:12:53.914467: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
+2023-07-15 01:12:53.914497: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
+2023-07-15 01:12:53.914526: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
+2023-07-15 01:12:53.914555: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
+2023-07-15 01:12:53.914584: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
+2023-07-15 01:12:53.956459: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
+2023-07-15 01:12:53.959245: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
+2023-07-15 01:12:56.752711: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
+2023-07-15 01:12:56.752854: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
+2023-07-15 01:12:56.752867: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
+2023-07-15 01:12:56.842172: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37381 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-40GB, pci bus id: 0000:07:00.0, compute capability: 8.0)
+2023-07-15 01:12:59.107600: 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.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet_formatting.stdout.txt

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fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet_model_params.tsv

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fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet_no_bias_formatting.stderr.txt

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fold_2/logs.models.fold_2.ENCSR011SAG/logfile.modelling.fold_2.ENCSR011SAG.chrombpnet_no_bias_formatting.stdout.txt

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