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- .gitattributes +7 -0
- README.md +120 -0
- fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet.params.json +11 -0
- fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet_fix_formatting.stdout.txt +406 -0
- fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet_model_params.tsv +9 -0
- fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.stdout_v1.txt +3 -0
- fold_0/model.bias_scaled.fold_0.ENCSR672MOG.h5 +3 -0
- fold_0/model.bias_scaled.fold_0.ENCSR672MOG.tar +3 -0
- fold_0/model.chrombpnet.fold_0.ENCSR672MOG.h5 +3 -0
- fold_0/model.chrombpnet.fold_0.ENCSR672MOG.tar +3 -0
- fold_0/model.chrombpnet_nobias.fold_0.ENCSR672MOG.h5 +3 -0
- fold_0/model.chrombpnet_nobias.fold_0.ENCSR672MOG.tar +3 -0
- fold_1/logs.models.fold_1.ENCSR672MOG/logfile.modelling.fold_1.ENCSR672MOG.stdout.txt +3 -0
- fold_1/logs.models.fold_1.ENCSR672MOG/logfile.modelling.fold_1.ENCSR672MOG.stdout_v1.txt +3 -0
- fold_1/model.bias_scaled.fold_1.ENCSR672MOG.h5 +3 -0
- fold_1/model.bias_scaled.fold_1.ENCSR672MOG.tar +3 -0
- fold_1/model.chrombpnet.fold_1.ENCSR672MOG.h5 +3 -0
- fold_1/model.chrombpnet.fold_1.ENCSR672MOG.tar +3 -0
- fold_1/model.chrombpnet_nobias.fold_1.ENCSR672MOG.h5 +3 -0
- fold_1/model.chrombpnet_nobias.fold_1.ENCSR672MOG.tar +3 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.args.json +23 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.batch_loss.tsv +0 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.bias_formatting.stderr.txt +38 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.bias_formatting.stdout.txt +1 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet.params.json +11 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_data_params.tsv +3 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_formatting.stderr.txt +40 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_formatting.stdout.txt +1 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_model_params.tsv +9 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_no_bias_formatting.stderr.txt +1 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_no_bias_formatting.stdout.txt +1 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.epoch_loss.csv +18 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stderr.txt +332 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stdout.txt +3 -0
- fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stdout_v1.txt +3 -0
- fold_2/model.bias_scaled.fold_2.ENCSR672MOG.h5 +3 -0
- fold_2/model.bias_scaled.fold_2.ENCSR672MOG.tar +3 -0
- fold_2/model.chrombpnet.fold_2.ENCSR672MOG.h5 +3 -0
- fold_2/model.chrombpnet.fold_2.ENCSR672MOG.tar +3 -0
- fold_2/model.chrombpnet_nobias.fold_2.ENCSR672MOG.h5 +3 -0
- fold_2/model.chrombpnet_nobias.fold_2.ENCSR672MOG.tar +3 -0
- fold_3/model.bias_scaled.fold_3.ENCSR672MOG.h5 +3 -0
- fold_3/model.bias_scaled.fold_3.ENCSR672MOG.tar +3 -0
- fold_3/model.chrombpnet.fold_3.ENCSR672MOG.h5 +3 -0
- fold_3/model.chrombpnet.fold_3.ENCSR672MOG.tar +3 -0
- fold_3/model.chrombpnet_nobias.fold_3.ENCSR672MOG.h5 +3 -0
- fold_3/model.chrombpnet_nobias.fold_3.ENCSR672MOG.tar +3 -0
- fold_4/logs.models.fold_4.ENCSR672MOG/logfile.modelling.fold_4.ENCSR672MOG.stdout.txt +3 -0
- fold_4/logs.models.fold_4.ENCSR672MOG/logfile.modelling.fold_4.ENCSR672MOG.stdout_v1.txt +3 -0
- fold_4/model.bias_scaled.fold_4.ENCSR672MOG.h5 +3 -0
.gitattributes
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fold_1/logs.models.fold_1.ENCSR672MOG/logfile.modelling.fold_1.ENCSR672MOG.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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fold_1/logs.models.fold_1.ENCSR672MOG/logfile.modelling.fold_1.ENCSR672MOG.stdout.txt filter=lfs diff=lfs merge=lfs -text
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fold_4/logs.models.fold_4.ENCSR672MOG/logfile.modelling.fold_4.ENCSR672MOG.stdout.txt filter=lfs diff=lfs merge=lfs -text
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fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stdout.txt filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
+
---
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| 2 |
+
license: mit
|
| 3 |
+
library_name: chrombpnet
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| 4 |
+
tags:
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| 5 |
+
- encode
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| 6 |
+
- chrombpnet
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| 7 |
+
- chromatin-accessibility
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| 8 |
+
- DNASE
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- nerve
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- hg38
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| 11 |
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---
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| 12 |
+
# ENCODE ChromBPNet Atlas
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+
As part of the ENCODE 4 Project, we trained ChromBPNet models on 1,512 ENCODE DNAse-seq and ATAC-seq across 408 biosamples. Here, we provide all models for open-source use.
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+
|
| 15 |
+
For more information about the models, see:
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| 16 |
+
- Main ENCODE 4 Paper
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| 17 |
+
- [A unified lexicon of predictive DNA sequence motifs from ENCODE transcription factor binding and chromatin accessibility assays](https://doi.org/10.5281/zenodo.17123347)
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| 18 |
+
- [ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants](https://doi.org/10.1101/2024.12.25.630221)
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| 19 |
+
|
| 20 |
+
## ChromBPNet model: DNASE in sciatic nerve (ENCSR672MOG)
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| 21 |
+
- Model: ChromBPNet
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| 22 |
+
- Assay: DNASE-seq
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| 23 |
+
- Experiment: [ENCSR672MOG](https://www.encodeproject.org/experiments/ENCSR672MOG/)
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| 24 |
+
- Model annotation: [ENCSR903LXC](https://www.encodeproject.org/annotations/ENCSR903LXC/)
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| 25 |
+
- Biosample: sciatic nerve (Homo sapiens sciatic nerve tissue female adult (41 years))
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| 26 |
+
- Cell slim(s): None
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| 27 |
+
- Organ slim(s): nerve
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| 28 |
+
- Developmental slim(s): ectoderm
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| 29 |
+
- System slim(s): peripheral-nervous-system
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| 30 |
+
- Assembly: hg38
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| 31 |
+
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| 32 |
+
## Directory structure
|
| 33 |
+
- `fold_0`: Model: Cross-validation fold: Fold 0
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| 34 |
+
- `model.chrombpnet.fold_0.encid.h5`: full chrombpnet model that combines both bias and corrected model in .h5 format
|
| 35 |
+
- `model.chrombpnet_nobias.fold_0.encid.h5`: bias-corrected accessibility model in .h5 format (Use for all biological discovery)
|
| 36 |
+
- `model.bias_scaled.fold_0.encid.h5`: bias model in .h5 format
|
| 37 |
+
- `model.chrombpnet.fold_0.encid.tar`: full chrombpnet model that combines both bias and corrected model in SavedModel format. After being untarred, it results in a directory named "chrombpnet".
|
| 38 |
+
- `model.chrombpnet_nobias.fold_0.encid.tar`: bias-corrected accessibility model in SavedModel format (Use for all biological discovery). After being untarred, it results in a directory named "chrombpnet_wo_bias".
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| 39 |
+
- `model.bias_scaled.fold_0.encid.tar`: bias model in SavedModel format. After being untarred, it results in a directory named "bias_model_scaled".
|
| 40 |
+
- `logs.models.fold_0.encid`: folder containing log files for training models
|
| 41 |
+
- `fold_1`: Model: Cross-validation fold: Fold 1
|
| 42 |
+
- `fold_2`: Model: Cross-validation fold: Fold 2
|
| 43 |
+
- `fold_3`: Model: Cross-validation fold: Fold 3
|
| 44 |
+
- `fold_4`: Model: Cross-validation fold: Fold 4
|
| 45 |
+
|
| 46 |
+
# Instructions
|
| 47 |
+
## (1) Pseudocode for loading models in .h5 format
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| 48 |
+
|
| 49 |
+
(1) Use the code in python after appropriately defining `model_in_h5_format` and `inputs`.
|
| 50 |
+
(2) `inputs` is a one hot encoded sequence of shape (N,2114,4). Here N corresponds to the
|
| 51 |
+
number of tested sequences, 2114 is the input sequence length and 4 corresponds to [A,C,G,T].
|
| 52 |
+
|
| 53 |
+
```python
|
| 54 |
+
import tensorflow as tf
|
| 55 |
+
from tensorflow.keras.utils import get_custom_objects
|
| 56 |
+
from tensorflow.keras.models import load_model
|
| 57 |
+
|
| 58 |
+
custom_objects={"tf": tf}
|
| 59 |
+
get_custom_objects().update(custom_objects)
|
| 60 |
+
|
| 61 |
+
model=load_model(model_in_h5_format,compile=False)
|
| 62 |
+
outputs = model(inputs)
|
| 63 |
+
```
|
| 64 |
+
|
| 65 |
+
The list `outputs` consists of two elements. The first element has a shape of (N, 1000) and
|
| 66 |
+
contains logit predictions for a 1000-base-pair output. The second element, with a shape of
|
| 67 |
+
(N, 1), contains logcount predictions. To transform these predictions into per-base signals,
|
| 68 |
+
follow the provided pseudo code lines below.
|
| 69 |
+
|
| 70 |
+
```python
|
| 71 |
+
import numpy as np
|
| 72 |
+
|
| 73 |
+
def softmax(x, temp=1):
|
| 74 |
+
norm_x = x - np.mean(x,axis=1, keepdims=True)
|
| 75 |
+
return np.exp(temp*norm_x)/np.sum(np.exp(temp*norm_x), axis=1, keepdims=True)
|
| 76 |
+
|
| 77 |
+
predictions = softmax(outputs[0]) * (np.exp(outputs[1])-1)
|
| 78 |
+
```
|
| 79 |
+
|
| 80 |
+
## (2) Pseudocode for loading models in .tar format
|
| 81 |
+
|
| 82 |
+
(1) First untar the directory as follows `tar -xvf model.tar`
|
| 83 |
+
(2) Use the code below in python after appropriately defining `model_dir_untared` and `inputs`
|
| 84 |
+
(3) `inputs` is a one hot encoded sequence of shape (N,2114,4). Here N corresponds to the number
|
| 85 |
+
of tested sequences, 2114 is the input sequence length and 4 corresponds to ACGT.
|
| 86 |
+
|
| 87 |
+
Reference: https://www.tensorflow.org/api_docs/python/tf/saved_model/load
|
| 88 |
+
|
| 89 |
+
```python
|
| 90 |
+
import tensorflow as tf
|
| 91 |
+
|
| 92 |
+
model = tf.saved_model.load('model_dir_untared')
|
| 93 |
+
outputs = model.signatures['serving_default'](**{'sequence':inputs.astype('float32')})
|
| 94 |
+
```
|
| 95 |
+
|
| 96 |
+
The variable `outputs` represents a dictionary containing two key-value pairs. The first key
|
| 97 |
+
is `logits_profile_predictions`, holding a value with a shape of (N, 1000). This value corresponds
|
| 98 |
+
to logit predictions for a 1000-base-pair output. The second key, named `logcount_predictions``,
|
| 99 |
+
is associated with a value of shape (N, 1), representing logcount predictions. To transform these
|
| 100 |
+
predictions into per-base signals, utilize the provided pseudo code lines mentioned below.
|
| 101 |
+
|
| 102 |
+
```python
|
| 103 |
+
import numpy as np
|
| 104 |
+
def softmax(x, temp=1):
|
| 105 |
+
norm_x = x - np.mean(x,axis=1, keepdims=True)
|
| 106 |
+
return np.exp(temp*norm_x)/np.sum(np.exp(temp*norm_x), axis=1, keepdims=True)
|
| 107 |
+
|
| 108 |
+
predictions = softmax(outputs["logits_profile_predictions"]) * (np.exp(outputs["logcount_predictions"])-1)
|
| 109 |
+
```
|
| 110 |
+
|
| 111 |
+
## Docker image to load and use the models
|
| 112 |
+
https://hub.docker.com/r/kundajelab/chrombpnet-atlas/ (tag:v1)
|
| 113 |
+
|
| 114 |
+
## Code for ChromBPNet
|
| 115 |
+
- https://github.com/kundajelab/chrombpnet/
|
| 116 |
+
|
| 117 |
+
# License & citation
|
| 118 |
+
External data users may freely download, analyze and publish results based on any ENCODE data without restrictions.
|
| 119 |
+
|
| 120 |
+
Released under the [ENCODE data-use policy](https://www.encodeproject.org/about/data-use-policy/). Please cite the ENCODE Project Consortium and the model software: [ChromBPNet](https://github.com/kundajelab/chrombpnet) (Pampari et al., bioRxiv 2024).
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fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet.params.json
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{
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| 2 |
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"counts_loss_weight": "20.8",
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| 3 |
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"filters": "512",
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| 4 |
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"n_dil_layers": "8",
|
| 5 |
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"bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5",
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"inputlen": "2114",
|
| 7 |
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"outputlen": "1000",
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| 8 |
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"max_jitter": "500",
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| 9 |
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"chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
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| 10 |
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"negative_sampling_ratio": "0.1"
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| 11 |
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}
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fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet_fix_formatting.stdout.txt
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|
| 1 |
+
Sun Aug 20 01:05:30 2023
|
| 2 |
+
+---------------------------------------------------------------------------------------+
|
| 3 |
+
| NVIDIA-SMI 535.54.03 Driver Version: 535.54.03 CUDA Version: 12.2 |
|
| 4 |
+
|-----------------------------------------+----------------------+----------------------+
|
| 5 |
+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
|
| 6 |
+
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
|
| 7 |
+
| | | MIG M. |
|
| 8 |
+
|=========================================+======================+======================|
|
| 9 |
+
| 0 Tesla P100-PCIE-16GB On | 00000000:04:00.0 Off | 0 |
|
| 10 |
+
| N/A 36C P0 30W / 250W | 0MiB / 16384MiB | 0% E. Process |
|
| 11 |
+
| | | N/A |
|
| 12 |
+
+-----------------------------------------+----------------------+----------------------+
|
| 13 |
+
|
| 14 |
+
+---------------------------------------------------------------------------------------+
|
| 15 |
+
| Processes: |
|
| 16 |
+
| GPU GI CI PID Type Process name GPU Memory |
|
| 17 |
+
| ID ID Usage |
|
| 18 |
+
|=======================================================================================|
|
| 19 |
+
| No running processes found |
|
| 20 |
+
+---------------------------------------------------------------------------------------+
|
| 21 |
+
singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python fix_h5_for_chrombpnet.py -e ENCSR672MOG -d DNASE
|
| 22 |
+
tissue
|
| 23 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombpnet_model_encsr880cub_bias/chrombpnet.h5
|
| 24 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombpnet_model_encsr880cub_bias/chrombpnet_wo_bias.h5
|
| 25 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5
|
| 26 |
+
cd /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombpnet_model_encsr880cub_bias/new_chrombpnet_model/ && tar -cf chrombpnet_new.tar chrombpnet_new/
|
| 27 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_1/chrombpnet.h5
|
| 28 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_1/chrombpnet_wo_bias.h5
|
| 29 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_1/bias_model_scaled.h5
|
| 30 |
+
chrombpnet model found
|
| 31 |
+
Model: "model_1"
|
| 32 |
+
__________________________________________________________________________________________________
|
| 33 |
+
Layer (type) Output Shape Param # Connected to
|
| 34 |
+
==================================================================================================
|
| 35 |
+
sequence (InputLayer) [(None, 2114, 4)] 0
|
| 36 |
+
__________________________________________________________________________________________________
|
| 37 |
+
wo_bias_bpnet_1st_conv (Conv1D) (None, 2094, 512) 43520 sequence[0][0]
|
| 38 |
+
__________________________________________________________________________________________________
|
| 39 |
+
wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 wo_bias_bpnet_1st_conv[0][0]
|
| 40 |
+
__________________________________________________________________________________________________
|
| 41 |
+
wo_bias_bpnet_1crop (Cropping1D (None, 2090, 512) 0 wo_bias_bpnet_1st_conv[0][0]
|
| 42 |
+
__________________________________________________________________________________________________
|
| 43 |
+
add (Add) (None, 2090, 512) 0 wo_bias_bpnet_1conv[0][0]
|
| 44 |
+
wo_bias_bpnet_1crop[0][0]
|
| 45 |
+
__________________________________________________________________________________________________
|
| 46 |
+
wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 add[0][0]
|
| 47 |
+
__________________________________________________________________________________________________
|
| 48 |
+
wo_bias_bpnet_2crop (Cropping1D (None, 2082, 512) 0 add[0][0]
|
| 49 |
+
__________________________________________________________________________________________________
|
| 50 |
+
add_1 (Add) (None, 2082, 512) 0 wo_bias_bpnet_2conv[0][0]
|
| 51 |
+
wo_bias_bpnet_2crop[0][0]
|
| 52 |
+
__________________________________________________________________________________________________
|
| 53 |
+
wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 add_1[0][0]
|
| 54 |
+
__________________________________________________________________________________________________
|
| 55 |
+
wo_bias_bpnet_3crop (Cropping1D (None, 2066, 512) 0 add_1[0][0]
|
| 56 |
+
__________________________________________________________________________________________________
|
| 57 |
+
add_2 (Add) (None, 2066, 512) 0 wo_bias_bpnet_3conv[0][0]
|
| 58 |
+
wo_bias_bpnet_3crop[0][0]
|
| 59 |
+
__________________________________________________________________________________________________
|
| 60 |
+
wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 add_2[0][0]
|
| 61 |
+
__________________________________________________________________________________________________
|
| 62 |
+
wo_bias_bpnet_4crop (Cropping1D (None, 2034, 512) 0 add_2[0][0]
|
| 63 |
+
__________________________________________________________________________________________________
|
| 64 |
+
add_3 (Add) (None, 2034, 512) 0 wo_bias_bpnet_4conv[0][0]
|
| 65 |
+
wo_bias_bpnet_4crop[0][0]
|
| 66 |
+
__________________________________________________________________________________________________
|
| 67 |
+
wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 add_3[0][0]
|
| 68 |
+
__________________________________________________________________________________________________
|
| 69 |
+
wo_bias_bpnet_5crop (Cropping1D (None, 1970, 512) 0 add_3[0][0]
|
| 70 |
+
__________________________________________________________________________________________________
|
| 71 |
+
add_4 (Add) (None, 1970, 512) 0 wo_bias_bpnet_5conv[0][0]
|
| 72 |
+
wo_bias_bpnet_5crop[0][0]
|
| 73 |
+
__________________________________________________________________________________________________
|
| 74 |
+
wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 add_4[0][0]
|
| 75 |
+
__________________________________________________________________________________________________
|
| 76 |
+
wo_bias_bpnet_6crop (Cropping1D (None, 1842, 512) 0 add_4[0][0]
|
| 77 |
+
__________________________________________________________________________________________________
|
| 78 |
+
add_5 (Add) (None, 1842, 512) 0 wo_bias_bpnet_6conv[0][0]
|
| 79 |
+
wo_bias_bpnet_6crop[0][0]
|
| 80 |
+
__________________________________________________________________________________________________
|
| 81 |
+
wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 add_5[0][0]
|
| 82 |
+
__________________________________________________________________________________________________
|
| 83 |
+
wo_bias_bpnet_7crop (Cropping1D (None, 1586, 512) 0 add_5[0][0]
|
| 84 |
+
__________________________________________________________________________________________________
|
| 85 |
+
add_6 (Add) (None, 1586, 512) 0 wo_bias_bpnet_7conv[0][0]
|
| 86 |
+
wo_bias_bpnet_7crop[0][0]
|
| 87 |
+
__________________________________________________________________________________________________
|
| 88 |
+
wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 add_6[0][0]
|
| 89 |
+
__________________________________________________________________________________________________
|
| 90 |
+
wo_bias_bpnet_8crop (Cropping1D (None, 1074, 512) 0 add_6[0][0]
|
| 91 |
+
__________________________________________________________________________________________________
|
| 92 |
+
add_7 (Add) (None, 1074, 512) 0 wo_bias_bpnet_8conv[0][0]
|
| 93 |
+
wo_bias_bpnet_8crop[0][0]
|
| 94 |
+
__________________________________________________________________________________________________
|
| 95 |
+
wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 add_7[0][0]
|
| 96 |
+
__________________________________________________________________________________________________
|
| 97 |
+
wo_bias_bpnet_logitt_before_fla (None, 1000, 1) 0 wo_bias_bpnet_prof_out_precrop[0]
|
| 98 |
+
__________________________________________________________________________________________________
|
| 99 |
+
gap (GlobalAveragePooling1D) (None, 512) 0 add_7[0][0]
|
| 100 |
+
__________________________________________________________________________________________________
|
| 101 |
+
wo_bias_bpnet_logits_profile_pr (None, 1000) 0 wo_bias_bpnet_logitt_before_flatt
|
| 102 |
+
__________________________________________________________________________________________________
|
| 103 |
+
wo_bias_bpnet_logcount_predicti (None, 1) 513 gap[0][0]
|
| 104 |
+
==================================================================================================
|
| 105 |
+
Total params: 6,377,986
|
| 106 |
+
Trainable params: 6,377,986
|
| 107 |
+
Non-trainable params: 0
|
| 108 |
+
__________________________________________________________________________________________________
|
| 109 |
+
None
|
| 110 |
+
wo_bias_bpnet_1st_conv
|
| 111 |
+
wo_bias_bpnet_1conv
|
| 112 |
+
wo_bias_bpnet_2conv
|
| 113 |
+
wo_bias_bpnet_3conv
|
| 114 |
+
wo_bias_bpnet_4conv
|
| 115 |
+
wo_bias_bpnet_5conv
|
| 116 |
+
wo_bias_bpnet_6conv
|
| 117 |
+
wo_bias_bpnet_7conv
|
| 118 |
+
wo_bias_bpnet_8conv
|
| 119 |
+
wo_bias_bpnet_logcount_predictions
|
| 120 |
+
wo_bias_bpnet_prof_out_precrop
|
| 121 |
+
True
|
| 122 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet.h5
|
| 123 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5
|
| 124 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5
|
| 125 |
+
chrombpnet model found
|
| 126 |
+
Model: "model_1"
|
| 127 |
+
__________________________________________________________________________________________________
|
| 128 |
+
Layer (type) Output Shape Param # Connected to
|
| 129 |
+
==================================================================================================
|
| 130 |
+
sequence (InputLayer) [(None, 2114, 4)] 0
|
| 131 |
+
__________________________________________________________________________________________________
|
| 132 |
+
wo_bias_bpnet_1st_conv (Conv1D) (None, 2094, 512) 43520 sequence[0][0]
|
| 133 |
+
__________________________________________________________________________________________________
|
| 134 |
+
wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 wo_bias_bpnet_1st_conv[0][0]
|
| 135 |
+
__________________________________________________________________________________________________
|
| 136 |
+
wo_bias_bpnet_1crop (Cropping1D (None, 2090, 512) 0 wo_bias_bpnet_1st_conv[0][0]
|
| 137 |
+
__________________________________________________________________________________________________
|
| 138 |
+
add (Add) (None, 2090, 512) 0 wo_bias_bpnet_1conv[0][0]
|
| 139 |
+
wo_bias_bpnet_1crop[0][0]
|
| 140 |
+
__________________________________________________________________________________________________
|
| 141 |
+
wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 add[0][0]
|
| 142 |
+
__________________________________________________________________________________________________
|
| 143 |
+
wo_bias_bpnet_2crop (Cropping1D (None, 2082, 512) 0 add[0][0]
|
| 144 |
+
__________________________________________________________________________________________________
|
| 145 |
+
add_1 (Add) (None, 2082, 512) 0 wo_bias_bpnet_2conv[0][0]
|
| 146 |
+
wo_bias_bpnet_2crop[0][0]
|
| 147 |
+
__________________________________________________________________________________________________
|
| 148 |
+
wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 add_1[0][0]
|
| 149 |
+
__________________________________________________________________________________________________
|
| 150 |
+
wo_bias_bpnet_3crop (Cropping1D (None, 2066, 512) 0 add_1[0][0]
|
| 151 |
+
__________________________________________________________________________________________________
|
| 152 |
+
add_2 (Add) (None, 2066, 512) 0 wo_bias_bpnet_3conv[0][0]
|
| 153 |
+
wo_bias_bpnet_3crop[0][0]
|
| 154 |
+
__________________________________________________________________________________________________
|
| 155 |
+
wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 add_2[0][0]
|
| 156 |
+
__________________________________________________________________________________________________
|
| 157 |
+
wo_bias_bpnet_4crop (Cropping1D (None, 2034, 512) 0 add_2[0][0]
|
| 158 |
+
__________________________________________________________________________________________________
|
| 159 |
+
add_3 (Add) (None, 2034, 512) 0 wo_bias_bpnet_4conv[0][0]
|
| 160 |
+
wo_bias_bpnet_4crop[0][0]
|
| 161 |
+
__________________________________________________________________________________________________
|
| 162 |
+
wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 add_3[0][0]
|
| 163 |
+
__________________________________________________________________________________________________
|
| 164 |
+
wo_bias_bpnet_5crop (Cropping1D (None, 1970, 512) 0 add_3[0][0]
|
| 165 |
+
__________________________________________________________________________________________________
|
| 166 |
+
add_4 (Add) (None, 1970, 512) 0 wo_bias_bpnet_5conv[0][0]
|
| 167 |
+
wo_bias_bpnet_5crop[0][0]
|
| 168 |
+
__________________________________________________________________________________________________
|
| 169 |
+
wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 add_4[0][0]
|
| 170 |
+
__________________________________________________________________________________________________
|
| 171 |
+
wo_bias_bpnet_6crop (Cropping1D (None, 1842, 512) 0 add_4[0][0]
|
| 172 |
+
__________________________________________________________________________________________________
|
| 173 |
+
add_5 (Add) (None, 1842, 512) 0 wo_bias_bpnet_6conv[0][0]
|
| 174 |
+
wo_bias_bpnet_6crop[0][0]
|
| 175 |
+
__________________________________________________________________________________________________
|
| 176 |
+
wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 add_5[0][0]
|
| 177 |
+
__________________________________________________________________________________________________
|
| 178 |
+
wo_bias_bpnet_7crop (Cropping1D (None, 1586, 512) 0 add_5[0][0]
|
| 179 |
+
__________________________________________________________________________________________________
|
| 180 |
+
add_6 (Add) (None, 1586, 512) 0 wo_bias_bpnet_7conv[0][0]
|
| 181 |
+
wo_bias_bpnet_7crop[0][0]
|
| 182 |
+
__________________________________________________________________________________________________
|
| 183 |
+
wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 add_6[0][0]
|
| 184 |
+
__________________________________________________________________________________________________
|
| 185 |
+
wo_bias_bpnet_8crop (Cropping1D (None, 1074, 512) 0 add_6[0][0]
|
| 186 |
+
__________________________________________________________________________________________________
|
| 187 |
+
add_7 (Add) (None, 1074, 512) 0 wo_bias_bpnet_8conv[0][0]
|
| 188 |
+
wo_bias_bpnet_8crop[0][0]
|
| 189 |
+
__________________________________________________________________________________________________
|
| 190 |
+
wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 add_7[0][0]
|
| 191 |
+
__________________________________________________________________________________________________
|
| 192 |
+
wo_bias_bpnet_logitt_before_fla (None, 1000, 1) 0 wo_bias_bpnet_prof_out_precrop[0]
|
| 193 |
+
__________________________________________________________________________________________________
|
| 194 |
+
gap (GlobalAveragePooling1D) (None, 512) 0 add_7[0][0]
|
| 195 |
+
__________________________________________________________________________________________________
|
| 196 |
+
wo_bias_bpnet_logits_profile_pr (None, 1000) 0 wo_bias_bpnet_logitt_before_flatt
|
| 197 |
+
__________________________________________________________________________________________________
|
| 198 |
+
wo_bias_bpnet_logcount_predicti (None, 1) 513 gap[0][0]
|
| 199 |
+
==================================================================================================
|
| 200 |
+
Total params: 6,377,986
|
| 201 |
+
Trainable params: 6,377,986
|
| 202 |
+
Non-trainable params: 0
|
| 203 |
+
__________________________________________________________________________________________________
|
| 204 |
+
None
|
| 205 |
+
wo_bias_bpnet_1st_conv
|
| 206 |
+
wo_bias_bpnet_1conv
|
| 207 |
+
wo_bias_bpnet_2conv
|
| 208 |
+
wo_bias_bpnet_3conv
|
| 209 |
+
wo_bias_bpnet_4conv
|
| 210 |
+
wo_bias_bpnet_5conv
|
| 211 |
+
wo_bias_bpnet_6conv
|
| 212 |
+
wo_bias_bpnet_7conv
|
| 213 |
+
wo_bias_bpnet_8conv
|
| 214 |
+
wo_bias_bpnet_logcount_predictions
|
| 215 |
+
wo_bias_bpnet_prof_out_precrop
|
| 216 |
+
True
|
| 217 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_3/chrombpnet.h5
|
| 218 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_3/chrombpnet_wo_bias.h5
|
| 219 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_3/bias_model_scaled.h5
|
| 220 |
+
chrombpnet model found
|
| 221 |
+
Model: "model_1"
|
| 222 |
+
__________________________________________________________________________________________________
|
| 223 |
+
Layer (type) Output Shape Param # Connected to
|
| 224 |
+
==================================================================================================
|
| 225 |
+
sequence (InputLayer) [(None, 2114, 4)] 0
|
| 226 |
+
__________________________________________________________________________________________________
|
| 227 |
+
wo_bias_bpnet_1st_conv (Conv1D) (None, 2094, 512) 43520 sequence[0][0]
|
| 228 |
+
__________________________________________________________________________________________________
|
| 229 |
+
wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 wo_bias_bpnet_1st_conv[0][0]
|
| 230 |
+
__________________________________________________________________________________________________
|
| 231 |
+
wo_bias_bpnet_1crop (Cropping1D (None, 2090, 512) 0 wo_bias_bpnet_1st_conv[0][0]
|
| 232 |
+
__________________________________________________________________________________________________
|
| 233 |
+
add (Add) (None, 2090, 512) 0 wo_bias_bpnet_1conv[0][0]
|
| 234 |
+
wo_bias_bpnet_1crop[0][0]
|
| 235 |
+
__________________________________________________________________________________________________
|
| 236 |
+
wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 add[0][0]
|
| 237 |
+
__________________________________________________________________________________________________
|
| 238 |
+
wo_bias_bpnet_2crop (Cropping1D (None, 2082, 512) 0 add[0][0]
|
| 239 |
+
__________________________________________________________________________________________________
|
| 240 |
+
add_1 (Add) (None, 2082, 512) 0 wo_bias_bpnet_2conv[0][0]
|
| 241 |
+
wo_bias_bpnet_2crop[0][0]
|
| 242 |
+
__________________________________________________________________________________________________
|
| 243 |
+
wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 add_1[0][0]
|
| 244 |
+
__________________________________________________________________________________________________
|
| 245 |
+
wo_bias_bpnet_3crop (Cropping1D (None, 2066, 512) 0 add_1[0][0]
|
| 246 |
+
__________________________________________________________________________________________________
|
| 247 |
+
add_2 (Add) (None, 2066, 512) 0 wo_bias_bpnet_3conv[0][0]
|
| 248 |
+
wo_bias_bpnet_3crop[0][0]
|
| 249 |
+
__________________________________________________________________________________________________
|
| 250 |
+
wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 add_2[0][0]
|
| 251 |
+
__________________________________________________________________________________________________
|
| 252 |
+
wo_bias_bpnet_4crop (Cropping1D (None, 2034, 512) 0 add_2[0][0]
|
| 253 |
+
__________________________________________________________________________________________________
|
| 254 |
+
add_3 (Add) (None, 2034, 512) 0 wo_bias_bpnet_4conv[0][0]
|
| 255 |
+
wo_bias_bpnet_4crop[0][0]
|
| 256 |
+
__________________________________________________________________________________________________
|
| 257 |
+
wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 add_3[0][0]
|
| 258 |
+
__________________________________________________________________________________________________
|
| 259 |
+
wo_bias_bpnet_5crop (Cropping1D (None, 1970, 512) 0 add_3[0][0]
|
| 260 |
+
__________________________________________________________________________________________________
|
| 261 |
+
add_4 (Add) (None, 1970, 512) 0 wo_bias_bpnet_5conv[0][0]
|
| 262 |
+
wo_bias_bpnet_5crop[0][0]
|
| 263 |
+
__________________________________________________________________________________________________
|
| 264 |
+
wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 add_4[0][0]
|
| 265 |
+
__________________________________________________________________________________________________
|
| 266 |
+
wo_bias_bpnet_6crop (Cropping1D (None, 1842, 512) 0 add_4[0][0]
|
| 267 |
+
__________________________________________________________________________________________________
|
| 268 |
+
add_5 (Add) (None, 1842, 512) 0 wo_bias_bpnet_6conv[0][0]
|
| 269 |
+
wo_bias_bpnet_6crop[0][0]
|
| 270 |
+
__________________________________________________________________________________________________
|
| 271 |
+
wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 add_5[0][0]
|
| 272 |
+
__________________________________________________________________________________________________
|
| 273 |
+
wo_bias_bpnet_7crop (Cropping1D (None, 1586, 512) 0 add_5[0][0]
|
| 274 |
+
__________________________________________________________________________________________________
|
| 275 |
+
add_6 (Add) (None, 1586, 512) 0 wo_bias_bpnet_7conv[0][0]
|
| 276 |
+
wo_bias_bpnet_7crop[0][0]
|
| 277 |
+
__________________________________________________________________________________________________
|
| 278 |
+
wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 add_6[0][0]
|
| 279 |
+
__________________________________________________________________________________________________
|
| 280 |
+
wo_bias_bpnet_8crop (Cropping1D (None, 1074, 512) 0 add_6[0][0]
|
| 281 |
+
__________________________________________________________________________________________________
|
| 282 |
+
add_7 (Add) (None, 1074, 512) 0 wo_bias_bpnet_8conv[0][0]
|
| 283 |
+
wo_bias_bpnet_8crop[0][0]
|
| 284 |
+
__________________________________________________________________________________________________
|
| 285 |
+
wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 add_7[0][0]
|
| 286 |
+
__________________________________________________________________________________________________
|
| 287 |
+
wo_bias_bpnet_logitt_before_fla (None, 1000, 1) 0 wo_bias_bpnet_prof_out_precrop[0]
|
| 288 |
+
__________________________________________________________________________________________________
|
| 289 |
+
gap (GlobalAveragePooling1D) (None, 512) 0 add_7[0][0]
|
| 290 |
+
__________________________________________________________________________________________________
|
| 291 |
+
wo_bias_bpnet_logits_profile_pr (None, 1000) 0 wo_bias_bpnet_logitt_before_flatt
|
| 292 |
+
__________________________________________________________________________________________________
|
| 293 |
+
wo_bias_bpnet_logcount_predicti (None, 1) 513 gap[0][0]
|
| 294 |
+
==================================================================================================
|
| 295 |
+
Total params: 6,377,986
|
| 296 |
+
Trainable params: 6,377,986
|
| 297 |
+
Non-trainable params: 0
|
| 298 |
+
__________________________________________________________________________________________________
|
| 299 |
+
None
|
| 300 |
+
wo_bias_bpnet_1st_conv
|
| 301 |
+
wo_bias_bpnet_1conv
|
| 302 |
+
wo_bias_bpnet_2conv
|
| 303 |
+
wo_bias_bpnet_3conv
|
| 304 |
+
wo_bias_bpnet_4conv
|
| 305 |
+
wo_bias_bpnet_5conv
|
| 306 |
+
wo_bias_bpnet_6conv
|
| 307 |
+
wo_bias_bpnet_7conv
|
| 308 |
+
wo_bias_bpnet_8conv
|
| 309 |
+
wo_bias_bpnet_logcount_predictions
|
| 310 |
+
wo_bias_bpnet_prof_out_precrop
|
| 311 |
+
True
|
| 312 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_4/chrombpnet.h5
|
| 313 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_4/chrombpnet_wo_bias.h5
|
| 314 |
+
/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE/ENCSR672MOG/chrombppnet_model_encsr880cub_bias_fold_4/bias_model_scaled.h5
|
| 315 |
+
chrombpnet model found
|
| 316 |
+
Model: "model_1"
|
| 317 |
+
__________________________________________________________________________________________________
|
| 318 |
+
Layer (type) Output Shape Param # Connected to
|
| 319 |
+
==================================================================================================
|
| 320 |
+
sequence (InputLayer) [(None, 2114, 4)] 0
|
| 321 |
+
__________________________________________________________________________________________________
|
| 322 |
+
wo_bias_bpnet_1st_conv (Conv1D) (None, 2094, 512) 43520 sequence[0][0]
|
| 323 |
+
__________________________________________________________________________________________________
|
| 324 |
+
wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 wo_bias_bpnet_1st_conv[0][0]
|
| 325 |
+
__________________________________________________________________________________________________
|
| 326 |
+
wo_bias_bpnet_1crop (Cropping1D (None, 2090, 512) 0 wo_bias_bpnet_1st_conv[0][0]
|
| 327 |
+
__________________________________________________________________________________________________
|
| 328 |
+
add (Add) (None, 2090, 512) 0 wo_bias_bpnet_1conv[0][0]
|
| 329 |
+
wo_bias_bpnet_1crop[0][0]
|
| 330 |
+
__________________________________________________________________________________________________
|
| 331 |
+
wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 add[0][0]
|
| 332 |
+
__________________________________________________________________________________________________
|
| 333 |
+
wo_bias_bpnet_2crop (Cropping1D (None, 2082, 512) 0 add[0][0]
|
| 334 |
+
__________________________________________________________________________________________________
|
| 335 |
+
add_1 (Add) (None, 2082, 512) 0 wo_bias_bpnet_2conv[0][0]
|
| 336 |
+
wo_bias_bpnet_2crop[0][0]
|
| 337 |
+
__________________________________________________________________________________________________
|
| 338 |
+
wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 add_1[0][0]
|
| 339 |
+
__________________________________________________________________________________________________
|
| 340 |
+
wo_bias_bpnet_3crop (Cropping1D (None, 2066, 512) 0 add_1[0][0]
|
| 341 |
+
__________________________________________________________________________________________________
|
| 342 |
+
add_2 (Add) (None, 2066, 512) 0 wo_bias_bpnet_3conv[0][0]
|
| 343 |
+
wo_bias_bpnet_3crop[0][0]
|
| 344 |
+
__________________________________________________________________________________________________
|
| 345 |
+
wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 add_2[0][0]
|
| 346 |
+
__________________________________________________________________________________________________
|
| 347 |
+
wo_bias_bpnet_4crop (Cropping1D (None, 2034, 512) 0 add_2[0][0]
|
| 348 |
+
__________________________________________________________________________________________________
|
| 349 |
+
add_3 (Add) (None, 2034, 512) 0 wo_bias_bpnet_4conv[0][0]
|
| 350 |
+
wo_bias_bpnet_4crop[0][0]
|
| 351 |
+
__________________________________________________________________________________________________
|
| 352 |
+
wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 add_3[0][0]
|
| 353 |
+
__________________________________________________________________________________________________
|
| 354 |
+
wo_bias_bpnet_5crop (Cropping1D (None, 1970, 512) 0 add_3[0][0]
|
| 355 |
+
__________________________________________________________________________________________________
|
| 356 |
+
add_4 (Add) (None, 1970, 512) 0 wo_bias_bpnet_5conv[0][0]
|
| 357 |
+
wo_bias_bpnet_5crop[0][0]
|
| 358 |
+
__________________________________________________________________________________________________
|
| 359 |
+
wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 add_4[0][0]
|
| 360 |
+
__________________________________________________________________________________________________
|
| 361 |
+
wo_bias_bpnet_6crop (Cropping1D (None, 1842, 512) 0 add_4[0][0]
|
| 362 |
+
__________________________________________________________________________________________________
|
| 363 |
+
add_5 (Add) (None, 1842, 512) 0 wo_bias_bpnet_6conv[0][0]
|
| 364 |
+
wo_bias_bpnet_6crop[0][0]
|
| 365 |
+
__________________________________________________________________________________________________
|
| 366 |
+
wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 add_5[0][0]
|
| 367 |
+
__________________________________________________________________________________________________
|
| 368 |
+
wo_bias_bpnet_7crop (Cropping1D (None, 1586, 512) 0 add_5[0][0]
|
| 369 |
+
__________________________________________________________________________________________________
|
| 370 |
+
add_6 (Add) (None, 1586, 512) 0 wo_bias_bpnet_7conv[0][0]
|
| 371 |
+
wo_bias_bpnet_7crop[0][0]
|
| 372 |
+
__________________________________________________________________________________________________
|
| 373 |
+
wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 add_6[0][0]
|
| 374 |
+
__________________________________________________________________________________________________
|
| 375 |
+
wo_bias_bpnet_8crop (Cropping1D (None, 1074, 512) 0 add_6[0][0]
|
| 376 |
+
__________________________________________________________________________________________________
|
| 377 |
+
add_7 (Add) (None, 1074, 512) 0 wo_bias_bpnet_8conv[0][0]
|
| 378 |
+
wo_bias_bpnet_8crop[0][0]
|
| 379 |
+
__________________________________________________________________________________________________
|
| 380 |
+
wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 add_7[0][0]
|
| 381 |
+
__________________________________________________________________________________________________
|
| 382 |
+
wo_bias_bpnet_logitt_before_fla (None, 1000, 1) 0 wo_bias_bpnet_prof_out_precrop[0]
|
| 383 |
+
__________________________________________________________________________________________________
|
| 384 |
+
gap (GlobalAveragePooling1D) (None, 512) 0 add_7[0][0]
|
| 385 |
+
__________________________________________________________________________________________________
|
| 386 |
+
wo_bias_bpnet_logits_profile_pr (None, 1000) 0 wo_bias_bpnet_logitt_before_flatt
|
| 387 |
+
__________________________________________________________________________________________________
|
| 388 |
+
wo_bias_bpnet_logcount_predicti (None, 1) 513 gap[0][0]
|
| 389 |
+
==================================================================================================
|
| 390 |
+
Total params: 6,377,986
|
| 391 |
+
Trainable params: 6,377,986
|
| 392 |
+
Non-trainable params: 0
|
| 393 |
+
__________________________________________________________________________________________________
|
| 394 |
+
None
|
| 395 |
+
wo_bias_bpnet_1st_conv
|
| 396 |
+
wo_bias_bpnet_1conv
|
| 397 |
+
wo_bias_bpnet_2conv
|
| 398 |
+
wo_bias_bpnet_3conv
|
| 399 |
+
wo_bias_bpnet_4conv
|
| 400 |
+
wo_bias_bpnet_5conv
|
| 401 |
+
wo_bias_bpnet_6conv
|
| 402 |
+
wo_bias_bpnet_7conv
|
| 403 |
+
wo_bias_bpnet_8conv
|
| 404 |
+
wo_bias_bpnet_logcount_predictions
|
| 405 |
+
wo_bias_bpnet_prof_out_precrop
|
| 406 |
+
True
|
fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.chrombpnet_model_params.tsv
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
counts_loss_weight 20.8
|
| 2 |
+
filters 512
|
| 3 |
+
n_dil_layers 8
|
| 4 |
+
bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//chrombpnet_model_encsr880cub_bias/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_0.json
|
| 9 |
+
negative_sampling_ratio 0.1
|
fold_0/logs.models.fold_0.ENCSR672MOG/logfile.modelling.fold_0.ENCSR672MOG.stdout_v1.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5685807f78fd7062f128b21175d188bba9bfcdb95f8892d3e432aeb020c9fd0e
|
| 3 |
+
size 14171991
|
fold_0/model.bias_scaled.fold_0.ENCSR672MOG.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:135f373c554627ad8a108a72409e1e5aa929d7143fe756f17bf9ebaaeb53dd0b
|
| 3 |
+
size 2688440
|
fold_0/model.bias_scaled.fold_0.ENCSR672MOG.tar
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a40f0b4da1c7d8f93b7a529d3714834d742c370110a8249b76077773a230c226
|
| 3 |
+
size 1198080
|
fold_0/model.chrombpnet.fold_0.ENCSR672MOG.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f2c90d6e36bb8e91c9ecd706260e2c39548712811f574780833a28b69dc86ee6
|
| 3 |
+
size 26447928
|
fold_0/model.chrombpnet.fold_0.ENCSR672MOG.tar
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
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ADDED
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ADDED
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ADDED
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version https://git-lfs.github.com/spec/v1
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fold_1/model.chrombpnet.fold_1.ENCSR672MOG.h5
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version https://git-lfs.github.com/spec/v1
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fold_1/model.chrombpnet.fold_1.ENCSR672MOG.tar
ADDED
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size 27607040
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fold_1/model.chrombpnet_nobias.fold_1.ENCSR672MOG.h5
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version https://git-lfs.github.com/spec/v1
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size 25583536
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fold_1/model.chrombpnet_nobias.fold_1.ENCSR672MOG.tar
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version https://git-lfs.github.com/spec/v1
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oid sha256:0577a4111e1b3cbc4dcfa2d6c6ff87a17a862163637e51b246684be7dd777c0a
|
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size 26081280
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.args.json
ADDED
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| 1 |
+
{
|
| 2 |
+
"genome": "/scratch/groups/akundaje/anusri/chromatin_atlas/reference/hg38.genome.fa",
|
| 3 |
+
"bigwig": "/oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR672MOG//preprocessing/bigWigs/ENCSR672MOG.bigWig",
|
| 4 |
+
"peaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2//filtered.peaks.bed",
|
| 5 |
+
"nonpeaks": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2//filtered.nonpeaks.bed",
|
| 6 |
+
"output_prefix": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//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",
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| 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/ENCSR672MOG//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.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.batch_loss.tsv
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+
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 02:36:24.986154: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 4 |
+
2023-07-15 02:36:28.037899: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 5 |
+
2023-07-15 02:36:28.044401: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 6 |
+
2023-07-15 02:36:28.076722: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 7 |
+
pciBusID: 0000:03:00.0 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 02:36:28.076800: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 10 |
+
2023-07-15 02:36:28.109992: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 11 |
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2023-07-15 02:36:28.110112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
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+
2023-07-15 02:36:28.126410: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 13 |
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2023-07-15 02:36:28.133080: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 14 |
+
2023-07-15 02:36:28.158554: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 15 |
+
2023-07-15 02:36:28.164717: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 16 |
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2023-07-15 02:36:28.166046: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 17 |
+
2023-07-15 02:36:28.182475: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 18 |
+
2023-07-15 02:36:28.182908: 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 02:36:28.183868: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 21 |
+
2023-07-15 02:36:28.184933: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 22 |
+
pciBusID: 0000:03:00.0 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 02:36:28.184971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 25 |
+
2023-07-15 02:36:28.185009: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 26 |
+
2023-07-15 02:36:28.185032: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 27 |
+
2023-07-15 02:36:28.185053: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 28 |
+
2023-07-15 02:36:28.185074: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 29 |
+
2023-07-15 02:36:28.185095: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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| 30 |
+
2023-07-15 02:36:28.185116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 31 |
+
2023-07-15 02:36:28.185138: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 32 |
+
2023-07-15 02:36:28.189196: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 33 |
+
2023-07-15 02:36:28.190615: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 34 |
+
2023-07-15 02:36:30.113134: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 35 |
+
2023-07-15 02:36:30.113228: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 36 |
+
2023-07-15 02:36:30.113246: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 37 |
+
2023-07-15 02:36:30.124588: 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)
|
| 38 |
+
2023-07-15 02:36:30.992403: 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.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.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//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/bias_model_scaled
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet.params.json
ADDED
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+
{
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| 2 |
+
"counts_loss_weight": "20.8",
|
| 3 |
+
"filters": "512",
|
| 4 |
+
"n_dil_layers": "8",
|
| 5 |
+
"bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//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.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_data_params.tsv
ADDED
|
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| 1 |
+
counts_sum_min_thresh 20.0
|
| 2 |
+
counts_sum_max_thresh 3874.48
|
| 3 |
+
trainings_pts_post_thresh 177763
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_formatting.stderr.txt
ADDED
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| 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 01:35:00.446508: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 4 |
+
2023-07-15 01:35:02.768303: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 5 |
+
2023-07-15 01:35:02.771624: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 6 |
+
2023-07-15 01:35:03.247927: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 7 |
+
pciBusID: 0000:8a: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 01:35:03.248002: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 10 |
+
2023-07-15 01:35:03.265632: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 11 |
+
2023-07-15 01:35:03.265681: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 12 |
+
2023-07-15 01:35:03.274997: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 13 |
+
2023-07-15 01:35:03.279302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 14 |
+
2023-07-15 01:35:03.294675: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 15 |
+
2023-07-15 01:35:03.298747: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 16 |
+
2023-07-15 01:35:03.299630: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 17 |
+
2023-07-15 01:35:03.310833: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 18 |
+
2023-07-15 01:35:03.311221: 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 01:35:03.312424: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 21 |
+
2023-07-15 01:35:03.318917: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 22 |
+
pciBusID: 0000:8a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 23 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 24 |
+
2023-07-15 01:35:03.318959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 25 |
+
2023-07-15 01:35:03.318989: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 26 |
+
2023-07-15 01:35:03.319011: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 27 |
+
2023-07-15 01:35:03.319031: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 28 |
+
2023-07-15 01:35:03.319051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 29 |
+
2023-07-15 01:35:03.319070: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 30 |
+
2023-07-15 01:35:03.319089: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 31 |
+
2023-07-15 01:35:03.319108: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 32 |
+
2023-07-15 01:35:03.367627: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 33 |
+
2023-07-15 01:35:03.370041: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 34 |
+
2023-07-15 01:35:06.665149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 35 |
+
2023-07-15 01:35:06.665260: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 36 |
+
2023-07-15 01:35:06.665273: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 37 |
+
2023-07-15 01:35:06.814032: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:8a:00.0, compute capability: 8.0)
|
| 38 |
+
2023-07-15 01:35:08.885251: 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.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.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//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.chrombpnet_model_params.tsv
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
counts_loss_weight 20.8
|
| 2 |
+
filters 512
|
| 3 |
+
n_dil_layers 8
|
| 4 |
+
bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//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.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.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//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.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//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.epoch_loss.csv
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
|
| 2 |
+
0,1.6094857454299927,691.991455078125,725.4683227539062,0.384331613779068,710.5374755859375,718.5317993164062
|
| 3 |
+
1,0.3747389614582062,659.16845703125,666.96240234375,0.3210064172744751,705.992919921875,712.6697387695312
|
| 4 |
+
2,0.3346666693687439,651.5318603515625,658.4934692382812,0.2860475182533264,699.2505493164062,705.2007446289062
|
| 5 |
+
3,0.31154873967170715,645.911865234375,652.3905029296875,0.2823723554611206,696.8991088867188,702.7720947265625
|
| 6 |
+
4,0.2912597060203552,642.8418579101562,648.8994140625,0.2868572175502777,690.2918090820312,696.258544921875
|
| 7 |
+
5,0.27457424998283386,639.16943359375,644.880126953125,0.29428932070732117,689.3873291015625,695.5088500976562
|
| 8 |
+
6,0.2677061855792999,637.6209716796875,643.1898193359375,0.26822659373283386,691.5794067382812,697.1583251953125
|
| 9 |
+
7,0.2545042037963867,635.4576416015625,640.7527465820312,0.3099289834499359,686.8641967773438,693.3109741210938
|
| 10 |
+
8,0.24839386343955994,633.5927124023438,638.759765625,0.32401466369628906,692.3016967773438,699.040771484375
|
| 11 |
+
9,0.24322275817394257,631.2125854492188,636.2718505859375,0.3014647364616394,689.6543579101562,695.9248657226562
|
| 12 |
+
10,0.2372054159641266,629.538330078125,634.47119140625,0.28684812784194946,690.968505859375,696.9347534179688
|
| 13 |
+
11,0.212617427110672,623.4627075195312,627.885009765625,0.2386186420917511,687.1268310546875,692.0907592773438
|
| 14 |
+
12,0.2069040834903717,619.5013427734375,623.8051147460938,0.2640482485294342,687.7653198242188,693.25732421875
|
| 15 |
+
13,0.20102395117282867,616.9718017578125,621.1533203125,0.23410753905773163,692.2532958984375,697.123046875
|
| 16 |
+
14,0.19423887133598328,614.1522216796875,618.1931762695312,0.23656189441680908,689.7716674804688,694.6923828125
|
| 17 |
+
15,0.18533657491207123,609.7149658203125,613.5703735351562,0.23439949750900269,688.0457763671875,692.921142578125
|
| 18 |
+
16,0.17923638224601746,607.9235229492188,611.6514892578125,0.24617815017700195,690.8587646484375,695.9795532226562
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stderr.txt
ADDED
|
@@ -0,0 +1,332 @@
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|
|
| 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 |
+
INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
|
| 4 |
+
INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
|
| 5 |
+
2022-10-17 08:30:53.604528: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 6 |
+
2022-10-17 08:38:40.266245: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 7 |
+
2022-10-17 08:38:40.272847: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 8 |
+
2022-10-17 08:38:40.796091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 9 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 10 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 11 |
+
2022-10-17 08:38:40.796217: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 12 |
+
2022-10-17 08:38:40.838616: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 13 |
+
2022-10-17 08:38:40.838833: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 14 |
+
2022-10-17 08:38:40.864618: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 15 |
+
2022-10-17 08:38:40.873907: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 16 |
+
2022-10-17 08:38:40.902162: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 17 |
+
2022-10-17 08:38:40.910155: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 18 |
+
2022-10-17 08:38:40.912256: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 19 |
+
2022-10-17 08:38:40.917748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 20 |
+
2022-10-17 08:38:40.918254: 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
|
| 21 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 22 |
+
2022-10-17 08:38:40.918414: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 23 |
+
2022-10-17 08:38:40.920103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 24 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 25 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 26 |
+
2022-10-17 08:38:40.920168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 27 |
+
2022-10-17 08:38:40.920208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 28 |
+
2022-10-17 08:38:40.920232: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 29 |
+
2022-10-17 08:38:40.920256: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 30 |
+
2022-10-17 08:38:40.920279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 31 |
+
2022-10-17 08:38:40.920301: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 32 |
+
2022-10-17 08:38:40.920322: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 33 |
+
2022-10-17 08:38:40.920344: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 34 |
+
2022-10-17 08:38:40.923387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 35 |
+
2022-10-17 08:38:40.925489: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 36 |
+
2022-10-17 08:38:43.173183: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 37 |
+
2022-10-17 08:38:43.173303: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 38 |
+
2022-10-17 08:38:43.173323: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 39 |
+
2022-10-17 08:38:43.180418: 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)
|
| 40 |
+
2022-10-17 08:38:45.322888: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 41 |
+
2022-10-17 08:38:45.350732: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 42 |
+
2022-10-17 08:38:45.647027: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 43 |
+
2022-10-17 08:38:47.652277: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 44 |
+
2022-10-17 08:38:47.666509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 45 |
+
2022-10-17 08:39:24.193919: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 46 |
+
2022-10-17 08:39:26.721334: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 47 |
+
2022-10-17 08:39:26.722625: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 48 |
+
2022-10-17 08:39:27.055381: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 49 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 50 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 51 |
+
2022-10-17 08:39:27.055499: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 52 |
+
2022-10-17 08:39:27.059294: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 53 |
+
2022-10-17 08:39:27.059430: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 54 |
+
2022-10-17 08:39:27.061289: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 55 |
+
2022-10-17 08:39:27.061870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 56 |
+
2022-10-17 08:39:27.065455: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 57 |
+
2022-10-17 08:39:27.066496: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 58 |
+
2022-10-17 08:39:27.067056: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 59 |
+
2022-10-17 08:39:27.069034: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 60 |
+
2022-10-17 08:39:27.069516: 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
|
| 61 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 62 |
+
2022-10-17 08:39:27.069813: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 63 |
+
2022-10-17 08:39:27.070857: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 64 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 65 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 66 |
+
2022-10-17 08:39:27.070899: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 67 |
+
2022-10-17 08:39:27.070937: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 68 |
+
2022-10-17 08:39:27.070959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 69 |
+
2022-10-17 08:39:27.070979: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 70 |
+
2022-10-17 08:39:27.070998: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 71 |
+
2022-10-17 08:39:27.071016: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 72 |
+
2022-10-17 08:39:27.071034: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 73 |
+
2022-10-17 08:39:27.071054: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 74 |
+
2022-10-17 08:39:27.072806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 75 |
+
2022-10-17 08:39:27.072856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 76 |
+
2022-10-17 08:39:27.710129: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 77 |
+
2022-10-17 08:39:27.710245: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 78 |
+
2022-10-17 08:39:27.710264: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 79 |
+
2022-10-17 08:39:27.713280: 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)
|
| 80 |
+
2022-10-17 08:46:41.474903: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 81 |
+
2022-10-17 08:46:41.475439: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 82 |
+
2022-10-17 08:46:43.384469: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 83 |
+
2022-10-17 08:46:44.055708: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 84 |
+
2022-10-17 08:46:44.080617: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 85 |
+
2022-10-17 08:46:47.672246: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
|
| 86 |
+
2022-10-17 10:37:50.616789: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 87 |
+
2022-10-17 10:37:53.240798: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 88 |
+
2022-10-17 10:37:53.242237: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 89 |
+
2022-10-17 10:37:53.384149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 90 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 91 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 92 |
+
2022-10-17 10:37:53.384214: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 93 |
+
2022-10-17 10:37:53.386515: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 94 |
+
2022-10-17 10:37:53.386561: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 95 |
+
2022-10-17 10:37:53.387566: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 96 |
+
2022-10-17 10:37:53.387856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 97 |
+
2022-10-17 10:37:53.389828: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 98 |
+
2022-10-17 10:37:53.390338: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 99 |
+
2022-10-17 10:37:53.390791: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 100 |
+
2022-10-17 10:37:53.392480: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 101 |
+
2022-10-17 10:37:53.392820: 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
|
| 102 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 103 |
+
2022-10-17 10:37:53.392946: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 104 |
+
2022-10-17 10:37:53.393832: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 105 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 106 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 107 |
+
2022-10-17 10:37:53.393855: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 108 |
+
2022-10-17 10:37:53.393872: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 109 |
+
2022-10-17 10:37:53.393886: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 110 |
+
2022-10-17 10:37:53.393898: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 111 |
+
2022-10-17 10:37:53.393910: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 112 |
+
2022-10-17 10:37:53.393922: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 113 |
+
2022-10-17 10:37:53.393934: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 114 |
+
2022-10-17 10:37:53.393945: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 115 |
+
2022-10-17 10:37:53.395545: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 116 |
+
2022-10-17 10:37:53.395580: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 117 |
+
2022-10-17 10:37:53.808474: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 118 |
+
2022-10-17 10:37:53.808579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 119 |
+
2022-10-17 10:37:53.808601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 120 |
+
2022-10-17 10:37:53.811491: 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)
|
| 121 |
+
2022-10-17 10:39:24.233488: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 122 |
+
2022-10-17 10:39:24.236239: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 123 |
+
2022-10-17 10:39:24.304712: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 124 |
+
2022-10-17 10:39:24.727047: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 125 |
+
2022-10-17 10:39:24.729538: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 126 |
+
/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.
|
| 127 |
+
, UserWarning)
|
| 128 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
|
| 129 |
+
cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
|
| 130 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
|
| 131 |
+
profile_prob = profile / np.sum(profile)
|
| 132 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
|
| 133 |
+
shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
|
| 134 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
|
| 135 |
+
curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
|
| 136 |
+
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.
|
| 137 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 138 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 139 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 140 |
+
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.
|
| 141 |
+
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.
|
| 142 |
+
2022-10-17 10:41:13.749194: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 143 |
+
2022-10-17 10:41:16.040848: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 144 |
+
2022-10-17 10:41:16.042430: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 145 |
+
2022-10-17 10:41:16.190091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 146 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 147 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 148 |
+
2022-10-17 10:41:16.190162: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 149 |
+
2022-10-17 10:41:16.192344: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 150 |
+
2022-10-17 10:41:16.192388: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 151 |
+
2022-10-17 10:41:16.193301: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 152 |
+
2022-10-17 10:41:16.193683: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 153 |
+
2022-10-17 10:41:16.195680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 154 |
+
2022-10-17 10:41:16.196298: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 155 |
+
2022-10-17 10:41:16.196604: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 156 |
+
2022-10-17 10:41:16.198294: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 157 |
+
2022-10-17 10:41:16.198593: 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
|
| 158 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 159 |
+
2022-10-17 10:41:16.198675: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 160 |
+
2022-10-17 10:41:16.199624: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 161 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 162 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 163 |
+
2022-10-17 10:41:16.199648: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 164 |
+
2022-10-17 10:41:16.199665: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 165 |
+
2022-10-17 10:41:16.199679: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 166 |
+
2022-10-17 10:41:16.199691: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 167 |
+
2022-10-17 10:41:16.199704: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 168 |
+
2022-10-17 10:41:16.199716: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 169 |
+
2022-10-17 10:41:16.199727: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 170 |
+
2022-10-17 10:41:16.199739: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 171 |
+
2022-10-17 10:41:16.201332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 172 |
+
2022-10-17 10:41:16.201383: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 173 |
+
2022-10-17 10:41:16.626778: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 174 |
+
2022-10-17 10:41:16.626873: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 175 |
+
2022-10-17 10:41:16.626886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 176 |
+
2022-10-17 10:41:16.629699: 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)
|
| 177 |
+
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
|
| 178 |
+
2022-10-17 10:42:20.405339: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 179 |
+
2022-10-17 10:42:20.407552: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 180 |
+
2022-10-17 10:42:20.452918: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 181 |
+
2022-10-17 10:42:20.863320: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 182 |
+
2022-10-17 10:42:20.865107: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 183 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
|
| 184 |
+
cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
|
| 185 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
|
| 186 |
+
profile_prob = profile / np.sum(profile)
|
| 187 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
|
| 188 |
+
shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
|
| 189 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
|
| 190 |
+
curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
|
| 191 |
+
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.
|
| 192 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 193 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 194 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 195 |
+
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.
|
| 196 |
+
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.
|
| 197 |
+
2022-10-17 10:44:05.483830: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 198 |
+
2022-10-17 10:44:07.753223: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 199 |
+
2022-10-17 10:44:07.754848: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 200 |
+
2022-10-17 10:44:07.878370: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 201 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 202 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 203 |
+
2022-10-17 10:44:07.878439: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 204 |
+
2022-10-17 10:44:07.880739: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 205 |
+
2022-10-17 10:44:07.880787: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 206 |
+
2022-10-17 10:44:07.881868: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 207 |
+
2022-10-17 10:44:07.882269: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 208 |
+
2022-10-17 10:44:07.884219: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 209 |
+
2022-10-17 10:44:07.884807: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 210 |
+
2022-10-17 10:44:07.885232: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 211 |
+
2022-10-17 10:44:07.886954: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 212 |
+
2022-10-17 10:44:07.887246: 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
|
| 213 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 214 |
+
2022-10-17 10:44:07.887372: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 215 |
+
2022-10-17 10:44:07.888225: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 216 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 217 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 218 |
+
2022-10-17 10:44:07.888246: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 219 |
+
2022-10-17 10:44:07.888279: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 220 |
+
2022-10-17 10:44:07.888295: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 221 |
+
2022-10-17 10:44:07.888308: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 222 |
+
2022-10-17 10:44:07.888321: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 223 |
+
2022-10-17 10:44:07.888333: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 224 |
+
2022-10-17 10:44:07.888345: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 225 |
+
2022-10-17 10:44:07.888357: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 226 |
+
2022-10-17 10:44:07.889957: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 227 |
+
2022-10-17 10:44:07.889993: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 228 |
+
2022-10-17 10:44:08.309119: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 229 |
+
2022-10-17 10:44:08.309221: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 230 |
+
2022-10-17 10:44:08.309234: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 231 |
+
2022-10-17 10:44:08.312046: 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)
|
| 232 |
+
2022-10-17 10:45:09.888608: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 233 |
+
2022-10-17 10:45:09.890396: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 234 |
+
2022-10-17 10:45:09.921126: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 235 |
+
2022-10-17 10:45:10.343161: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 236 |
+
2022-10-17 10:45:10.344684: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 237 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
|
| 238 |
+
cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
|
| 239 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
|
| 240 |
+
profile_prob = profile / np.sum(profile)
|
| 241 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
|
| 242 |
+
shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
|
| 243 |
+
/home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
|
| 244 |
+
curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
|
| 245 |
+
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.
|
| 246 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 247 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 248 |
+
findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
|
| 249 |
+
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.
|
| 250 |
+
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.
|
| 251 |
+
2022-10-17 10:46:04.384651: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 252 |
+
2022-10-17 10:46:05.503301: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 253 |
+
2022-10-17 10:46:05.504671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 254 |
+
2022-10-17 10:46:05.628145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 255 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 256 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 257 |
+
2022-10-17 10:46:05.628228: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 258 |
+
2022-10-17 10:46:05.630445: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 259 |
+
2022-10-17 10:46:05.630496: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 260 |
+
2022-10-17 10:46:05.631508: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 261 |
+
2022-10-17 10:46:05.631905: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 262 |
+
2022-10-17 10:46:05.633886: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 263 |
+
2022-10-17 10:46:05.634475: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 264 |
+
2022-10-17 10:46:05.634859: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 265 |
+
2022-10-17 10:46:05.636515: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 266 |
+
2022-10-17 10:46:05.636798: 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
|
| 267 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 268 |
+
2022-10-17 10:46:05.636941: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 269 |
+
2022-10-17 10:46:05.637830: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 270 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 271 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 272 |
+
2022-10-17 10:46:05.637862: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 273 |
+
2022-10-17 10:46:05.637878: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 274 |
+
2022-10-17 10:46:05.637892: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 275 |
+
2022-10-17 10:46:05.637905: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 276 |
+
2022-10-17 10:46:05.637917: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 277 |
+
2022-10-17 10:46:05.637929: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 278 |
+
2022-10-17 10:46:05.637941: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 279 |
+
2022-10-17 10:46:05.637953: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 280 |
+
2022-10-17 10:46:05.639571: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 281 |
+
2022-10-17 10:46:05.639625: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 282 |
+
2022-10-17 10:46:06.052637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 283 |
+
2022-10-17 10:46:06.052740: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 284 |
+
2022-10-17 10:46:06.052754: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 285 |
+
2022-10-17 10:46:06.055542: 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)
|
| 286 |
+
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
|
| 287 |
+
2022-10-17 10:46:16.151544: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 288 |
+
2022-10-17 10:46:16.152049: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 289 |
+
2022-10-17 10:46:16.320981: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 290 |
+
2022-10-17 10:46:16.764803: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 291 |
+
2022-10-17 10:46:16.766575: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 292 |
+
mkdir: cannot create directory ‘/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR672MOG//chrombppnet_model_encsr880cub_bias_fold_2//footprints’: File exists
|
| 293 |
+
2022-10-17 10:47:57.174367: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 294 |
+
2022-10-17 10:47:58.225463: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 295 |
+
2022-10-17 10:47:58.237592: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
|
| 296 |
+
2022-10-17 10:47:58.359017: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 297 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 298 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 299 |
+
2022-10-17 10:47:58.359098: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 300 |
+
2022-10-17 10:47:58.361192: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 301 |
+
2022-10-17 10:47:58.361236: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 302 |
+
2022-10-17 10:47:58.362215: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 303 |
+
2022-10-17 10:47:58.362539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 304 |
+
2022-10-17 10:47:58.364480: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 305 |
+
2022-10-17 10:47:58.365065: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 306 |
+
2022-10-17 10:47:58.365491: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 307 |
+
2022-10-17 10:47:58.367145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 308 |
+
2022-10-17 10:47:58.367416: 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
|
| 309 |
+
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
|
| 310 |
+
2022-10-17 10:47:58.367569: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
|
| 311 |
+
2022-10-17 10:47:58.368458: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
|
| 312 |
+
pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
|
| 313 |
+
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
|
| 314 |
+
2022-10-17 10:47:58.368485: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 315 |
+
2022-10-17 10:47:58.368501: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 316 |
+
2022-10-17 10:47:58.368515: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 317 |
+
2022-10-17 10:47:58.368527: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
|
| 318 |
+
2022-10-17 10:47:58.368539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
|
| 319 |
+
2022-10-17 10:47:58.368551: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
|
| 320 |
+
2022-10-17 10:47:58.368562: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
|
| 321 |
+
2022-10-17 10:47:58.368574: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
| 322 |
+
2022-10-17 10:47:58.370175: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
|
| 323 |
+
2022-10-17 10:47:58.370213: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
|
| 324 |
+
2022-10-17 10:47:58.793882: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
|
| 325 |
+
2022-10-17 10:47:58.793980: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
|
| 326 |
+
2022-10-17 10:47:58.793993: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
|
| 327 |
+
2022-10-17 10:47:58.796816: 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)
|
| 328 |
+
2022-10-17 10:48:08.646783: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
|
| 329 |
+
2022-10-17 10:48:08.647292: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2449945000 Hz
|
| 330 |
+
2022-10-17 10:48:08.766566: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
|
| 331 |
+
2022-10-17 10:48:09.229473: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
|
| 332 |
+
2022-10-17 10:48:09.231131: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
|
fold_2/logs.models.fold_2.ENCSR672MOG/logfile.modelling.fold_2.ENCSR672MOG.stdout.txt
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