StevenSong

#!/usr/bin/env python

# eog not bundled with your distro?
# no sudo access?
# do it all with python!
# easiest to use with miniconda env with matplotlib

import sys
import matplotlib.pyplot as plt
from PIL import Image

StevenSong

import os
import re
import gzip
import hashlib
from tqdm import tqdm
from bs4 import BeautifulSoup, SoupStrainer

fnames = []
for fname in os.listdir('PubMed'):
    if fname.endswith('.xml'):

StevenSong

import tensorflow as tf
b = tf.constant(21306806, dtype=tf.float32)
print((1+b)-b)
print(1+(b-b))

StevenSong

# Launch jupyter notebook in a new tmux session for Colab to connect to
# https://research.google.com/colaboratory/local-runtimes.html

SESSION=colab

tmux new -d -s $SESSION
tmux send-keys -t $SESSION "jupyter notebook \
  --NotebookApp.allow_origin='https://colab.research.google.com' \
  --port=8888 \
  --NotebookApp.port_retries=0 \

StevenSong

#!/bin/bash

# Log files are stored in subdirectories of current directly: ./*/log*
# Log files contain output like: ROC AUC * {label} * = 0.NNN
# Where the AUC for a label on the test set is the last ocurrence of the above fragment in the file
#
# For example, in an experiment to predict "death", our results are in a 
# folder "experiment" with 10 subfolders "trial_N", where N is the trial number.
# Within each "trial_N" subfolder, there is a file "log" with output lines:
#

StevenSong

#!/bin/python
#
# usage:
# python dispatch.py \
#     --gpus 0-3 \
#     --bootstraps 0-9 \
#     --scripts \
#         train-simple.sh \
#         train-varied.sh \
#         train-deeper.sh