rreece

# Use an official centos7 image
FROM centos:7

RUN localedef -i fr_FR -c -f UTF-8 -A /usr/share/locale/locale.alias fr_FR.UTF-8
ENV LANG fr_FR.utf8

# gcc because we need regex and pyldap
# openldap-devel because we need pyldap
RUN yum update -y \
    && yum install -y https://centos7.iuscommunity.org/ius-release.rpm \

rreece

#!/usr/bin/env bash
log=mv_files.log
spare=/spare/ryan
dest=/cb/data/imagenet1k2/new/
while true; do
    if test -n "$(shopt -s nullglob; echo $spare/*)"
    then
        echo "Moving files to $dest"
        echo "Moving files to $dest" >> $log
        ls -rt1 $spare | head -n -10 | xargs -n 1 echo

rreece

import numpy as np
import tensorflow as tf

__author__ = "Sangwoong Yoon"

def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
    """
    Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
    For supervised learning, feed training inputs to X and training labels to Y.
    For unsupervised learning, only feed training inputs to X, and feed None to Y.

rreece

"""
Helper module for displaying ROOT canvases in ipython notebooks

Usage example:
    # Save this file as rootnotes.py to your working directory.
    
    import rootnotes
    c1 = rootnotes.default_canvas()
    fun1 = TF1( 'fun1', 'abs(sin(x)/x)', 0, 10)
    c1.SetGridx()

rreece

#!/usr/bin/env python

# Set up ROOT and RootCore
import ROOT
ROOT.gROOT.Macro('$ROOTCOREDIR/scripts/load_packages.C')

# Initialize the xAOD infrastructure
ROOT.xAOD.Init()

# Set up the input files (PDSF)