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# https://rtyley.github.io/bfg-repo-cleaner/

# check pack size
git count-objects -v -H

# download bfg and move to directory, rename to bfg
wget https://repo1.maven.org/maven2/com/madgag/bfg/1.13.0/bfg-1.13.0.jar

# clone mirror
git clone --mirror git://example.com/some-big-repo.git

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#install samba
sudo apt install samba

#check installation
whereis samba
# output :
# samba: /usr/sbin/samba /usr/lib/samba /etc/samba /usr/share/samba /usr/share/man/man7/samba.7.gz /usr/share/man/man8/samba.8.gz

# edit file
sudo nano /etc/samba/smb.conf

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# build images from Dockerfile
docker build -t horovod:latest horovod-docker-gpu

# get list images
docker images

# get list container
docker ps

# remove container

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# This Dockerfile specifically for using PyTorch 1.3.0
FROM nvidia/cuda:10.0-devel-ubuntu18.04

# TensorFlow version is tightly coupled to CUDA and cuDNN so it should be selected carefully
# ENV TENSORFLOW_VERSION=2.0.0
ENV PYTORCH_VERSION=1.3.0
ENV TORCHVISION_VERSION=0.4.1
ENV CUDNN_VERSION=7.6.0.64-1+cuda10.0
ENV NCCL_VERSION=2.4.7-1+cuda10.0
# ENV MXNET_VERSION=1.5.0

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# Install nvidia-container-toolkit
# source : https://github.com/NVIDIA/nvidia-docker#ubuntu-16041804-debian-jessiestretchbuster
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit

# Install nvidia-runtime
# Download nvidia-runtime packages

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# add the GPG key for the official Docker repository to the system
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

# add the Docker repository to APT sources
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

# update the package database with the Docker packages from the newly added repo
sudo apt-get update

# install from the Docker repo instead of the default Ubuntu 16.04 repo

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# https://stackoverflow.com/questions/8751653/how-to-convert-a-binary-string-into-a-float-value
# http://weitz.de/ieee/

from codecs import decode
import struct


def bin_to_float(b):
    """ Convert binary string to a float. """
    bf = int_to_bytes(int(b, 2), 8)  # 8 bytes needed for IEEE 754 binary64.

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# get actual name of file before extension
file = 'my.report.txt'
print file.rsplit('.', 1)[0]

# list of comprehension
words = [w.replace('[br]', '<br />') for w in words]

# get intersection of list
def intersection(lst1, lst2): 
    temp = set(lst2) 

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# Get amount of directories and files
tree <FOLDER_NAME>/ | tail -1

# get amount of file
find . | wc -l

# zip file
zip -r output_file.zip file1 folder1
# add -q for quiet operation
zip -q -r output_file.zip file1 folder1

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import os, random, shutil

#Prompting user to enter number of files to select randomly along with directory
source=input("Enter the Source Directory : ")
dest=input("Enter the Destination Directory : ")
no_of_files=int(input("Enter The Number of Files To Select : "))

print("%"*25+"{ Details Of Transfer }"+"%"*25)
print("\n\nList of Files Moved to %s :-"%(dest))