(Et pour voir les départements les plus accueillants, c'est ici: https://gist.github.com/cerisara/928ad03cf15c77dda8897c2cf49ef27d )
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| import mmap | |
| import torch | |
| import json | |
| import os | |
| from huggingface_hub import hf_hub_download | |
| def load_file(filename, device): | |
| with open(filename, mode="r", encoding="utf8") as file_obj: | |
| with mmap.mmap(file_obj.fileno(), length=0, access=mmap.ACCESS_READ) as m: |
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| import termuxgui as tg | |
| import sys | |
| import time | |
| import threading | |
| import os | |
| import datetime | |
| import calendar | |
| with tg.Connection() as c: | |
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| 01 46°05’58" 5°20’56" E AIN | |
| 02 49°33’34" 3°33’30" E AISNE | |
| 03 46°23’37" 3°11’18" E ALLIER | |
| 04 44°06’22" 6°14’38" E ALPES-DE-HAUTEPROVENCE | |
| 05 44°39’49" 6°15’47" E HAUTES-ALPES | |
| 06 43°56’15" 7°06’59" E ALPES-MARITIMES | |
| 07 44°45’06" 4°25’29" E ARDECHE | |
| 08 49°36’56" 4°38’27" E ARDENNES | |
| 09 42°55’15" 1°30’14" E ARIEGE | |
| 10 48°18’16" 4°09’42" E AUBE |
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| #!/bin/bash | |
| d=0.5 | |
| if [ $# -ge 2 ]; then | |
| echo "2parms $1 $2" | |
| d=$2 | |
| fi | |
| rm -f /tmp/pp.gp | |
| touch /tmp/pp.gp |
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| En ne comptant que les personnes décédées dans un autre département que leur département de naissance, | |
| voici les départements (à droite) ayant accueillis le plus de personnes jusqu'à la fin de leur vie: | |
| On retrouve, comme on pouvait s'y attendre, la région Parisienne et la côté d'azur qui accueillent le plus | |
| de personnes jusqu'à la fin de leur vie. | |
| Et dans l'autre sens, c'est la Lozère qui accueille le moins de monde en fin de vie ! | |
| (Ou alors, il y a un biais dans les données...) | |
| 6 96 | |
| 1991 98 |
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| #!/bin/bash | |
| # arxiv paper ID | |
| python2 getarxivid.py $1 > arxivids | |
| mkdir papers | |
| for i in $(cat arxivids) | |
| do |
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| import sys | |
| def getText(l): | |
| l=l.replace('\\citep','') | |
| l=l.replace('\\cite','') | |
| return l | |
| with open(sys.argv[1],'rb') as f : ls = f.readlines() | |
| empty=False |
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| Data Parallelization with multi-GPU over TensorFlow | |
| Jonathan Laserson <[email protected]> | |
| 9 oct. (Il y a 2 jours) | |
| À Keras-users Se désabonner | |
| Here is how to take an existing model and do data parallelization across multiple GPUs. |
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| #!/usr/bin/php -qC | |
| <?php | |
| /****************************************************************************** | |
| * | |
| * @file gitolab.php | |
| * @author Benoit Zohar | |
| * @link http://benoitzohar.fr/ | |
| * @last-edited 2015-01-09 | |
| * @description Migrate projects from Gitolite to GitLab |
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