ibmua

  var country_codes = [
    { code: 'AF', name: 'Afghanistan' },
    { code: 'AX', name: 'Åland Islands' },
    { code: 'AL', name: 'Albania' },
    { code: 'DZ', name: 'Algeria' },
    { code: 'AS', name: 'American Samoa' },
    { code: 'AD', name: 'Andorra' },
    { code: 'AO', name: 'Angola' },
    { code: 'AI', name: 'Anguilla' },
    { code: 'AQ', name: 'Antarctica' },

ibmua

/*
//	By Ihor Menshykov, MIT license

g++ sol.cpp -fsanitize=address -include bits/stdc++.h -O3 -pthread -lm -std=c++14 -o executables/executable && ulimit -Sv 1000000000000 && time ./executables/executable < ./ins/a

time g++ sol.cpp -O3 -pthread -lm -std=c++14 -o executables/executable && ./executables/executable < ./ins/a


time taskset --cpu-list 0 g++ sol.cpp -include bits/stdc++.h -O3 -pthread -lm -std=c++14 -o executables/executable && ulimit -Sv 1000000 &&
time ./executables/executable < ./ins/a

ibmua

/*
g++ -std=gnu++11 -fsanitize=address -O3 Lossy2dCompression.cpp -o Lossy2dCompression &&
java -jar tester.jar -exec "./Lossy2dCompression" -seed 9 -debug

g++ -std=gnu++11 -include bits/stdc++.h -O3 Lossy2dCompression.cpp -o Lossy2dCompression &&
java -jar tester.jar -exec "./Lossy2dCompression /path/to/store_result_for_seed_9 9" -seed 9 -novis

g++ -std=gnu++11 -include bits/stdc++.h -O3 Lossy2dCompression.cpp -o Lossy2dCompression &&
java -jar tester.jar -exec "./Lossy2dCompression /home/i/C/marathon/116/outs/a 9" -seed 9 -novis

ibmua

#	python3 launcher.py 0 parallel 4 name
#	DO CHANGE THE DIRECTORIES TO YOURS
#	ALSO, in ' /home/i/C/marathon/116/stats" -seed '  
#	/home/i/C/marathon/116/stats can be removed -- it's just for storing some additional statistics.
from multiprocessing.pool import ThreadPool
import os
import sys
import json
import random
import string

ibmua

# python3 vis.py or use a jupyter notebook
import os
import json
import random
import string
import time
import subprocess
from pathlib import Path
directory = '/home/i/C/marathon/116/outs/'

ibmua

1 0.36563468414359174
2 0.17885260845064882
3 0.28852262366620873
4 0.2514404966692652
5 0.06748542738613812
244169730541 0.23256174721268402
244169730542 0.26269463658657066
244169730543 0.22041798309044436
244169730544 0.16611180158391606
244169730545 0.23481191179623626

ibmua

# for use with https://github.com/1adrianb/face-alignment
import cv2
import numpy as np
import face_alignment
imread = cv2.imread
_DEAFAULT_JPG_QUALITY = 99
imwrite = partial(cv2.imwrite, params=[int(cv2.IMWRITE_JPEG_QUALITY), _DEAFAULT_JPG_QUALITY])


fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, device='cuda')

ibmua

>>   AI-Benchmark-v.0.1.2   
>>   Let the AI Games begin..

2020-11-11 16:50:17.642293: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2599990000 Hz
2020-11-11 16:50:17.643424: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x560d110 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-11-11 16:50:17.643440: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-11-11 16:50:17.645168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-11-11 16:50:17.767055: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x560f580 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-11-11 16:50:17.767084: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce RTX 3090, Compute Capability 8.6
2020-11-11 16:50:17.768002: I tensorflow/core/common_ru

ibmua

First goes 3080 Gigabyte Gaming OC, then 3080 MSI Gaming X Trio

>>   AI-Benchmark-v.0.1.2   
>>   Let the AI Games begin..

2020-11-11 17:04:23.002305: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2599990000 Hz
2020-11-11 17:04:23.003399: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5b4a090 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-11-11 17:04:23.003415: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-11-11 17:04:23.005150: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-11-11 17:04:23.108471: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5b4c500 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:

ibmua

'''
Copyright (c) 2020 Lucas Ryan

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so.