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| # -*- coding: utf-8 -*- | |
| def quick_sort(arr): | |
| lower_than_or_equal_head = [elem for elem in arr if elem < arr[0]] | |
| greater_than_head = [elem for elem in arr if elem > arr[0]] | |
| if len(arr) < 2: return arr | |
| return quick_sort(lower_than_or_equal_head) + [arr[0]] + quick_sort(greater_than_head) | |
| print(quick_sort([1, 3, 4, 2, 1000, 10, 4])) |
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| def compute_clf(confusion_matrix: numpy.ndarray, classes: list): | |
| """ | |
| return TP, TN, FP, FN followed by the order of classes | |
| shape: (n_classes, 4) | |
| """ | |
| ret = list() | |
| total = confusion_matrix.sum() | |
| for index, _class in enumerate(classes): |
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| import threading | |
| import socket | |
| import time | |
| ADDR = '127.0.0.1' | |
| PORT = 8890 | |
| class Server: | |
| def __init__(self): |
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| //#define _GRIBCXX_DEBUG | |
| #include <bits/stdc++.h> | |
| # define rep(i, n) for (int i = 0; i < (int)(n); i++) | |
| using namespace std; | |
| int v, e, r; | |
| vector<long long> s, t, d; | |
| vector<long long> dist; | |
| const long long INF = 1LL<<50; |
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| //#define _GRIBCXX_DEBUG | |
| #include <bits/stdc++.h> | |
| # define rep(i, n) for (int i = 0; i < (int)(n); i++) | |
| using namespace std; | |
| using ll = long long; | |
| using P = pair<ll, int>; | |
| struct edge{ | |
| edge(int to, ll cost) : to(to), cost(cost) {}; |
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| import collections | |
| import tqdm | |
| import math | |
| class HMM: | |
| def __init__(self): | |
| pass |
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| #! /bin/zsh | |
| acat () { | |
| fsize=`du -k $1| awk '{print $1}'` | |
| if [ $(($fsize)) -gt 100 ]; then | |
| echo 'this file is too large' | |
| else | |
| cat $1 |
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| import argparse | |
| import subprocess | |
| import pathlib | |
| BASE_COMMAND = 'ffmpeg -fflags +genpts -i {input}' | |
| BASE_COMMAND += ' -c:a copy -c:v copy -threads 8 -sn -y {output}' | |
| def load_arguments(): |
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| In [39]: a = chainer.initializers.GlorotUniform(rng=numpy.random.seed(1)) | |
| In [40]: a2 = copy.deepcopy(a) | |
| In [41]: a(b) | |
| In [42]: b | |
| Out[42]: | |
| array([[-0.09089784, 0.24135339, -0.54759727, -0.21653382, -0.38695953, | |
| -0.44657069, -0.34368472, -0.16917975, -0.11308557, 0.0425216 ], |
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| In [33]: a = chainer.initializers.GlorotUniform(rng=numpy.random.seed(1)) | |
| In [34]: a(b) | |
| In [35]: b | |
| Out[35]: | |
| array([[-0.09089784, 0.24135339, -0.54759727, -0.21653382, -0.38695953, | |
| -0.44657069, -0.34368472, -0.16917975, -0.11308557, 0.0425216 ], | |
| [-0.08851797, 0.2028978 , -0.32375634, 0.4142069 , -0.51772095, | |
| 0.1867378 , -0.09058805, 0.06429149, -0.39393637, -0.33071325], |
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