simonjisu

# Python
import json
import requests

class Parser(object):
    def __init__(self, token: str, base_url: str, verbose=0):
                
        if base_url[-1] == '/':
            base_url = base_url[:-1]
        self.base_url = base_url

simonjisu

<!-- Author: https://github.com/simonjisu
Change `div.article-content` to your article container in jekyll blog
Put your file into `_include/text-expand.html`
-->
<script>
var elements = document.querySelectorAll('div.article-content')[0].childNodes; // 수정1 
var addContent = false;
var contentsToAdd = [];
var expandtags = null;
var detailText = null;

simonjisu

# References:
# ==============
# WebLogo-2M Dataset
#   http://www.eecs.qmul.ac.uk/~hs308/WebLogo-2M.html/
#   Hang Su, Xiatian Zhu, Shaogang Gong.
#   Deep Learning Logo Detection with Data Expansion by Synthesising Context
#   IEEE Winter Conference on Applications of Computer Science (WACV), Santa Rosa, USA, March 2017.
# 
#   Hang Su, Shaogang Gong, Xiatian Zhu.
#   WebLogo-2M: Scalable Logo Detection by Deep Learning from the Web

simonjisu

import numpy as np
import matplotlib.pyplot as plt

def g(y):
    """x = g(y)"""
    return np.log(y) - np.log(1-y) + 5

def g_inv(x):
    """y = g^{-1}(x)"""
    return 1 / (1 + np.exp(-x + 5))

simonjisu

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
# Embedding dim: E = 12
# Batch size: B = 2
# Tokens: T = 6
# Hidden Size: H = 20
# Vocab Size: V = 10
E, B, T, H, V = (12, 1, 6, 20, 10)

simonjisu

wget https://www.python.org/ftp/python/3.6.5/Python-3.6.5.tar.xz
tar xf Python-3.6.5.tar.xz
cd Python-3.6.5
./configure && make && make install

simonjisu

#!/bin/bash

git clone https://github.com/simonjisu/autoupdate.git
python autoupdate/src/main.py \
    --opt "new_init" \
    -bp "." \
    -dp "/usr/bin" \
    -ms 1000 \
    -sv \
    -em $1 \