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Jaemin Cho j-min

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j-min / tokenize_dparser.py
Last active December 3, 2016 09:02
Get tokenized list from dparser
import json
import requests
def tokenize_dparser(text):
dparser_link = 'http://parser.datanada.com/parse?version=1&string='
url = dparser_link+text
response = requests.get(url)
@j-min
j-min / hangul.py
Created December 20, 2016 04:07 — forked from allieus/hangul.py
# -*- coding: utf-8 -*-
class Hangul:
BASE_CODE = 44032
CHOSUNG = 588
JUNGSUNG = 28
# 초성 리스트. 00 ~ 18
CHOSUNG_LIST = [
'ㄱ', 'ㄲ', 'ㄴ', 'ㄷ', 'ㄸ', 'ㄹ', 'ㅁ', 'ㅂ', 'ㅃ',
@j-min
j-min / convertSize.py
Created January 6, 2017 16:14
convertSize.py
import math
def convertSize(size):
"""
Return filesize (in Bytes) in human-readable format
"""
if (size == 0):
return '0B'
units = ("B", "KB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB")
i = int(math.floor(math.log(size,1024)))
@j-min
j-min / .zshrc
Created February 9, 2017 14:35
ZSH=$HOME/.zsh
HISTFILE=$HOME/.history
HISTSIZE=10000
SAVEHIST=10000
export TERM=xterm-256color
export LANG=en_US.UTF-8
# added by Anaconda3 4.1.1 installer
export PATH=$HOME/anaconda3/bin:$PATH
@j-min
j-min / matplotlib_plot_demo.py
Created June 25, 2017 10:58
matplotlib configuration
import matplotlib
# font configuration
matplotlib.rc('font', family='NanumGothic', size=22)
@j-min
j-min / TF_MDN.ipynb
Created November 15, 2016 10:46
Mixture Density Network in TensorFlow
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@j-min
j-min / tensorboard_inline.py
Created May 16, 2017 04:16
tensorboard inline
from IPython.display import clear_output, Image, display, HTML
import numpy as np
def strip_consts(graph_def, max_const_size=32):
"""Strip large constant values from graph_def."""
strip_def = tf.GraphDef()
for n0 in graph_def.node:
n = strip_def.node.add()
n.MergeFrom(n0)
if n.op == 'Const':
@j-min
j-min / exp_lr_scheduler.py
Created June 25, 2017 14:07
learning rate decay in pytorch
# http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
def exp_lr_scheduler(optimizer, epoch, init_lr=0.001, lr_decay_epoch=7):
"""Decay learning rate by a factor of 0.1 every lr_decay_epoch epochs."""
lr = init_lr * (0.1**(epoch // lr_decay_epoch))
if epoch % lr_decay_epoch == 0:
print('LR is set to {}'.format(lr))
for param_group in optimizer.param_groups:
@j-min
j-min / backprop.ipynb
Created March 1, 2017 14:25
Simple backprop implementation in TensorFlow without its optimizer API
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@j-min
j-min / RNN_hunkim's_tutorial_BasicRNNCell.ipynb
Last active December 11, 2018 02:06
TensorFlow 0.9 implementation of BasicRNNCell based on hunkim's tutorial
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