jovianlin

from keras.models import Model
from keras.layers import Input, Dense
 
input_1 = Input(..., name='input_1')
x = Dense(...)(input_1)
x = Dense(...)(x)
...
output_1 = Dense(dim_output_1, ..., name='output_1')
 
input_2 = Input(..., name='input_2')

jovianlin

===== BLOG HEADER =====

<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/highlight.js/9.9.0/styles/agate.min.css">
<script src="//cdnjs.cloudflare.com/ajax/libs/highlight.js/9.9.0/highlight.min.js"></script>
<style>
    .inner { max-width:50em; }
    pre .lines { margin-top:-12px; }
</style>

jovianlin

n = int(input())
L = list(map(int, input().strip().split()))

X = [0] * n
count = 0
for i, x in enumerate(L):
    start = (i+1)%n # OK to START collection at the pos after the "i"
    end = (start - x + n)%n # WORST place to start the collection
    X[start] += 1
    X[end] -= 1

jovianlin

# Use TQDM if installed
tqdm_installed = False
try:
    from tqdm import tqdm
    tqdm_installed = True
except:
    pass

jovianlin

##############################
# Tell ``ls`` to be colorful #
##############################
export CLICOLOR=1
COLOR_BOLD="\[\e[1m\]"
COLOR_DEFAULT="\[\e[0m\]"
#PS1='\[\033[32m\]\u@\h\[\033[00m\]:\[\033[34m\]\w\[\033[31m\]$\[\033[00m\]'
#PS1='\[\033[32m\]\u@\h\[\033[00m\]:\[\033[34m\]\w\[\033[31m\]$\[\033[00m\]'
PS1="\[\033[32m\]\u\[\033[31m\]:\[\033[34m\]\w⚡ \[\033[00m\] "

jovianlin

###########################
# ~/.tmux.conf for iTerm2 #
#                         #
# by Jovian Lin           #
###########################

##########
# Basics #
##########

jovianlin

from __future__ import print_function
import sys

if sys.version_info[0] >= 3:
  from urllib.request import urlretrieve
else:
  from urllib import urlretrieve

local_filename, headers = urlretrieve('http://jovianlin.com')
html = open(local_filename)

jovianlin

import random, sys, time
from termcolor import colored
       
colors = ['grey', 'red', 'green', 'yellow', 'blue', 'magenta', 'cyan', None]
generated = ''
sys.stdout.write(generated)

for i in range(100):
    sys.stdout.write(colored('%02d ' % i, random.choice(colors)))
    sys.stdout.flush()

jovianlin

import sys

def is_kernel():
    """
    Determine if we're in an IPython notebook session
    Source: Source: http://stackoverflow.com/a/34092072
    -------------------------------------------------
    You can't detect that the frontend is a notebook with perfect precision, 
    because an IPython Kernel can have one or more different Jupyter frontends 
    with different capabilities (terminal console, qtconsole, notebook, etc.). 

jovianlin

from pyspark import SparkContext
from pyspark.sql import HiveContext
from graphframes.examples import Graphs

sc = SparkContext()
sc.setLogLevel("ERROR")
sqlContext = HiveContext(sc)


g = Graphs(sqlContext).friends()  # Get example graph