vietvudanh

package main

import (
	"fmt"
	"sync"
	"time"
)

const concurrency = 3
const numTasks = 100

vietvudanh

vietvudanh

// This can be imported via ./bin/gremlin.sh -i describe.groovy
// A variable 'graph' must be defined with a JanusGraph graph
// Run it as a plugin command ':schema'
// :schema describe
// 

import org.janusgraph.graphdb.database.management.MgmtLogType
import org.codehaus.groovy.tools.shell.Groovysh
import org.codehaus.groovy.tools.shell.CommandSupport

vietvudanh

Here is a list of scopes to use in Sublime Text 2/3 snippets -

ActionScript: source.actionscript.2
AppleScript: source.applescript
ASP: source.asp
Batch FIle: source.dosbatch
C#: source.cs
C++: source.c++
Clojure: source.clojure

vietvudanh

# the following two lines give a two-line status, with the current window highlighted
hardstatus alwayslastline
hardstatus string '%{= kG}[%{G}%H%? %1`%?%{g}][%= %{= kw}%-w%{+b yk} %n*%t%?(%u)%? %{-}%+w %=%{g}][%{B}%m/%d %{W}%C%A%{g}]'

# huge scrollback buffer
defscrollback 5000

# no welcome message
startup_message off

vietvudanh

# settings.py
EMAIL_BACKEND = 'backends.SMTPEmailBackend'

# backends.py
"""Custom SMTP email backend class"""
import smtplib
from django.core.mail.utils import DNS_NAME
from django.core.mail.backends.smtp import EmailBackend

class SMTPEmailBackend(EmailBackend):

vietvudanh

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

vietvudanh

Here is a list of scopes to use in Sublime Text 2 snippets - 

ActionScript: source.actionscript.2
AppleScript: source.applescript
ASP: source.asp
Batch FIle: source.dosbatch
C#: source.cs
C++: source.c++
Clojure: source.clojure
CoffeeScript: source.coffee