sh -c "$(curl -fsSL https://raw.githubusercontent.com/robbyrussell/oh-my-zsh/master/tools/install.sh)"
- Download zsh-autosuggestions by
var mediaJSON = { "categories" : [ { "name" : "Movies", | |
"videos" : [ | |
{ "description" : "Big Buck Bunny tells the story of a giant rabbit with a heart bigger than himself. When one sunny day three rodents rudely harass him, something snaps... and the rabbit ain't no bunny anymore! In the typical cartoon tradition he prepares the nasty rodents a comical revenge.\n\nLicensed under the Creative Commons Attribution license\nhttp://www.bigbuckbunny.org", | |
"sources" : [ "http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/BigBuckBunny.mp4" ], | |
"subtitle" : "By Blender Foundation", | |
"thumb" : "images/BigBuckBunny.jpg", | |
"title" : "Big Buck Bunny" | |
}, | |
{ "description" : "The first Blender Open Movie from 2006", | |
"sources" : [ "http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/ElephantsDream.mp4" ], |
CREATE TABLE testing_partition(patent_id BIGINT, date DATE) WITH ( OIDS=FALSE); | |
CREATE OR REPLACE FUNCTION create_partition_and_insert() RETURNS trigger AS | |
$BODY$ | |
DECLARE | |
partition_date TEXT; | |
partition TEXT; | |
BEGIN | |
partition_date := to_char(NEW.date,'YYYY_MM_DD'); | |
partition := TG_TABLE_NAME || '_' || partition_date; |
public class TestActivity extends AppCompatActivity { | |
@Override | |
protected void onCreate(@Nullable Bundle savedInstanceState) { | |
super.onCreate(savedInstanceState); | |
setContentView(R.layout.test_activity); | |
RecyclerView recycler = (RecyclerView) findViewById(R.id.recycler); | |
recycler.setLayoutManager(new LinearLayoutManager(this)); | |
Next.js, Nginx with Reverse proxy, SSL certificate
service: service-name | |
provider: | |
name: aws | |
runtime: nodejs6.10 | |
functions: | |
myfunc: | |
handler: handler.myfunc |
package main | |
import ( | |
"fmt" | |
"io" | |
"net/http" | |
"os" | |
) | |
func main() { |
"""TensorFlow 2.0 implementation of vanilla Autoencoder.""" | |
import numpy as np | |
import tensorflow as tf | |
__author__ = "Abien Fred Agarap" | |
np.random.seed(1) | |
tf.random.set_seed(1) | |
batch_size = 128 | |
epochs = 10 |