From this gist ... I'm trying to link to the inline anchor.
As this comment says, all has to be in lower case, and no space between #
and the first character.
:set nopaste "Fixes weird indentation when pasting" | |
"Didn't know 'paste' mode exists. do `:set paste` manually" | |
"when you have to paste and back to `:set nopaste` after you are done" | |
"Else, the 'paste' mode, bottom reading `--INSERT (paste)--` will ignore other settings here" | |
"Refer to `:help paste`" | |
:set tabstop=4 "Default is 8 and is too much for me" | |
:set expandtab "I prefer space" | |
:set shiftwidth=4 "Set to 4 spaces for indenting with `Shift + >>` in view mode" | |
:set autoindent "The above doesn't 'autoindent'" | |
:set splitright "Why the hell the default would open the new file on the LEFT???" |
function LogFile(path) { | |
this.file = File(path) | |
} | |
LogFile.prototype.write = function(line) { | |
this.file.open('a'); | |
this.file.write(line + "\n"); | |
this.file.close() | |
} |
<!DOCTYPE html> | |
<html> | |
<head> | |
<title></title> | |
</head> | |
<script type="text/javascript"> | |
function lazyLoad() { | |
var w = window; | |
var lazy = function(){ | |
var imgs = document.querySelectorAll('[lazy]'); |
<!DOCTYPE html> | |
<html> | |
<head> | |
<title></title> | |
</head> | |
<body> | |
<!-- LAZY LOAD --> | |
<img onerror=" | |
var w = window; | |
var lazy = function(){ |
<!DOCTYPE html> | |
<html> | |
<head> | |
<title></title> | |
</head> | |
<body> | |
<!-- LAZY LOAD --> | |
<img onerror=" | |
var w = window; | |
var lazy = function(){ |
import json, sys | |
from functools import reduce | |
inputfilename = sys.argv[1] | |
outputfilename = sys.argv[2] | |
file = open(inputfilename, mode='r', encoding='utf-8') | |
raw = file.read() | |
file.close() | |
raw_json = json.loads(raw) |
# I needed this for my own AfterEffects Script. | |
// Use absolute path for the JSON file. | |
path = '/d/path/to/your/json/file.json' | |
// Get file object | |
file = File(path); | |
// open it before reading. | |
file.open('r'); |
video = tf.keras.layers.Input(shape=(None, 150, 150, 3)) | |
cnn = tf.keras.applications.InceptionV3( | |
weights='imagenet', | |
include_top = False, | |
pool='avg') | |
cnn.trainable = False | |
encoded_frames = tf.keras.layers.TimeDistributed(cnn)(video) | |
encoded_vid = tf.layers.LSTM(256)(encoded_frames) | |
question = tf.keras.layers.Input(shape=(100), dtype='int32') |