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{
  "message": "healthy",
  "label": "ping",
  "color": "green"
}

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import os
[
    (
        fp := os.path.join('data', fn), 
        ff := open(fp), 
        text := ff.read(),
        [
            (
                line := ln.strip(),
                line := '"{}"'.format(line)

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https://www.zdnet.com/sitemap/
https://gizmodo.com/sitemap.xml
https://betanews.com/sitemap.xml
https://www.wired.com/sitemap.xml
https://lifehacker.com/sitemap.xml
https://arstechnica.com/sitemap.xml
https://www.pcworld.com/sitemap.xml
https://www.engadget.com/sitemap.xml
https://www.geekwire.com/sitemap.xml
https://www.techradar.com/sitemap.xml

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# Researches a topic on the internet and collects content required for video generation.

from enum import Enum
from selenium import webdriver


# from selenium.webdriver.common.keys import Keys

# Trailer Compiler Template

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* {
  margin: 0;
  padding: 0;
  font-family: 'Open Sans', sans-serif;
}

.padded {
  padding: 20px
}

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#!/bin/bash
# Usage bash gdrive-download.sh <file_id> <file_name>
fileid="$1"
filename="$2"
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename}
rm cookie

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#!/bin/bash
fileid="$1"
filename="$2"
curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null
curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename}
rm cookie

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# Implements GAN
from itertools import chain

import torch
from torch.optim import *
from torch.autograd import *
from torch.nn.modules import *
import torchvision.transforms as T
from torchvision.datasets import MNIST
from torch.utils.data import DataLoader

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# Pure TF implm.
# Fibonacci series using tensorflow
import tensorflow as tf
import numpy as np
import time

def build_graph2(max_count):
	init = np.zeros([max_count], dtype=int)
	m0 = tf.Variable(init,dtype=tf.int32)
	i0 = tf.constant(2)

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# This script converts msra ground truth format to east training format
# Download and extract MSRA, cd <MSRA_DIR>, mkdir out and run this script
# https://github.com/argman/EAST

import os
import math
import shutil
import numpy as np

rotate = lambda xy, theta: [xy[0] * math.cos(theta) - xy[1] * math.sin(theta),xy[0] * math.sin(theta) + xy[1] * math.cos(theta)]