urigoren

import numpy as np
from scipy.sparse import linalg, eye, csr_matrix
from sklearn.preprocessing import normalize
from sklearn.metrics.pairwise import pairwise_distances
from collections import defaultdict



class MarkovClustering:
    def __init__(self, matrix, metric="cosine", bias=1):

urigoren

from PIL import Image
from pathlib import Path
from pillow_heif import register_heif_opener
from tqdm import tqdm
from argparse import ArgumentParser
register_heif_opener()

def main(params):
    print("Converting HEIC files to JPG")
    files = list(Path(".").glob("*.heic")) + list(Path(".").glob("*.HEIC"))

urigoren

import openai
from decouple import config
openai.api_key =  config("OPENAI_KEY")

YES_TOKEN = frozenset([5297, 3763, 3363, 8505, 3363, 3763, 43335, 3763, 21560])
NO_TOKEN = frozenset([2949, 645, 1400, 3919, 1400, 645, 15285, 645, 8005])

def yes_or_no(txt: str)->bool:
    response = openai.Completion.create(
    model="text-davinci-003",

urigoren

from keras.layers import Dense, Dropout, LSTM, Embedding
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
import pandas as pd
import numpy as np

input_file = 'input.csv'

def load_data(test_split = 0.2):
    print ('Loading data...')

urigoren

urigoren

wsl --shutdown
diskpart
# open window Diskpart
select vdisk file="C:\Users\ugore\AppData\Local\Packages\CanonicalGroupLimited.Ubuntu20.04onWindows_79rhkp1fndgsc\LocalState\ext4.vhdx"
attach vdisk readonly
compact vdisk
detach vdisk
exit

urigoren

hadoop fs -text $1>hvim.txt
vim hvim.txt
hadoop fs -rm -skipTrash $1
hadoop fs -copyFromLocal hvim.txt $1
rm hvim.txt
hadoop fs -chmod 777 $1

urigoren

import sys, random, json
from gensim.models import Word2Vec
from argparse import ArgumentParser
from collections import Counter
from pathlib import Path

__dir__= Path(__file__).absolute().parent


class DirSentences(object):

urigoren

from collections import defaultdict
from itertools import product
from scipy import sparse
from sklearn.base import TransformerMixin

class InteractionBySplit(TransformerMixin):
  """
  Takes a sparse matrix as input, and an index to split by, and returns all possible interactions before and after that index.
  """
  def __init__(self, split_index,*args,**kwargs):

urigoren

<?php
define('SLACK_WEBHOOK', 'https://hooks.slack.com/services/xxx/yyy/zzz');
define('TELEGRAM_BOT_TOKEN', '...');
define('TELEGRAM_CHAT_ID', '12345');

function slack($txt) {
  $msg = array('text' => $txt);
  $c = curl_init(SLACK_WEBHOOK);
  curl_setopt($c, CURLOPT_RETURNTRANSFER, true);
  curl_setopt($c, CURLOPT_SSL_VERIFYPEER, false);