djinn

#include <iostream>
#include <vector>
#include <random>
#include <algorithm>
#include <numeric>
#include <thread>
#include <mutex>

const int num_simulations = 10000; // Number of Monte Carlo simulations
const int num_days = 252;          // Number of trading days in a year

djinn

import numpy as np
import math

# Define the Transformer model architecture
class Transformer:
    def __init__(self, input_vocab_size, output_vocab_size, max_seq_length, d_model, num_heads, num_layers):
        self.input_vocab_size = input_vocab_size
        self.output_vocab_size = output_vocab_size
        self.max_seq_length = max_seq_length
        self.d_model = d_model

djinn

#!/bin/sh
# The cheapest CUDA instance on AWS is Graviton2 based g5g instances
# 1) Install right CUDA Drivers on the system. Whilst this script has been tested on Ubuntu 22.04. It should work on others
# 2) Install torch with GPU support. Compiling from source works the best 
# 3) Preferably Quantize the models - https://huggingface.co/docs/transformers/main/en/main_classes/quantization
#
# Author: Supreet Sethi <supreet.sethi@gmail.com>
# Web: https://www.linkedin.com/in/djinn
# 
# Step 1) is here 

djinn

#!/usr/bin/env python3
from json import dumps

test_load = """SQL statistics:
    queries performed:
        read:                            845684
        write:                           241589
        other:                           120831
        total:                           1208104
    transactions:                        60398  (1506.89 per sec.)

djinn

#!/bin/sh
# Author Supreet Sethi <supreet.sethi@gmail.com>
# Dated Thu Jul 21 13:26:06 +08 2022
# Instructions - wget <script>; chmod +x yubikey.sh; ./yubikey.sh

sudo pmset -a hibernatemode 25 && sudo pmset -a standbydelay 15
echo "Yubikey hibernation changes installed"

djinn

#include <iostream>
#include <string>
#include <cinttypes> // for uint32_t 
#include <cfenv>
#include <cmath>



std::string float_to_binary(float f) {
	union {float f; uint32_t i;} u;

djinn

#!/usr/bin/env python3
# Copyright(C) 2020 Supreet Sethi <supreet.sethi@gmail.com>
# I do Hindi, Punjabi and Urdu in Python dude!

बोल = print
बोल("ਬੋਲ ਕੇ ਲਾਬ ਆਜ਼ਾਦ ਹੈਂ ਤੇਰੇ - فیض احمد فیض")

djinn

#!/usr/bin/env python3
# Author: Supreet Sethi <supreet.sethi@gmail.com>
# Dated: 16/10/2020
# Please use it has working prototype
# Lot can be done from process management and general housekeeping perspective



from multiprocessing import Pool, cpu_count, Manager
from collections import namedtuple

djinn

import pandas, boto3 
from sklearn.utils import shuffle
ratings = pandas.read_csv('ratings.csv')
ratings = shuffle(ratings)
ratings = ratings[ratings['rating']>3.6]
ratings = ratings.drop(columns='rating')
ratings.columns = ['USER_ID','ITEM_ID','TIMESTAMP']
ratings = ratings[:100000]
ratings.to_csv('ratings.processed.csv',index=False)
s3 = boto3.client('s3')

djinn

#!/usr/bin/env python3
from requests import get
from shutil import copyfileobj
from tempfile import NamedTemporaryFile as TemporaryFile
import time
from os import sendfile
import hashlib
import os.path

WIKIDUMPURL = 'https://dumps.wikimedia.org/enwikinews/20200701/enwikinews-20200701-pages-articles-multistream.xml.bz2'