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import numpy as np
from numpy.polynomial import Polynomial

def polynomial_modulo(polynomial, mod):
    """
    Perform polynomial modulo operation using divmod.
    """
    q, r = divmod(polynomial, mod)
    return r

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// ==UserScript==
// @name         Google Docs Side Panel Hide
// @namespace    http://tampermonkey.net/
// @version      2024-04-21
// @description  Hide the Google Docs Side Panel (Calendar, Keep, Maps, etc.) toggle button for a clean slate.
// @author       Bastiaan Quast
// @match        https://docs.google.com/document/d/*
// @icon         none
// @grant        GM_addStyle
// ==/UserScript==

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gelu <- function(x) {
  return(0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3))))
}

softmax <- function(x) {
  exp_x <- exp(x - apply(x, 1, max))
  return(exp_x / rowSums(exp_x))
}

layer_norm <- function(x, g, b, eps = 1e-5) {

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import math
import numpy as np
import statsmodels.api as sm
from statsmodels.base.model import GenericLikelihoodModel
from scipy.stats import poisson
from scipy.stats import binom
from patsy import dmatrices
import statsmodels.graphics.tsaplots as tsa
from matplotlib import pyplot as plt

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## ----setup----
library(polynom)
library(HEtools)

## ----params----
d  =   4
n  =   2^d
p  =   (n/2)-1
t  =   p
q  = 868

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import numpy as np
from numpy.polynomial import Polynomial

def polynomial_modulo(polynomial, mod):
    q, r = divmod(polynomial, mod)
    return r

def mod_on_coefficients(polynomial, modulo):
    coefs = polynomial.coef
    mod_coefs = [c % modulo for c in coefs]

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const { Readability } = require('@mozilla/readability');
const jsdom = require('jsdom');
const fs = require('fs');
const path = require('path');
const os = require('os');
const fetch = (...args) => import('node-fetch').then(({default: fetch}) => fetch(...args));

// Helper to download an image and return the local filename
async function downloadImage(imgUrl, folder, idx) {
  try {

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import Foundation
import AVFoundation
import Vision
import CoreImage

class CameraCapture: NSObject, AVCaptureVideoDataOutputSampleBufferDelegate {
    var foundQR: String?
    let qrQueue = DispatchQueue(label: "qrqueue")

    func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {

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import numpy as np
from numpy.polynomial import Polynomial

# Set the parameters
M = 8
N = M // 2
scale = 64
xi = np.exp(2 * np.pi * 1j / M)

def vandermonde(xi: np.complex128, M: int) -> np.array:

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## ----setup----
library(polynom)
library(HomomorphicEncryption)

## ----seed-----
set.seed(123)

## ----params-----
M     <-   8
N     <-   M / 2