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import torch
import torch.nn as nn
import math
from torch import Tensor
from torch.nn import functional as F
from dataclasses import dataclass
from typing import Optional, Literal


def count_parameters(model: nn.Module) -> int:

viig99

#!/usr/bin/env bash

# ---------------------------------------------
# This has been updated to work with Fedora 35
# ---------------------------------------------

# Run a System Update
sudo dnf update

# Enable RPM Fusion

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/*
  Author: Arjun Variar
  Date: 23rd Oct 2012
  kMeans Clustering algorithm implemented from javascript as per the logic from Andrew Ng's ML class.
  Implementation is for node.js, should work on the browser too.
  Dependencies:
    Javascript Sylvester library is used for matrix operations.
  Notes:
    Added feature scaling to the algorithm as an optional thing to do, somehow it doesnt fit well this data.
*/

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var text = "FourscoreandsevenyearsagoourfaathersbroughtforthonthiscontainentanewnationconceivedinzLibertyanddedicatedtothepropositionthatallmenarecreatedequalNowweareengagedinagreahtcivilwartestingwhetherthatnaptionoranynartionsoconceivedandsodedicatedcanlongendureWeareqmetonagreatbattlefiemldoftzhatwarWehavecometodedicpateaportionofthatfieldasafinalrestingplaceforthosewhoheregavetheirlivesthatthatnationmightliveItisaltogetherfangandproperthatweshoulddothisButinalargersensewecannotdedicatewecannotconsecratewecannothallowthisgroundThebravelmenlivinganddeadwhostruggledherehaveconsecrateditfaraboveourpoorponwertoaddordetractTgheworldadswfilllittlenotlenorlongrememberwhatwesayherebutitcanneverforgetwhattheydidhereItisforusthelivingrathertobededicatedheretotheulnfinishedworkwhichtheywhofoughtherehavethusfarsonoblyadvancedItisratherforustobeherededicatedtothegreattdafskremainingbeforeusthatfromthesehonoreddeadwetakeincreaseddevotiontothatcauseforwhichtheygavethelastpfullmeasureofdevotionthatweherehighlyresolvethatt

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function FIB(n) {
	phi = (1 + Math.sqrt(5))/2
	eta = (1-phi)
	return (Math.pow(phi,n) - Math.pow(eta,n)) / Math.sqrt(5)
}

var j = 0

for (var i = 5;i < 500;i++) {

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var arr = [3, 4, 9, 14, 15, 19, 28, 37, 47, 50, 54, 56, 59, 61, 70, 73, 78, 81, 92, 95, 97, 99]
//var arr = [1,2,3,4,6]
function powerset(ary) {
    var ps = [[]];
    for (var i=0; i < ary.length; i++) {
        for (var j = 0, len = ps.length; j < len; j++) {
            ps.push(ps[j].concat(ary[i]));
        }
    }
    return ps;

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# Author - Arjun Variar
# Thanks to Ben for introducing me to fiftyfootshadows, Awesome Wallpapers!!
#!/bin/sh

if [[ -z "$TMP" ]]
then
   TMP="/private/tmp"
fi

dir="$HOME/fifty_downloads"

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/* This Function determines the direction of your displacement based upon the width and height of the widget / viewport width height you are scrolling them.
 The theta is calculated based upon the width and height of the widget, and sets the direction based upon the 4 quadrants which are formed due to the intersection of lines drawn from the vertices and the point on origin on the center of the widget.
 This Leads to a cleaner user experience for scrolling, as this works smoothly for small or large widgets.

 @Arjun Variar
*/


function returnDirectionOfScroll(deltaX,deltaY,width,height) {
	var angle = Math.atan2(-deltaY,-deltaX).toDeg();