jenyeeiam

function uniqueSum(arr) {
  if(!arr || arr.length === 0){
    return 0
  }
  
  const stringArr = arr.map(function(num) {
      return num.toString();
  })

  let runningSum = 0;

jenyeeiam

# -*- coding: utf-8 -*-
"""matchy_matchy.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1CCjJxeSXELh08NWzuKw4WDX8Aun8gMiy
"""

from google.colab import files

jenyeeiam

import torch
import pandas as pd
from multi_label_class import MultiTaskBertModel  # Import the model class
from transformers import AutoTokenizer


def load_model(model_path, device):
    model = MultiTaskBertModel.from_pretrained("bert-base-cased")
    model.load_state_dict(torch.load(model_path, map_location=device))
    model.to(device)

jenyeeiam

import csv
import json

# Define the input and output file names
input_csv_file = 'connection_data.csv'
output_json_file = 'connection_data.json'

# Function to preprocess text according to the specified rules
def preprocess_text(text):
    # Replace internal double quotes with two double quotes

jenyeeiam

function ArrayQueue(capacity) {
  this.capacity = capacity;
  this.start = 0;
  this.end = 0;
  this.length = 0;
  this.a = new Array(capacity);

  this.add = function(num) {
    if(this.length == this.a.length) {
      console.log('MAX CAPACITY');

jenyeeiam

from xml.etree import ElementTree
from xml import etree

#in order to test it you have to create testing.xml file in the folder with the script
xmlParsedWithET = ElementTree.parse("testing.xml")
root = xmlParsedWithET.getroot()

def CDATA(text=None):
    element = ElementTree.Element('![CDATA[')
    element.text = text

jenyeeiam

import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.patches as mpatches # needed for waffle Charts
from wordcloud import WordCloud, STOPWORDS
from PIL import Image
import seaborn as sns
import pdb
import sys

jenyeeiam

# frozen_string_literal: true

source "https://rubygems.org"

git_source(:github) {|repo_name| "https://github.com/#{repo_name}" }

# gem "rails"
gem 'kimurai'
gem 'nokogiri'
gem 'mechanize'

jenyeeiam

import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.patches as mpatches # needed for waffle Charts
from wordcloud import WordCloud, STOPWORDS
from PIL import Image
import seaborn as sns
import pdb
from stats_reader import NCAA_DATA_FRAME as df

jenyeeiam

require 'httparty'
require 'mechanize'
require 'Nokogiri'
require 'csv'
require 'pry'

inputs = ARGV
if !inputs then
  raise "Input a year from 2018 to 2002"
end