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'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
' SAMPLE: Encryption and decryption using DPAPI functions.
'
' To run this sample, create a new Visual Basic.NET project using the Console
' Application template and replace the contents of the Module1.vb file with
' the code below.
'
' Go to the folder %APPDATA%\Subversion\auth\svn.simple
' Copy the Encrypted Value of the password denoted by the line below 2 lines below the line saying password
' Compile the code and put this value in a new file called InputFile.txt and in the same location where you are executing the code.

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import functools

import pandas as pd
import torch
import transformers
from accelerate import Accelerator
from datasets import Dataset
from torch.utils.data import DataLoader
from tqdm.auto import tqdm

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from flask import Flask, jsonify, request, render_template

from queued_map import example_items
  
app = Flask(__name__)

@app.get("/")
@app.get("/<int:n>")
def home(n: int=10):
    output = example_items(n)

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import asyncio

def async_decorator(acreate_fn):
    async def _f(*args, **kwargs):
        print(f"Decorated fn: {args=}, {kwargs=}. Sleeping.")
        await asyncio.sleep(0.1)
        return await acreate_fn(*args, **kwargs)
    return _f

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from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from scipy import sparse

from joblib import dump, load
import joblib
import time

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mkdir food.com
cd food.com
wget https://www.food.com/sitemap.xml
for url in $(cat sitemap.xml | grep "<loc>https://www.food.com/sitemap-" | sed -n 's:.*<loc>\(.*\)</loc>.*:\1:p');
do echo "Download: $url"; 
done

for url in $(cat sitemap.xml | grep "<loc>https://www.food.com/sitemap-" | sed -n 's:.*<loc>\(.*\)</loc>.*:\1:p');
do wget "$url"; 
done

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/**
 * progress.c - Progress bar and progress percentage in C. 
 * This program uses ANSI escape codes to show an always updating progress line in the terminal. 
 * Author: Shubhanshu Mishra 
**/

#include <stdio.h>
#include <string.h>
#include <stdlib.h>

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from pathlib import Path

import torch
from transformers import CLIPProcessor, CLIPTextModelWithProjection
from accelerate import Accelerator
from datasets import Dataset

import pandas as pd
import numpy as np

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"""
pip install pypdf
"""

from pypdf import PdfWriter

def main(args):
  merger = PdfWriter()
  file_paths = args.input_files
  for pdf in file_paths: