Siladittya Manna sadimanna

How to fix a USB drive showing up as two drives (fragmented into multiple partitions) on Windows:

Hold the Windows key and press X, select PowerShell (Admin), select Yes to the pop-up. You can also use Command Prompt.
In the Powershell interface type diskpart to enter the disk partition tool.
Type list disk to see all disks listed.
Select the USB drive by typing select disk [NUMBER]. Be careful to select the correct drive.
Type clean. An error will occur if you have the drive folder open, close the window and repeat the command if this happens.
Type create partition primary.
Type format fs=ntfs quick to format the drive (you can also choose to set fs=fat32).
Type active.

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	#!/bin/bash

	### steps ####
	# verify the system has a cuda-capable gpu
	# download and install the nvidia cuda toolkit and cudnn
	# setup environmental variables
	# verify the installation
	###

	### to verify your gpu is cuda enable check

	// Dowloaded from: http://download.shredderchess.com/div/uci.zip

	Description of the universal chess interface (UCI) April 2006
	=================================================================

	* The specification is independent of the operating system. For Windows,
	the engine is a normal exe file, either a console or "real" windows application.

	* all communication is done via standard input and output with text commands,

	'''
	"Contrast Limited Adaptive Histogram Equalization"
	by Karel Zuiderveld, karel@cv.ruu.nl
	in "Graphics Gems IV", Academic Press, 1994

	_Author_ -- Siladittya Manna

	The below implementation does not assume that the
	X- and Y image resolutions are an integer multiple
	of the X- and Y sizes of the contextual regions.

	# Info on how to get your api key (kaggle.json) here: https://github.com/Kaggle/kaggle-api#api-credentials
	!pip install kaggle
	api_token = {"username":"USERNAME","key":"API_KEY"}
	import json
	import zipfile
	import os
	with open('/content/.kaggle/kaggle.json', 'w') as file:
	json.dump(api_token, file)
	!chmod 600 /content/.kaggle/kaggle.json
	!kaggle config path -p /content

	#!/usr/bin/env python3
	# -- coding: utf-8 --
	"""Building an LSTM from scratch with Keras (if that's not a contradiction)"""

	from keras import backend as K
	from keras.engine.topology import Layer
	import numpy as np
	from keras.layers import RNN, Dense, Activation,LSTM
	from keras.models import Model
	import keras

	/*
	* ANSI C code from the article
	* "Contrast Limited Adaptive Histogram Equalization"
	* by Karel Zuiderveld, karel@cv.ruu.nl
	* in "Graphics Gems IV", Academic Press, 1994
	*
	*
	* These functions implement Contrast Limited Adaptive Histogram Equalization.
	* The main routine (CLAHE) expects an input image that is stored contiguously in
	* memory; the CLAHE output image overwrites the original input image and has the