


from __future__ import annotations

from typing import TypedDict


class 			_a				(     UpperCamelCase__     ):
							_lowercase      :     str
							_lowercase      :     int
def      _a					( SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		if not isinstance(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):
				raise TypeError('''The parameter s type must be str.'''	)

		return [s[i:] + s[:i] for i in range(len(SCREAMING_SNAKE_CASE	)	)]
def      _a					( SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		if not isinstance(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):
				raise TypeError('''The parameter s type must be str.'''	)
		if not s:
				raise ValueError('''The parameter s must not be empty.'''	)

		lowercase__				= all_rotations(SCREAMING_SNAKE_CASE	)
		rotations.sort()  # sort the list of rotations in alphabetically order
		# make a string composed of the last char of each rotation
		lowercase__				= {
		    "bwt_string": "".join([word[-1] for word in rotations]	),
		    "idx_original_string": rotations.index(SCREAMING_SNAKE_CASE	),
		}
		return response
def      _a					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		if not isinstance(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):
				raise TypeError('''The parameter bwt_string type must be str.'''	)
		if not bwt_string:
				raise ValueError('''The parameter bwt_string must not be empty.'''	)
		try:
				lowercase__				= int(SCREAMING_SNAKE_CASE	)
		except ValueError:
				raise TypeError(
				    '''The parameter idx_original_string type must be int or passive'''
				    ''' of cast to int.'''	)
		if idx_original_string < 0:
				raise ValueError('''The parameter idx_original_string must not be lower than 0.'''	)
		if idx_original_string >= len(SCREAMING_SNAKE_CASE	):
				raise ValueError(
				    '''The parameter idx_original_string must be lower than''' ''' len(bwt_string).'''	)

		lowercase__				= [''''''] * len(SCREAMING_SNAKE_CASE	)
		for _ in range(len(SCREAMING_SNAKE_CASE	)	):
				for i in range(len(SCREAMING_SNAKE_CASE	)	):
						lowercase__				= bwt_string[i] + ordered_rotations[i]
				ordered_rotations.sort()
		return ordered_rotations[idx_original_string]


if __name__ == "__main__":
			lowerCAmelCase			=				'Provide a string that I will generate its BWT transform: '
			lowerCAmelCase			=				input(entry_msg).strip()
			lowerCAmelCase			=				bwt_transform(s)
			print(
			    f"""Burrows Wheeler transform for string '{s}' results """
			    f"""in '{result["bwt_string"]}'"""
			)
			lowerCAmelCase			=				reverse_bwt(result['bwt_string'], result['idx_original_string'])
			print(
			    f"""Reversing Burrows Wheeler transform for entry '{result["bwt_string"]}' """
			    f"""we get original string '{original_string}'"""
			)



'''simple docstring'''

import gc
import threading
import time

import psutil
import torch


class     __UpperCAmelCase       :





  def __init__(	self ):
     lowerCAmelCase_			=      psutil.Process()
     lowerCAmelCase_			=      False





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      -1

     while True:
        lowerCAmelCase_			=      max(self.process.memory_info().rss    ,     self.cpu_memory_peak )

        # can't sleep or will not catch the peak right (this comment is here on purpose)
        if not self.peak_monitoring:
           break





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      True
     lowerCAmelCase_			=      threading.Thread(target=self.peak_monitor )
     lowerCAmelCase_			=      True
     self.thread.start()







  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      False
     self.thread.join()
     return self.cpu_memory_peak






A_     :						List[str]    							=PeakCPUMemory()



def snake_case_      (					)			->					Tuple:
   # Time
   lowerCAmelCase_			=      {'''time''': time.time()}

   gc.collect()
   torch.cuda.empty_cache()

   # CPU mem
   lowerCAmelCase_			=      psutil.Process().memory_info().rss
   cpu_peak_tracker.start()

   # GPU mem
   for i in range(torch.cuda.device_count()):
      lowerCAmelCase_			=      torch.cuda.memory_allocated(__snake_case)
   torch.cuda.reset_peak_memory_stats()

   return measures



def snake_case_      (					__snake_case  :							Any)			->					List[str]:
   # Time
   lowerCAmelCase_			=      {'''time''': time.time() - start_measures['''time''']}

   gc.collect()
   torch.cuda.empty_cache()

   # CPU mem
   lowerCAmelCase_			=      (psutil.Process().memory_info().rss - start_measures['''cpu''']) / 2**20
   lowerCAmelCase_			=      (cpu_peak_tracker.stop() - start_measures['''cpu''']) / 2**20

   # GPU mem
   for i in range(torch.cuda.device_count()):
      lowerCAmelCase_			=      (torch.cuda.memory_allocated(__snake_case) - start_measures[str(__snake_case)]) / 2**20
      lowerCAmelCase_			=      (torch.cuda.max_memory_allocated(__snake_case) - start_measures[str(__snake_case)]) / 2**20

   return measures






def snake_case_      (					__snake_case  :							Dict	,   __snake_case  :							Optional[int])			->					Dict:
   print(F'''{description}:''')
   print(F'''- Time: {measures['time']:.2f}s''')
   for i in range(torch.cuda.device_count()):
      print(F'''- GPU {i} allocated: {measures[str(__snake_case)]:.2f}MiB''')
      lowerCAmelCase_			=      measures[F'''{i}-peak''']
      print(F'''- GPU {i} peak: {peak:.2f}MiB''')
   print(F'''- CPU RAM allocated: {measures['cpu']:.2f}MiB''')
   print(F'''- CPU RAM peak: {measures['cpu-peak']:.2f}MiB''')





