




'''simple docstring'''





UpperCamelCase_		:    Dict									=		[0.3_3, 0.4_4, 0.5_5, 0.4_4, 0.3_3]
UpperCamelCase_		:    List[str]									=		3
UpperCamelCase_		:    Dict									=		5

# Buffer Space (with Parameters Space)
UpperCamelCase_		:    list[float]									=		[]
UpperCamelCase_		:    list[float]									=		[]

# Machine Time
UpperCamelCase_		:    Optional[Any]									=		0





def 			__a			(     _UpperCamelCase:					int					)		->				List[Any]:

     """simple docstring"""




     global buffer_space, params_space, machine_time, K, m, t

     # Choosing Dynamical Systems (All)
     for key, value in enumerate(_UpperCamelCase					):
          # Evolution Parameter
          _snake_case							=   float(seed / value					)

          # Control Theory: Orbit Change
          _snake_case							=   (buffer_space[(key + 1) % m] + e) % 1

          # Control Theory: Trajectory Change
          _snake_case							=   (params_space[key] + e) % 1 + 3

          # Modification (Transition Function) - Jumps
          _snake_case							=   round(float(r * value * (1 - value)					)      ,		10					)
          _snake_case							=   r  # Saving to Parameters Space

     # Logistic Map
     assert max(_UpperCamelCase					) < 1
     assert max(_UpperCamelCase					) < 4

     # Machine Time
     machine_time += 1





def 			__a			(     )		->				int:

     """simple docstring"""




     global buffer_space, params_space, machine_time, K, m, t

     # PRNG (Xorshift by George Marsaglia)
     def xorshift(_UpperCamelCase:					Tuple      ,		_UpperCamelCase:					Dict					):
          x ^= y >> 13
          y ^= x << 17
          x ^= y >> 5
          return x

     # Choosing Dynamical Systems (Increment)
     _snake_case							=   machine_time % m

     # Evolution (Time Length)
     for _ in range(0      ,		_UpperCamelCase					):
          # Variables (Position + Parameters)
          _snake_case							=   params_space[key]
          _snake_case							=   buffer_space[key]

          # Modification (Transition Function) - Flow
          _snake_case							=   round(float(r * value * (1 - value)					)      ,		10					)
          _snake_case							=   (machine_time * 0.01 + r * 1.01) % 1 + 3

     # Choosing Chaotic Data
     _snake_case							=   int(buffer_space[(key + 2) % m] * (10**10)					)
     _snake_case							=   int(buffer_space[(key - 2) % m] * (10**10)					)

     # Machine Time
     machine_time += 1

     return xorshift(_UpperCamelCase      ,		_UpperCamelCase					) % 0Xf_f_f_f_f_f_f_f





def 			__a			(     )		->				Optional[int]:

     """simple docstring"""




     global buffer_space, params_space, machine_time, K, m, t

     _snake_case							=   K
     _snake_case							=   [0] * m
     _snake_case							=   0


if __name__ == "__main__":
   # Initialization
   reset()

   # Pushing Data (Input)
   import random

   UpperCamelCase_		:    int									=		random.sample(range(0Xffffffff), 100)
   for chunk in message:
      push(chunk)

   # for controlling
   UpperCamelCase_		:    Union[str, Any]									=		''''''

   # Pulling Data (Output)
   while inp in ("e", "E"):
      print(F'{format(pull(), "#04x")}')
      print(buffer_space)
      print(params_space)
      UpperCamelCase_		:    List[Any]									=		input('''(e)exit? ''').strip()








'''simple docstring'''





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


UpperCamelCase_		:    List[str]									=		500000

UpperCamelCase_			,			UpperCamelCase_		:    Dict									=		os.path.split(__file__)
UpperCamelCase_		:    int									=		os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.select(range(0      ,		len(_UpperCamelCase					)      ,		2					)					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.sort("numbers"					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.shuffle()





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				Any:

     """simple docstring"""




     _snake_case							=   dataset.train_test_split(0.1					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset      ,		_UpperCamelCase:					int=10					)		->				List[str]:

     """simple docstring"""




     for shard_id in range(_UpperCamelCase					):
          _snake_case							=   dataset.shard(_UpperCamelCase      ,		_UpperCamelCase					)





def 			__a			(     )		->				int:

     """simple docstring"""




     _snake_case							=   {"num examples": SPEED_TEST_N_EXAMPLES}
     _snake_case							=   (select, sort, shuffle, train_test_split, shard)
     with tempfile.TemporaryDirectory() as tmp_dir:
          print("generating dataset"					)
          _snake_case							=   datasets.Features({"text": datasets.Value("string"					), "numbers": datasets.Value("float32"					)}					)
          _snake_case							=   generate_example_dataset(
              os.path.join(_UpperCamelCase      ,		"dataset.arrow"					)      ,		_UpperCamelCase      ,		num_examples=_UpperCamelCase					)
          print("Functions"					)
          for func in functions:
               print(func.__name__					)
               _snake_case							=   func(_UpperCamelCase					)

     with open(_UpperCamelCase      ,		"wb"					) as f:
          f.write(json.dumps(_UpperCamelCase					).encode("utf-8"					)					)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_indices_mapping()


