


"""simple docstring"""






SCREAMING_SNAKE_CASE__				:  int						= [0.3_3, 0.4_4, 0.5_5, 0.4_4, 0.3_3]
SCREAMING_SNAKE_CASE__				:  Union[str, Any]						= 3
SCREAMING_SNAKE_CASE__				:  Tuple						= 5

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

# Machine Time
SCREAMING_SNAKE_CASE__				:  Any						= 0




def        A_					(					UpperCAmelCase__				)     ->     Optional[int]:
   global buffer_space, params_space, machine_time, K, m, t

   # Choosing Dynamical Systems (All)
   for key, value in enumerate(UpperCAmelCase__				):
      # Evolution Parameter
      a   :	List[Any]						=    float(seed / value				)

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

      # Control Theory: Trajectory Change
      a   :	Union[str, Any]						=    (params_space[key] + e) % 1 + 3

      # Modification (Transition Function) - Jumps
      a   :	List[Any]						=    round(float(r * value * (1 - value)				)       ,   10				)
      a   :	List[str]						=    r  # Saving to Parameters Space

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

   # Machine Time
   machine_time += 1




def        A_					(					)     ->     List[Any]:
   global buffer_space, params_space, machine_time, K, m, t

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

   # Choosing Dynamical Systems (Increment)
   a   :	List[Any]						=    machine_time % m

   # Evolution (Time Length)
   for _ in range(0       ,   UpperCAmelCase__				):
      # Variables (Position + Parameters)
      a   :	Dict						=    params_space[key]
      a   :	str						=    buffer_space[key]

      # Modification (Transition Function) - Flow
      a   :	Any						=    round(float(r * value * (1 - value)				)       ,   10				)
      a   :	int						=    (machine_time * 0.0_1 + r * 1.0_1) % 1 + 3

   # Choosing Chaotic Data
   a   :	List[str]						=    int(buffer_space[(key + 2) % m] * (10**10)				)
   a   :	int						=    int(buffer_space[(key - 2) % m] * (10**10)				)

   # Machine Time
   machine_time += 1

   return xorshift(UpperCAmelCase__       ,   UpperCAmelCase__				) % 0Xffffffff




def        A_					(					)     ->     str:
   global buffer_space, params_space, machine_time, K, m, t

   a   :	int						=    K
   a   :	Dict						=    [0] * m
   a   :	Union[str, Any]						=    0


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

 # Pushing Data (Input)
 import random

 SCREAMING_SNAKE_CASE__				:  Dict						= random.sample(range(0xFFFFFFFF), 100)
 for chunk in message:
  push(chunk)

 # for controlling
 SCREAMING_SNAKE_CASE__				:  Any						= ""

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









"""simple docstring"""






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property


class 	A_       (     unittest.TestCase   ):





  """simple docstring"""

  @cached_property
  def 							lowercase_     (						self						)				->					Optional[Any]:
     return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'						)
  @cached_property
  def 							lowercase_     (						self						)				->					Optional[int]:
     return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'						)
  def 							lowercase_     (						self						)				->					Union[str, Any]:
     a   :	List[Any]						=    self.tokenizer_ab
     a   :	int						=    ' I am a small frog.'
     a   :	Any						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	List[str]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Optional[Any]:
     a   :	Optional[int]						=    self.rust_tokenizer_ab
     a   :	List[Any]						=    ' I am a small frog.'
     a   :	Union[str, Any]						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	Optional[Any]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Tuple:
     assert self.tokenizer_ab.add_prefix_space
     assert self.tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]






  def 							lowercase_     (						self						)				->					Tuple:
     assert self.rust_tokenizer_ab.add_prefix_space
     assert self.rust_tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]





