


_snake_case					=					[0.33, 0.44, 0.55, 0.44, 0.33]
_snake_case					=					3
_snake_case					=					5

# Buffer Space (with Parameters Space)
_snake_case					=					[]
_snake_case					=					[]

# Machine Time
_snake_case					=					0






def 		lowercase_(  SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

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

  # Choosing Dynamical Systems (All)
  for key, value in enumerate(SCREAMING_SNAKE_CASE_     ):
    # Evolution Parameter
    lowerCamelCase			: Union[str, Any]   =    float(seed / value     )

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

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

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

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

  # Machine Time
  machine_time += 1






def 		lowercase_(  ):


  '''simple docstring'''

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

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

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

  # Evolution (Time Length)
  for _ in range(0				,						SCREAMING_SNAKE_CASE_     ):
    # Variables (Position + Parameters)
    lowerCamelCase			: Dict   =    params_space[key]
    lowerCamelCase			: List[Any]   =    buffer_space[key]

    # Modification (Transition Function) - Flow
    lowerCamelCase			: Tuple   =    round(float(r * value * (1 - value)     )				,						10     )
    lowerCamelCase			: Union[str, Any]   =    (machine_time * 0.01 + r * 1.01) % 1 + 3

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

  # Machine Time
  machine_time += 1

  return xorshift(SCREAMING_SNAKE_CASE_				,						SCREAMING_SNAKE_CASE_     ) % 0xFFFFFFFF






def 		lowercase_(  ):


  '''simple docstring'''

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

  lowerCamelCase			: Tuple   =    K
  lowerCamelCase			: str   =    [0] * m
  lowerCamelCase			: str   =    0


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

       # Pushing Data (Input)
       import random

       _snake_case					=					random.sample(range(0XF_F_F_F_F_F_F_F), 1_00)
       for chunk in message:
              push(chunk)

       # for controlling
       _snake_case					=					''''''

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







import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast
@require_vision
class      UpperCAmelCase_ ( unittest.TestCase   ):

   '''simple docstring'''




   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Tuple   =    tempfile.mkdtemp()

     lowerCamelCase			: List[Any]   =    CLIPImageProcessor()
     lowerCamelCase			: str   =    BertTokenizer.from_pretrained(
         "hf-internal-testing/tiny-random-BertModel"						,    model_input_names=["input_ids", "attention_mask"]			)

     lowerCamelCase			: List[str]   =    GitProcessor(__A						,    __A			)

     processor.save_pretrained(self.tmpdirname			)






   def _snake_case   (		self						,    **__A			):






     """simple docstring"""





     return AutoProcessor.from_pretrained(self.tmpdirname						,    **__A			).tokenizer






   def _snake_case   (		self						,    **__A			):






     """simple docstring"""





     return AutoProcessor.from_pretrained(self.tmpdirname						,    **__A			).image_processor






   def _snake_case   (		self			):






     """simple docstring"""





     shutil.rmtree(self.tmpdirname			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: str   =    [np.random.randint(255						,    size=(3, 30, 400)						,    dtype=np.uinta			)]

     lowerCamelCase			: Any   =    [Image.fromarray(np.moveaxis(__A						,    0						,    -1			)			) for x in image_inputs]

     return image_inputs






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Tuple   =    GitProcessor(tokenizer=self.get_tokenizer()						,    image_processor=self.get_image_processor()			)
     processor.save_pretrained(self.tmpdirname			)

     lowerCamelCase			: Optional[Any]   =    self.get_tokenizer(bos_token="(BOS)"						,    eos_token="(EOS)"			)
     lowerCamelCase			: List[str]   =    self.get_image_processor(do_normalize=__A						,    padding_value=1.0			)

     lowerCamelCase			: Dict   =    GitProcessor.from_pretrained(
         self.tmpdirname						,    bos_token="(BOS)"						,    eos_token="(EOS)"						,    do_normalize=__A						,    padding_value=1.0			)

     self.assertEqual(processor.tokenizer.get_vocab()						,    tokenizer_add_kwargs.get_vocab()			)
     self.assertIsInstance(processor.tokenizer						,    __A			)

     self.assertEqual(processor.image_processor.to_json_string()						,    image_processor_add_kwargs.to_json_string()			)
     self.assertIsInstance(processor.image_processor						,    __A			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Any   =    self.get_image_processor()
     lowerCamelCase			: Optional[int]   =    self.get_tokenizer()

     lowerCamelCase			: Optional[Any]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: List[str]   =    self.prepare_image_inputs()

     lowerCamelCase			: str   =    image_processor(__A						,    return_tensors="np"			)
     lowerCamelCase			: Union[str, Any]   =    processor(images=__A						,    return_tensors="np"			)

     for key in input_feat_extract.keys():
       self.assertAlmostEqual(input_feat_extract[key].sum()						,    input_processor[key].sum()						,    delta=1e-2			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: int   =    self.get_image_processor()
     lowerCamelCase			: Dict   =    self.get_tokenizer()

     lowerCamelCase			: Optional[int]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: int   =    "lower newer"

     lowerCamelCase			: str   =    processor(text=__A			)

     lowerCamelCase			: Union[str, Any]   =    tokenizer(__A						,    return_token_type_ids=__A			)

     for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]						,    encoded_processor[key]			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Dict   =    self.get_image_processor()
     lowerCamelCase			: Optional[int]   =    self.get_tokenizer()

     lowerCamelCase			: List[str]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: str   =    "lower newer"
     lowerCamelCase			: Tuple   =    self.prepare_image_inputs()

     lowerCamelCase			: str   =    processor(text=__A						,    images=__A			)

     self.assertListEqual(list(inputs.keys()			)						,    ["input_ids", "attention_mask", "pixel_values"]			)

     # test if it raises when no input is passed
     with pytest.raises(__A			):
       processor()






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Union[str, Any]   =    self.get_image_processor()
     lowerCamelCase			: Tuple   =    self.get_tokenizer()

     lowerCamelCase			: Tuple   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: Optional[Any]   =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     lowerCamelCase			: str   =    processor.batch_decode(__A			)
     lowerCamelCase			: int   =    tokenizer.batch_decode(__A			)

     self.assertListEqual(__A						,    __A			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[Any]   =    self.get_image_processor()
     lowerCamelCase			: int   =    self.get_tokenizer()

     lowerCamelCase			: Optional[int]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: Optional[Any]   =    "lower newer"
     lowerCamelCase			: List[Any]   =    self.prepare_image_inputs()

     lowerCamelCase			: Optional[int]   =    processor(text=__A						,    images=__A			)

     # For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
     self.assertListEqual(list(inputs.keys()			)						,    ["input_ids", "attention_mask", "pixel_values"]			)



