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

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

# Machine Time
_lowerCamelCase        =0





def    _a (						lowerCamelCase							):
 global buffer_space, params_space, machine_time, K, m, t

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

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

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

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

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

 # Machine Time
 machine_time += 1





def    _a (						):
 global buffer_space, params_space, machine_time, K, m, t

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

 # Choosing Dynamical Systems (Increment)
 lowerCamelCase		:     Dict          =				machine_time % m

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

  # Modification (Transition Function) - Flow
  lowerCamelCase		:     Union[str, Any]          =				round(float(r * value * (1 - value)							),     10							)
  lowerCamelCase		:     Optional[int]          =				(machine_time * 0.0_1 + r * 1.0_1) % 1 + 3

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

 # Machine Time
 machine_time += 1

 return xorshift(lowerCamelCase,     lowerCamelCase							) % 0xf_f_f_f_f_f_f_f





def    _a (						):
 global buffer_space, params_space, machine_time, K, m, t

 lowerCamelCase		:     Any          =				K
 lowerCamelCase		:     Optional[Any]          =				[0] * m
 lowerCamelCase		:     Optional[int]          =				0


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

      # Pushing Data (Input)
      import random

      _lowerCamelCase        =random.sample(range(0xffff_ffff), 1_0_0)
      for chunk in message:
            push(chunk)

      # for controlling
      _lowerCamelCase        =""""""

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






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


_lowerCamelCase        ={
    """configuration_tvlt""": ["""TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TvltConfig"""],
    """feature_extraction_tvlt""": ["""TvltFeatureExtractor"""],
    """processing_tvlt""": ["""TvltProcessor"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase        =[
          """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TvltModel""",
          """TvltForPreTraining""",
          """TvltForAudioVisualClassification""",
          """TvltPreTrainedModel""",
      ]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase        =["""TvltImageProcessor"""]


if TYPE_CHECKING:
      from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
      from .processing_tvlt import TvltProcessor
      from .feature_extraction_tvlt import TvltFeatureExtractor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tvlt import (
                TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TvltForAudioVisualClassification,
                TvltForPreTraining,
                TvltModel,
                TvltPreTrainedModel,
            )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_tvlt import TvltImageProcessor


else:
      import sys

      _lowerCamelCase        =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




