
from random import randint, random



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__ = False				,    lowerCAmelCase__ = False				,    lowerCAmelCase__ = 5				,    ):
     '''simple docstring'''
     lowercase					=		[[-1] * number_of_cells]  # Create a highway without any car
     lowercase					=		0
     lowercase					=		max(__A				,    0	)
     while i < number_of_cells:
          lowercase					=		(
              randint(0				,    __A	) if random_speed else initial_speed
          )  # Place the cars
          i += (
              randint(1				,    max_speed * 2	) if random_frequency else frequency
          )  # Arbitrary number, may need tuning
     return highway



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		0
     lowercase					=		highway_now[car_index + 1 :]
     for cell in range(len(__A	)	):  # May need a better name for this
          if cells[cell] != -1:  # If the cell is not empty then
               return distance  # we have the distance we wanted
          distance += 1
     # Here if the car is near the end of the highway
     return distance + get_distance(__A				,    -1	)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		len(__A	)
     # Beforce calculations, the highway is empty
     lowercase					=		[-1] * number_of_cells

     for car_index in range(__A	):
          if highway_now[car_index] != -1:
               # Add 1 to the current speed of the car and cap the speed
               lowercase					=		min(highway_now[car_index] + 1				,    __A	)
               # Number of empty cell before the next car
               lowercase					=		get_distance(__A				,    __A	) - 1
               # We can't have the car causing an accident
               lowercase					=		min(next_highway[car_index]				,    __A	)
               if random() < probability:
                    # Randomly, a driver will slow down
                    lowercase					=		max(next_highway[car_index] - 1				,    0	)
     return next_highway



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__	):
     '''simple docstring'''
     lowercase					=		len(highway[0]	)

     for i in range(__A	):
          lowercase					=		update(highway[i]				,    __A				,    __A	)
          lowercase					=		[-1] * number_of_cells

          for car_index in range(__A	):
               lowercase					=		next_speeds_calculated[car_index]
               if speed != -1:
                    # Change the position based on the speed (with % to create the loop)
                    lowercase					=		(car_index + speed) % number_of_cells
                    # Commit the change of position
                    lowercase					=		speed
          highway.append(__A	)

     return highway


if __name__ == "__main__":
       import doctest

       doctest.testmod()






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase__	:Tuple										=					{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	:Union[str, Any]										=					[
							    "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "BioGptForCausalLM",
							    "BioGptForTokenClassification",
							    "BioGptForSequenceClassification",
							    "BioGptModel",
							    "BioGptPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
							from .tokenization_biogpt import BioGptTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_biogpt import (
														    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BioGptForCausalLM,
														    BioGptForSequenceClassification,
														    BioGptForTokenClassification,
														    BioGptModel,
														    BioGptPreTrainedModel,
														)


else:
							import sys

							lowercase__	:Any										=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




