






from random import randint, random






def 				lowerCamelCase__      (    __lowerCamelCase			:     Optional[int]  ,		__lowerCamelCase			:     Union[str, Any]  ,		__lowerCamelCase			:     Optional[Any]  ,		__lowerCamelCase			:     List[str] = False  ,		__lowerCamelCase			:     int = False  ,		__lowerCamelCase			:     Tuple = 5  ,		):
  __UpperCAmelCase							:	Dict           =  [[-1] * number_of_cells]  # Create a highway without any car
  __UpperCAmelCase							:	Dict           =  0
  __UpperCAmelCase							:	List[Any]           =  max(__lowerCamelCase  ,		0		)
  while i < number_of_cells:
    __UpperCAmelCase							:	Optional[Any]           =  (
        randint(0  ,		__lowerCamelCase		) 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 				lowerCamelCase__      (    __lowerCamelCase			:     int  ,		__lowerCamelCase			:     Union[str, Any]		):
  __UpperCAmelCase							:	Tuple           =  0
  __UpperCAmelCase							:	Union[str, Any]           =  highway_now[car_index + 1 :]
  for cell in range(len(__lowerCamelCase		)		):  # 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(__lowerCamelCase  ,		-1		)






def 				lowerCamelCase__      (    __lowerCamelCase			:     Tuple  ,		__lowerCamelCase			:     Tuple  ,		__lowerCamelCase			:     List[str]		):
  __UpperCAmelCase							:	List[Any]           =  len(__lowerCamelCase		)
  # Beforce calculations, the highway is empty
  __UpperCAmelCase							:	int           =  [-1] * number_of_cells

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






def 				lowerCamelCase__      (    __lowerCamelCase			:     Tuple  ,		__lowerCamelCase			:     Dict  ,		__lowerCamelCase			:     int  ,		__lowerCamelCase			:     List[str]		):
  __UpperCAmelCase							:	Union[str, Any]           =  len(highway[0]		)

  for i in range(__lowerCamelCase		):
    __UpperCAmelCase							:	Tuple           =  update(highway[i]  ,		__lowerCamelCase  ,		__lowerCamelCase		)
    __UpperCAmelCase							:	Optional[int]           =  [-1] * number_of_cells

    for car_index in range(__lowerCamelCase		):
      __UpperCAmelCase							:	List[str]           =  next_speeds_calculated[car_index]
      if speed != -1:
        # Change the position based on the speed (with % to create the loop)
        __UpperCAmelCase							:	Union[str, Any]           =  (car_index + speed) % number_of_cells
        # Commit the change of position
        __UpperCAmelCase							:	Dict           =  speed
    highway.append(__lowerCamelCase		)

  return highway


if __name__ == "__main__":
       import doctest

       doctest.testmod()




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase					: Union[str, Any]      =       {
    "configuration_instructblip": [
        "INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InstructBlipConfig",
        "InstructBlipQFormerConfig",
        "InstructBlipVisionConfig",
    ],
    "processing_instructblip": ["InstructBlipProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase					: List[Any]      =       [
					    "INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "InstructBlipQFormerModel",
					    "InstructBlipPreTrainedModel",
					    "InstructBlipForConditionalGeneration",
					    "InstructBlipVisionModel",
					]

if TYPE_CHECKING:
					from .configuration_instructblip import (
					    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    InstructBlipConfig,
					    InstructBlipQFormerConfig,
					    InstructBlipVisionConfig,
					)
					from .processing_instructblip import InstructBlipProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_instructblip import (
										    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    InstructBlipForConditionalGeneration,
										    InstructBlipPreTrainedModel,
										    InstructBlipQFormerModel,
										    InstructBlipVisionModel,
										)

else:
					import sys

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