
"""simple docstring"""







from random import randint, random
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase = False ,						_UpperCamelCase = False ,						_UpperCamelCase = 5 ,						):
	__lowerCAmelCase    :		Tuple		    =   [[-1] * number_of_cells]  # Create a highway without any car
	__lowerCAmelCase    :		Union[str, Any]		    =   0
	__lowerCAmelCase    :		List[str]		    =   max(_UpperCamelCase ,						0	)
	while i < number_of_cells:
		__lowerCAmelCase    :		str		    =   (
		    randint(0 ,						_UpperCamelCase	) 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       (_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		Dict		    =   0
	__lowerCAmelCase    :		int		    =   highway_now[car_index + 1 :]
	for cell in range(len(_UpperCamelCase	)	):  # 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(_UpperCamelCase ,						-1	)
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		List[str]		    =   len(_UpperCamelCase	)
	# Beforce calculations, the highway is empty
	__lowerCAmelCase    :		Tuple		    =   [-1] * number_of_cells

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

	for i in range(_UpperCamelCase	):
		__lowerCAmelCase    :		Union[str, Any]		    =   update(highway[i] ,						_UpperCamelCase ,						_UpperCamelCase	)
		__lowerCAmelCase    :		Optional[int]		    =   [-1] * number_of_cells

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

	return highway


if __name__ == "__main__":
							import doctest

							doctest.testmod()

"""simple docstring"""







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 					__lowerCAmelCase       ():
	__lowerCAmelCase    :		Tuple		    =   HfArgumentParser(_UpperCamelCase	)
	__lowerCAmelCase    :		Optional[Any]		    =   parser.parse_args_into_dataclasses()[0]
	__lowerCAmelCase    :		int		    =   TensorFlowBenchmark(args=_UpperCamelCase	)
	try:
		__lowerCAmelCase    :		Dict		    =   parser.parse_args_into_dataclasses()[0]
	except ValueError as e:
		__lowerCAmelCase    :		List[Any]		    =   'Arg --no_{0} is no longer used, please use --no-{0} instead.'
		__lowerCAmelCase    :		Union[str, Any]		    =   ' '.join(str(_UpperCamelCase	).split(' '	)[:-1]	)
		__lowerCAmelCase    :		List[str]		    =   ''
		__lowerCAmelCase    :		Any		    =   eval(str(_UpperCamelCase	).split(' '	)[-1]	)
		__lowerCAmelCase    :		Dict		    =   []
		for arg in depreciated_args:
			# arg[2:] removes '--'
			if arg[2:] in TensorFlowBenchmark.deprecated_args:
				# arg[5:] removes '--no_'
				full_error_msg += arg_error_msg.format(arg[5:]	)
			else:
				wrong_args.append(_UpperCamelCase	)
		if len(_UpperCamelCase	) > 0:
			__lowerCAmelCase    :		Any		    =   full_error_msg + begin_error_msg + str(_UpperCamelCase	)
		raise ValueError(_UpperCamelCase	)
	benchmark.run()


if __name__ == "__main__":
							main()