
from __future__ import annotations







def        A__					(						lowerCamelCase     ,    lowerCamelCase     ,    lowerCamelCase     ,    lowerCamelCase     ,    lowerCamelCase     ,    )  ->	None:
				UpperCamelCase_:							int	=						len(SCREAMING_SNAKE_CASE_						)

				# If row is equal to the size of the board it means there are a queen in each row in
				# the current board (possible_board)
				if row == n:
								# We convert the variable possible_board that looks like this: [1, 3, 0, 2] to
								# this: ['. Q . . ', '. . . Q ', 'Q . . . ', '. . Q . ']
								boards.append([""". """ * i + """Q """ + """. """ * (n - 1 - i) for i in possible_board]						)
								return

				# We iterate each column in the row to find all possible results in each row
				for col in range(SCREAMING_SNAKE_CASE_						):
								# We apply that we learned previously. First we check that in the current board
								# (possible_board) there are not other same value because if there is it means
								# that there are a collision in vertical. Then we apply the two formulas we
								# learned before:
								#
								# 45º: y - x = b or 45: row - col = b
								# 135º: y + x = b or row + col = b.
								#
								# And we verify if the results of this two formulas not exist in their variables
								# respectively.  (diagonal_right_collisions, diagonal_left_collisions)
								#
								# If any or these are True it means there is a collision so we continue to the
								# next value in the for loop.
								if (
								    col in possible_board
								    or row - col in diagonal_right_collisions
								    or row + col in diagonal_left_collisions
								):
												continue

								# If it is False we call dfs function again and we update the inputs
								depth_first_search(
								    [*possible_board, col]     ,    [*diagonal_right_collisions, row - col]     ,    [*diagonal_left_collisions, row + col]     ,    SCREAMING_SNAKE_CASE_     ,    SCREAMING_SNAKE_CASE_     ,    )







def        A__					(						lowerCamelCase						)  ->	None:
				UpperCamelCase_:							list[list[str]]	=						[]
				depth_first_search([]     ,    []     ,    []     ,    SCREAMING_SNAKE_CASE_     ,    SCREAMING_SNAKE_CASE_						)

				# Print all the boards
				for board in boards:
								for column in board:
												print(SCREAMING_SNAKE_CASE_						)
								print(""""""						)

				print(len(SCREAMING_SNAKE_CASE_						)     ,    """solutions were found."""						)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							n_queens_solution(4)








lowerCamelCase_						: Optional[Any]         =  """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

lowerCamelCase_						: Union[str, Any]         =  [{"""type""": """code""", """content""": INSTALL_CONTENT}]
lowerCamelCase_						: Optional[Any]         =  {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}






